Patent Publication Number: US-2023144532-A1

Title: Automatic span context propagation to worker threads in rich-client applications

Description:
CROSS-REFERENCES TO RELATED APPLICATIONS 
     The present application is a continuation of U.S. application Ser. No. 17/339,673, entitled “AUTOMATIC SPAN CONTEXT PROPAGATION TO WORKER THREADS IN RICH-CLIENT APPLICATIONS,” filed Jun. 4, 2021, which claims the benefit and priority of U.S. Provisional Application No. 63/077,649, entitled “TELEMETRY FOR VISUAL BUILDER,” filed Sep. 13, 2020, which are hereby incorporated by reference in their entirety for all purposes. 
     This application is related to co-pending U.S. patent application Ser. No. 17/339,676 entitled “OUT-OF-THE-BOX TELEMETRY FOR RICH-CLIENT APPLICATION RUNTIME FRAMEWORKS,” filed Jun. 4, 2021; co-pending U.S. patent application Ser. No. 17/339,682 entitled “SMART DISTRIBUTED TRACING CONTEXT INJECTION,” filed Jun. 4, 2021, and co-pending U.S. patent application Ser. No. 17/339,680 titled “SMART SPAN PRIORITIZATION BASED ON INGESTION SERVICE BACKPRESSURE,” filed Jun. 4, 2021, the contents of which are hereby incorporated by reference in their entirety for all purposes. 
    
    
     BACKGROUND 
     As web-based applications become more advanced, traditional tracer applications may be unable to capture accurate telemetry data across servers, platforms, or threads. Disclosed solutions facilitate improved telemetry capabilities and analytics that overcome these deficiencies. 
     BRIEF SUMMARY 
     A method of tracing a subsidiary thread of a web page application includes providing a web page application to a web browser on a client device. The method further includes creating, from the web page application, a global tracer configured to log tracing data for the web page application and a span. The span represents one or more of: (i) a number of processing cycles corresponding to an execution of operations corresponding to the web page application or (ii) an execution time of the operations corresponding to the web page application. The method further includes instantiating, from the web page application, a wrapper for a subsidiary thread. The wrapper configured to execute shim code before executing the subsidiary thread. The method further includes passing, from the wrapper to the shim code, configuration data of the global tracer. The method further includes creating, from the shim code and the configuration data, a subsidiary tracer. The subsidiary tracer configured to log tracing data for the subsidiary thread and a thread span that represents one or more of (i) a number of processing cycles corresponding to an execution of operations corresponding to the subsidiary thread or (ii) an execution time of the operations corresponding to the subsidiary thread. 
     In an aspect, the method further includes automatically logging a start of the thread span. The method further includes executing, via the shim code, the operations corresponding to the subsidiary thread. The method further includes automatically logging an end of the thread span based upon a completion of the operations corresponding to the subsidiary thread. The method further includes returning the thread span via the shim code to the wrapper. 
     In an aspect, the method further includes automatically logging a start of the span. The method further includes executing the operations corresponding to the web page application. The method further includes automatically logging an end of the span based upon a completion of the operations corresponding to the web page application. The method further includes associating the span and the thread span as a hierarchy. 
     In an aspect, the method further includes sending, from the web page application via wrapper to the subsidiary tracer, a first message. The method further includes receiving, from the subsidiary tracer and the wrapper, a second message generated by the subsidiary thread in response to the first message. 
     In an aspect, the method further includes determining a successful completion of the subsidiary thread. The method further includes returning an indication of the successful completion of the subsidiary thread via the shim code to the wrapper responsive to determining the successful completion. 
     In an aspect, the web page application includes JavaScript and the subsidiary thread is a web worker thread. 
     In an aspect, the method further includes detecting an event initiated by interaction with the web page application. The thread span represents determining an action to perform based on the event. The method further includes executing the operations corresponding to the subsidiary thread occurs responsive to detecting the event. The operations correspond to the subsidiary thread implement the action. 
     In an aspect, the method further includes determining that the priority is outside a priority tolerance. The method further include, based on determining that the priority is outside a priority tolerance, identifying the span as a proxy span. Identifying the span as the proxy span causes the global tracer to not log information based on the execution of the operations corresponding to the web page application. 
     The above methods can be implemented as tangible computer-readable media and/or operating within a computer processor and attached memory. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    depicts an example of a system for automatically instrumenting enterprise applications with telemetry, according to an aspect of the present disclosure. 
         FIG.  2    depicts an example of a process used to gather telemetry data, according to an aspect of the present disclosure. 
         FIG.  3    depicts an example of an instrumented application for generating span context, according to certain aspects of the disclosure. 
         FIG.  4    depicts an example of a span hierarchy, according to an aspect of the present disclosure. 
         FIG.  5    depicts tracer components within an instrumented application that are used to generate span context and logs, according to certain aspects of the disclosure. 
         FIG.  6    depicts an example of a tracing architecture used to manage backpressure caused by instrumentation of spans, according to certain aspects of the disclosure. 
         FIG.  7    depicts an example of a span hierarchy with prioritization, according to certain aspects of the disclosure. 
         FIG.  8    depicts an example of a process for prioritizing spans, according to certain aspects of the disclosure. 
         FIG.  9    depicts an example of a distributing tracing environment with a traceworker client, according to certain aspects of the disclosure. 
         FIG.  10    depicts an example of a process for instrumenting threads, according to certain aspects of the disclosure. 
         FIG.  11    depicts an example of a process for propagating tracing across a distributed software application, according to certain aspects of the disclosure. 
         FIG.  12    depicts an example of propagating span context across a service in a distributed system, according to certain aspects of the disclosure. 
         FIG.  13    depicts an example of headers, according to certain aspects of the disclosure. 
         FIG.  14    depicts a simplified diagram of a distributed system for implementing one of the aspects. 
         FIG.  15    is a simplified block diagram of components of a system environment by which services provided by the components of an aspect system may be offered as cloud services in accordance with an aspect. 
         FIG.  16    illustrates an exemplary computing subsystem, in which various aspects of the present invention may be implemented. 
     
    
    
     DETAILED DESCRIPTION 
     Techniques disclosed herein provide solutions for automatically providing telemetry capabilities for enterprise applications. Telemetry refers to gathering of reporting performance data about the runtime execution of software. Examples of such data include how often certain features on a web page or application are used, measurements of start-up time or execution time, whether a process crashed, failure information, and user experiences. Telemetry data can be gathered on an application basis, or on a more granular level, such as runtime metrics on how long each process of the web page took to complete. Disclosed solutions use Application Programmer Interface (API) capabilities to enable access to the telemetry data. 
     As discussed, existing solutions suffer from deficiencies. For instance, some existing solutions may require a manual importing or linking of a tracing library followed by adding of one or more function calls around parts of code on which instrumentation data is desired. Additionally, such solutions can require developers to select instrumentation libraries from one or more vendors and configure those libraries. By contrast, disclosed solutions automatically instrument web-based applications by detecting events and calls to servers in code and automatically instrumenting those events. 
     In an aspect, disclosed systems can automatically instrument an enterprise application without requiring input from a software developer. Certain aspects of the present disclosure relate to software development tools that provide a runtime telemetry framework that can be automatically integrated into a custom application designed by a software developer. For example, software development tools can automatically inject tracing functionality into an enterprise application. The tracing functionality automatically track operations such as user interactions, page navigation, and server calls and groups related logical transactions together in such a way as to enable end-to-end tracing from a click of a user on a web page, including a distributed server system (heterogeneous or otherwise) that implements back-end services. 
     In another aspect, disclosed systems enable the prioritization of one or more spans and messages relating to the spans to minimize network congestion caused in some cases by a high amount of instrumentation data. For instance, at runtime or before, a particular span can be designated lower priority, which causes the instrumentation to not measure performance of the particular span while still gathering data for child spans, which may be of greater interest to a developer. 
     In yet another aspect, disclosed solutions involve enabling developers of web-based applications can obtain detailed instrumentation about one or more processes executing as part of the enterprise application, regardless of whether the processes include multiple threads. At runtime execution of the application, the telemetry framework facilitates instrumentation across various processes, threads, and servers. In this manner, the instrumentation context is maintained across threads, resulting in more granular instrumentation data. 
     In another aspect, disclosed systems facilitate telemetry across a distributed system, including on distributed servers that, due to security requirements or for other reasons, may not automatically permit instrumentation indicated by way of tracing headers. More specifically, certain aspects can automatically discover protocol support and adjust injection of tracing information into different calls based on protocol support. Disclosed systems are therefore able to obtain detailed telemetry data for processes that execute on remote servers, and in particular, remote servers that are accessed by a cross-domain request. Such servers can be operated by different entities in different domains. 
       FIG.  1    depicts an example of a system for automatically instrumenting enterprise applications with telemetry, according to an aspect of the present disclosure.  FIG.  1    depicts developer computing device  110 , end user computing device  130 , network  150 , and servers  140   a - n . In the example depicted in  FIG.  1   , developer computing device  110  builds instrumented application  120  and deploys instrumented application  120  to server  140   a . Server  140   a , in turn, serves the application to end user computing device  140 . An example of a process used by an instrumented application to obtain telemetry data is shown in  FIG.  2   . An example of an instrumented application is shown in  FIG.  3   . Examples of suitable computing devices for developer computing device  110  and end user computing device  140  include those depicted in client computing devices  1402 ,  1404 ,  1406 , and  1408  and examples of suitable servers include server  1412 , are depicted in  FIG.  14   . 
     During or in connection with the execution of instrumented application  120 , end user computing device  140  may connect with one or more servers  140   b - n  to obtain different resources (e.g., images, scripts, etc.) and/or perform instrumentation functions. During or after execution of the instrumented application  120 , telemetry data  122  is communicated back to developer computing device  110  for analysis. 
     Developer computing device  110  includes one or more of developer integrated development environment (IDE)  112 , back-end developer tools  114 , console  116 , and telemetry data  122 . Developer IDE  112  is a graphical development tool that provides compiling, linking, debugging, tracing, or other functionality. Back-end developer tools  114  can include one or more compilers, linkers, debuggers, simulators, and so forth. Console  116  is used to view telemetry data  122  obtained by the execution of instrumented application  120 . 
     As depicted, telemetry data  122  includes data that a particular web page executed on “server 1” and took 0.5 seconds, an image load executed on “server 2” and took 0.4 seconds, and a button click caused 0.2 seconds of processing. 
     Servers  140   a - n  can be configured to perform identical, similar, or different functions. For example, servers  140   a - n  can operate as a distributed server system. In another example, servers  140   a - n  can be web-servers, file servers, or other servers that serve one or more components from web pages or can receive database queries and provide results. In some cases, servers  140   a - n  can be under the control of different entities (companies or individuals) and/or at different locations. Accordingly, certain aspects described herein relate to obtaining telemetry data across different servers via span context propagation. Developer computing device  110 , end user computing device  140 , network  150 , and servers  140   a - n  can be connected across one or more connections such as network  150 . Examples of network  150  include wired networks, wireless networks, and the Internet. 
     End user computing device  130  includes web application  134  (e.g., a web page), web browser  132 , and tracer application  136 . Web application  134  can be rendered by web browser  132 . Tracer application  136 , which can be part of web application  134 , provides instrumentation capabilities. For instance, tracer application  136  collects telemetry data, which can be exported to an external device periodically or on-demand. Examples of telemetry data include how often certain features are used, measurements of start-up time or execution time, whether a process crashed, failure information, and user types. 
     In an example, a software developer builds a custom web-based application using developer IDE  112  and back-end developer tools  114 . In particular, software tools running on developer computing device  110  insert code (e.g., tracer code) that provides telemetry capability, generating instrumented application  120 . In some cases, instrumented application  120  can be sent directly from developer computing device  110  to end user computing device  140 . In other cases, instrumented application  120  is sent directly to a server  140   a - n , where instrumented application  120  is hosted and later downloaded by end user computing device  140 . 
     End user computing device  140  accesses the application, for example, from server  140   a  across network  150 . A user operating end user computing device  140  interacts with the application, which causes the end user computing device  140  to access one or more of servers  140   a - n , which, in turn, serve all or part of the application to the end user computing device  140 . End user computing device  140  executes the telemetry functionality, which causes operations caused directly by user interactions with the application (e.g., clicks, reloads) or indirectly (e.g., images linked from a page to be loaded, etc.) to be instrumented. In this manner, more detailed telemetry information is available than with previous solutions. The telemetry data  122  is gathered by one or more servers  140   a - n.    
     As discussed, certain aspects relate to obtaining telemetry information from enterprise applications. To facilitate telemetry, within an enterprise application, one or more spans are created. As used herein, a span refers to a set of named operations that represent a unit of work. A particular span can refer to a process. A span has a span context. As used herein, a span context can include a trace identifier and a span identifier. Accordingly, a first process can have a first span and a second process a second span. If the second process is called by the first process, then the first and second spans are related by a parent-child relationship such that the first span is a parent and the second is a child. Tracking the spans of different processes facilitates a more detailed instrumentation. 
     Certain figures and associated description further explain certain aspects. For instance,  FIGS.  4 - 5    relate to different aspects of span instrumentation.  FIGS.  6 - 8    relate to prioritization of various spans during instrumentation.  FIGS.  9  and  10    relate to instrumenting threads.  FIGS.  11 - 13    relate to propagating span context across different devices.  FIGS.  14 - 16    illustrate various computing systems which can implement instrumentation functionality. 
     Instrumentation of Web-Based Enterprise Applications 
       FIG.  2    depicts an example of a process  200  used to gather telemetry data, according to an aspect of the present disclosure. Process  200  can be performed by one or more of developer computing device  110  and servers  140   a - n.    
     At block  202 , process  200  involves providing a web page application to a web browser on a client device. For instance, server  140   a  serves web application  134  to web browser  132 . Web application  134  includes tracer application  136 , which provides instrumentation. Web application  134  instrumented with tracer application  136  prior to process  200 . 
     At block  204 , process  200  involves detecting a start of the web page application. Web browser  132  begins executing web application  134  and tracer application  136 . Server  140   a  can detect the start of the execution by determining that web browser  132  has requested one or more resources. 
     At block  206 , process  200  involves instantiating, based on a start of the web page application, the tracer application. Tracer application  136  is configured to log tracing data for web application  134 . 
     At block  208 , process  200  involves detecting an event initiated by interaction with the web page application. Web application  134  continues to execute and an event is triggered. Examples of events include user interface interactions, clicks, navigations, mouse-overs, refreshes, etc. Additionally, an event can be representational state transfer (REST). 
     At block  210 , process  200  involves automatically logging a start of a span based on the detection, the logging associating the span with the tracer application. Tracer application  136  causes the logging of a span that corresponds to the event. 
     At block  212 , process  200  involves executing operations corresponding to the event. Web browser  132  executes code corresponding to the event, such as loading an image or resource. 
     At block  214 , process  200  involves automatically logging an end of the span based upon a completion of the operations corresponding to the event. Upon the completion of the code referred to in block  212 , tracer application  136  logs the end of the span. Data collected can include processing cycles used, time taken to execute the span, memory consumption, and so forth. 
     As discussed herein, certain aspects can measure data relating to a span that crosses multiple servers, processing threads, or uses multiple separately identifiable operations. For instance, an execution of block  210  can result in additional spans, each providing more granular information, being created. For instance, the tracer application  136  can create a first child span corresponding to a first operation and a second child span corresponding to a second operation. The first and second child spans can be children of the span. 
     Continuing the example, tracer application  136  automatically logs an end of the first child span based on completion of the first operation and automatically logs an end of the first child span based on completion of the first operation. Therefore, the tracer application  136  obtains more granular information than just the span alone. The first child span and the second child span are associated with the span. 
     An example below shows code for an insertion of a client-side span context using Javascript: 
     
       
         
           
               
             
               
                   
               
             
            
               
                 define([“@oracle/trace-client/trace”, 
               
               
                   “@oracle/trace-client/trace_utils”], 
               
               
                   (Trace, TraceUtils) =&gt; { 
               
               
                   //Create a tracer 
               
               
                   const tracer = Trace.initTracer({ 
               
               
                     url: getCollectorUrl( ) //Domain-specific 
               
               
                   }); 
               
               
                   //Create a root span 
               
               
                   tracer.span({ 
               
               
                    operationName: “rootSpan” 
               
               
                   }, (span) =&gt; { 
               
               
                      //Log a simple message 
               
               
                      rootSpan.info(“Here&#39;s a message”); 
               
               
                      //Log a message with custom fields 
               
               
                      rootSpan.info({messageStatus: ‘lit’}, “This message is lit.”); 
               
               
                      //Create a child span (if desired) 
               
               
                      tracer.span({ 
               
               
                       operationName: “childSpan2”, 
               
               
                      }, (childSpan) =&gt; { 
               
               
                      //Create a fetch request 
               
               
                      let request = new Request(“http://.../myService/endpoint”); 
               
               
                      //Inject the child span&#39;s context 
               
               
                      request = tracer.inject(childSpan, request); 
               
               
                      //Make the fetch call 
               
               
                      fetch(request).then((response) =&gt; { 
               
               
                         // ... process the response 
               
               
                         // Close the child span 
               
               
                        childSpan.finish( ); 
               
               
                         }); 
               
               
                      }); // end child 
               
               
                      //Close up root span when we&#39;re done 
               
               
                      rootSpan.finish( ); 
               
               
                     }); //end root 
               
               
                    }); //end process response 
               
               
                  }); //end define 
               
               
                   
               
            
           
         
       
     
       FIG.  3    depicts an example of an instrumented application for generating span context, according to certain aspects of the disclosure. The instrumented application can be built and instrumented by a software development tool such as developer IDE  112  and may be executed a browser executing on a computing device.  FIG.  3    depicts web application environment  300 , which includes web application  302 , server  340 , query  350 , and a response  352 . In the example depicted in  FIG.  3   , web application  302 , which is instrumented with tracer capabilities executes on a web browser, communicating with server  340  to serve one or more web pages. Web application  302  sends one or more queries  350  and receives in response, one or more responses  352 . While  FIG.  3    is described with regard to a web page, it should be appreciated that the flow and components can be executed by a mobile application, or other application. 
     Web application  302  shows a flow  310 , which includes web page  312  having components  314 ,  316 , and  318 . The components can be mobile applications, web applications, service connections, business objects, or processes. Each component can perform different functionality such as part of a web page. Each of components  314 ,  316 , and  318  can cause component events  315 ,  317 , and  318  respectively. Each of component events  315 ,  317 , and  318  trigger one or more occurrences in the telemetry runtime  320 , which in turn causes one more actions to be performed, while logging the events. 
     Modules of a flow  310  or a web page  312  may interact or relate to each other. For instance, for a particular web page, the components may be user interface (UI) components, variables, action chains, web page flows, and page navigation, and data access through REST endpoints. Variables can be a mechanism used to store and manage a state of the browser settings, client device settings, user settings or other parameters. The components of the web page can interact with a telemetry runtime that processes various events for each component. 
     The telemetry runtime  320  can generate actions or action changes that correspond to component events  315 ,  317 , and  319 . For example, a user may click on a particular visual element of the web page displayed within the browser, causing a component event. The telemetry runtime  320  may determine that the web browser should navigate to a new web page  330 . The telemetry runtime  320  may determine that the action associated with the user click is to update a portion of a user interface (UI) of the web page  312 . 
     In another example, the telemetry runtime  320  may initiate an action chain  333  that corresponds to the steps to update the portion of the UI. For instance, an action chain may be a set of one or more individual actions that are related or sequential actions  336 . Each action chain can be triggered by an event. For example, a user click can trigger navigation to a page that corresponds to the location on the browser that the user click was received (e.g., a hyperlink, a navigation button, etc.). An action chain can define input parameters and local variables that are available within the scope of that action chain, and can include application-scoped parameters and variables. The telemetry runtime may determine that one or more REST calls  338  to the server are needed to update the portion of the UI. 
     In response to REST call  338 , web application  302  sends a query  350  to the a REST service endpoint  332  of server  340 . The query  350  can include an injection span context. In return, the server  340  sends back a response  352 , which can include additional HTTP headers. The web application  302  then uses the response to complete the actions caused by the component event(s). 
     Flows of a web page and page navigation govern the communication of information between a first page to a second page. Each web page has a predefined lifecycle, as does each application that is running in the browser. Each lifecycle event, such as entry or exit from a page, can provide a trigger for an action chain. All data entering a mobile or web application may be based on REST protocols. This data can come from custom business objects and from business objects provided by service connections. Actions and variables control how data is sent to and from a REST endpoint in a mobile or web application. Action chains have a well-defined context and contract: an action chain orchestrates its underlying actions, coordinating state flow and the execution path. The action chain can define input parameters and local variables that are only available in that context. An example of an action chain is one that makes a REST call (first action), then takes the result of that and stores that in a variable (second action). Actions may export a new state to that context, but it is only available to future actions along that same action chain. An action chain can be created in the context of a page or the application and exists within the scope of the page or the application. It has a defined interface and contract and can be called by event triggers using its ID. 
     A telemetry Application Programmer Interface (API)  322  can enable programmer access to the activities of the telemetry runtime, any actions or action chains, component events, and other related activities (e.g., a server response to an action). The telemetry API  322  can output span logs to a database, storage medium, or another server or browser for additional processing. In one example, the telemetry API may be a REST API. The telemetry API  322  can store cloud infrastructure objects such as audit logs, application flow logs, or other log files. The telemetry API  322  may periodically sample the stored cloud infrastructure objects to output telemetry data to common analytics ingestion  324  or a client log ingestion endpoint  326 . 
     Common analytics ingestion  324  may ingest log data from telemetry API  322 . In one example, the common analytics ingestion  324  can ingest log data from cloud infrastructure object storage using a REST API. In one example, the common analytics ingestion  324  may determine storage locations for the collected log data. The common analytics ingestion  324  can ingest various log data at a user, group, or organization level. In some examples, common analytics ingestion  324  can transform the log data into a visualization for an analytics console. 
     A client log ingestion endpoint  326  can also be configured to receive log data from the telemetry API  322 . The client log ingestion endpoint  326  can store log data, transform log data into various visualizations, or perform additional processing to log data. 
     Generally, distributed tracing may be implemented using a Trace-Client API within the distributed tracing architecture. The Trace-Client API consists of a tracer which is used to create spans around operations within an application. Spans can have child spans that indicate smaller granularity operations of the respective parent span, which can, in turn, have children that indicate smaller granularity operations than the first child span. A set of spans emanating from a single parent may be considered a trace. Spans contain metadata about the operation they are measuring, along with some identifying information. For applications with operations that make out-of-process calls (for example, a client application making a call to a REST service), span context can be propagated along with the outgoing request (for example, in the form of special HTTP headers). The receiving application or server can extract the span context and use it to create child spans of the parent span on the client. The Trace-Client API has the ability to output span information in the form of log messages (one each for the beginning and end of spans) to various backend servers. 
     An example of application spans is a simple application flow. For instance, a user navigates to a web page and click a button. The button click triggers an event, which causes the application to call an event handler. The event handler makes a REST (define) request, which is processed by a REST service. The service returns a response, which causes the user interface of the application to be updated. This example is illustrated in  FIG.  4   . 
       FIG.  4    depicts an example of a span hierarchy, according to an aspect of the present disclosure.  FIG.  4    depicts a span hierarchy  410  and a span timeline  430 . Together, span hierarchy  410  and a span timeline  430  describe a set of relationships between various spans in the span context. Within span hierarchy  410  or a span timeline  430 , relationships exist between parent and child spans. As depicted, span hierarchy  410  represents a hierarchy of events such as user click  412 , event handler  414 , REST request  416 , process response  418 , server process request  420 , and update UI  422 . Span timeline  430  includes span A  424 , span B  434 , span C  436 , span D  440 , span E  438 , and span F  442 . 
     In an example, web browser  132  receives user click  412 . User click  412  results in the creation of span A  424 . In response, web browser  132  initiates an event represented by the action of the user click, which triggers the operation of event handler  414 . The web browser  132  may use event handler  414  to determine one or more actions to take responsive to what event is detected based on the user click that was received. The instantiation of event handler  414  causes span B  434 , which is a child span of span A  424 . 
     Continuing the example, event handler  414  causes REST request  416  and process response  418 . Because processing the response of the REST request occurs after the REST itself, span C  436  (corresponding to the REST request) occurs before span E  438 . The REST request causes a server to process the request. The processing of the REST response causes the user interface (UI) to be updated accordingly. Therefore, as depicted, REST request  416  causes server process request and update UI  422 . Because the UI is not updated until after the server processes the request, span D  440  (corresponding to server process request) starts and completes before span F  442  (corresponding to updating the UI). Therefore, span D  440  represents the server&#39;s processing of the request. 
     As can be seen, span D  440  occurs during span C  436  and span F  442  occurs during span E  438 . Span E  438  represents the browser processing of a response from the server that corresponds to the REST request made from the browser. Span F  442  represents the browser updating the user interface based on the processing of the response from the server. Spans C  436  and E  438  are children of span B but execute sequentially. Span D  440  and F  442  are children of spans C  436  and E  438  respectively. 
     Span contexts such as those discussed with respect to  FIG.  4    are managed by instrumentation libraries that are added to custom enterprise applications by a software development tool (e.g., developer IDE  112 ). 
       FIG.  5    depicts tracer components within an instrumented application that are used to generate span context and logs, according to certain aspects of the disclosure. In the example depicted in  FIG.  5   , end user computing device  520 , which executes web application  522 , communicates with server  560  via various commands and/or API calls. Web application  522  can be developed by developer IDE  112  and can be customer-developed software. Code to support instrumentation is automatically added by developer IDE  112 . 
     End user computing device  520  includes one or more modules such as web application  522  (or any other consuming client), trace module  524 , tracer interface  526 , span interface  528 , tracer  530 , span  532 , a span logging library  534  (i.e., a Bunyan Logger), span stack  536 , browser console  538 , compression layer  544 , tracer server stream  546 , sender task  548 , message queue  542 , and tracer console stream  552 . In turn, tracer  530  operates to perform instrumentation on web application and creates one or more spans  532  and adds active spans to span stack  536 . Server  560  includes one or more modules such as a trace-collector servlet  562 . 
     Subsequently, web application  522  receives or detects interactions from the user (e.g., a user click). Web application  522  interacts with trace module  524  and/or tracer interface  526  to start one or more tracers  530 . In turn, span logging library  534  logs information and metadata such as an event type, name of the event, URL of a server request, status code of the return value, errors, warnings, and so forth via span interface  528 . 
     Various API calls are available. The API call initTracer( ) initializes and returns a global tracer object. The API call initTracer is called once for an application context and returns a TracerOptions object. The API call activeTracer returns the global tracer object. For example, The API call inject( ) causes a span to be injected into a request (e.g., to a server). Upon return the API call extract( ) can be used to extract a span. 
     Multiple spans can be generated. For instance, tracer  530  can create a span to represent an event or a thread of the web application  522 . Tracer  530  can create child spans as appropriate (e.g., as described with regard to  FIG.  4   ) based on the particular operation for which the tracer created the span. As discussed further herein, instrumented applications can obtain information from different threads and/or different servers that service requests caused by the triggering of events in the application. 
     Web application  522  may use tracer interface  526  to control the tracer or receive injections for the span. The tracer may also monitor, write, or read to span stack  536  where one or more spans can be cached or accessed by the tracer to monitor parent spans, or insert span context within a newly created span such as span  532 . Web application  522  may use span interface  528  to communicate span related information to a span logging library  534 . Compression layer  544  can compress span related information minimization before it is sent to the trace-collector servlet  562 . Examples of compression techniques used by compression layer  544  include zip and gzip. In one example, the tracer console stream  552  may output a stream of the span log to a browser console presented on the end user computing device  140 . In turn, server  560  may execute a trace-collector servlet  562 , which stream of span logs and collects traces from sender task  548  on end user computing device  520 . 
     Prioritization of Spans 
     Aspects of the present disclosure relate to instrumenting web applications. In some cases, due to a high number of events and resulting spans and/or calls resulting in child spans, a number of spans can become difficult to manage or prioritize. In such cases, certain aspects provide features for reducing the payloads of spans for the purpose of reducing capacity for span logs and streamlining telemetry data. 
     In a default mode, the instrumentation can to capture all spans and emit messages based on all of the spans to the browser console and any services. However in some cases, an unmanageable number of span messages may be present, obfuscating a clear picture of relevant telemetry data of interest. Therefore, spans can be filtered based on one or more criteria. 
     Further, in some cases, a span of interest is a child span, providing more detailed information than a corresponding parent span. But the parent span information may be contributing to a congestion of span data. Accordingly, certain aspects introduce the concept of proxy spans allow for maintaining a span tree while only gathering instrumentation details for one or more specific child spans of interest. 
       FIG.  6    depicts an example of a tracing architecture used to manage backpressure caused by instrumentation of spans, according to certain aspects of the disclosure.  FIG.  6    depicts tracing architecture  600 , which includes one or more of application runtime  602 , tracer implementation  604 , span controller  606 , browser span logging library  634 , console stream  610 , client logging service (CLS) stream  612 , and client logging service  614 . In the example depicted, span controller  606  manages and prioritizes spans based on one or more parameters. Application runtime  602  may be similar to the telemetry runtime  320  and perform operations similar to telemetry runtime  320  described with regards to  FIG.  3   . 
     In a first example, a tracer implementation  604  starts spans for application runtime  602 . The tracer implementation  604  may concurrently communicate span monitoring data to browser span logging library  634  while executing spans. The browser span logging library  634  outputs the span log data to console stream  610 , which may be presented within the browser of an end user device. The browser span logging library  634  can also output the span log data to the CLS stream  612 . The CLS stream  612  may be a stream of log data communicated to the client logging service  614 . The client logging service  614  may store the log data for additional processing. 
     In another example, the tracer implementation  604  receives spans that are created by span controller  606 . The tracer implementation  604  can also return spans (e.g., terminate a span) upon completion of the event for which the span was generated. The tracer implementation  604  may also receive a command to terminate the span from the application runtime  602 . Span controller  606  can implement span prioritization. Each span can have a priority level. For instance, span controller  606  can receive one or more parameters indicating which span(s) to prioritize. In an example, a default span priority is set. If a priority level of a given span is less than a default priority, then data for the span and associated child spans is not returned. 
     In yet another example, tracing architecture  600  provides for an initial set of spans to be generated, for instance, as discussed with respect to process  200 . Each span in the initial set of spans can be given a corresponding priority. Subsequently, at runtime, spans in the initial set of spans can be measured or not measured, or pruned to a subset, based on programmer or user input. For instance, a threshold priority can be set. At runtime, any span that has a priority greater than the threshold priority is converted into a proxy span and is not measured. 
     A proxy span maintains the span tree, that is the relationships between parent and child spans. But because proxy spans are not measured, span controller  606  does not obtain runtime instrumentation measurements for the spans, but still obtains measurements for any child spans that are not proxy spans. The span proxy preserves the relationship between parent and child and therefore maintains the tree structure, even if certain proxy spans in the tree do not have instrumentation data. Hence, in a way, the span tree is pruned such that the data for the spans that are interesting to a developer are maintained.  FIG.  7    provides an example of using proxy spans. 
       FIG.  7    depicts examples of a span hierarchy without span prioritization and a span hierarchy with prioritization, according to certain aspects of the disclosure. In particular,  FIG.  7    depicts span hierarchy  700 , which does not use prioritization, and a span hierarchy  730 , which uses prioritization. 
     In span hierarchy  700 , span A  702  is a parent span of span B  704 . In turn, span B  704  is a parent span of span C  706 , span D  708 , and span E  710 . In span hierarchy  700 , data for all spans, span A  702 , span B  704 , span C  706 , span D  708 , and span E  710  is gathered. 
     In span hierarchy  730 , by contrast, illustrates a hierarchy with span prioritization. Span hierarchy  730  includes span A  732  and span proxy B  734 , which is a child of span A  732 . Span A  732  has a priority of 1. Span proxy B  734  has a priority of 2, which is greater than the priority of span A  732 . In this example, the default priority is set to be 1. Span proxy B  734  has been converted from an original span B because instrumentation data from span B was not needed as indicated by the priority of span B being 2, which is greater than the default priority. 
     As a consequence, span C  736 , span D  738 , and span E  740 , all of which have priority of 1 and are therefore not pruned, are marked as having parent span A  732  because their original parent, span B, was proxied. Accordingly, at runtime, instrumentation data is gathered for span A  732 , span proxy B  734 , span D  738 , and span E  740 . 
     From an implementation perspective, a SpanOptions object used for creating spans contains a priority field. In some cases, an absence of priority on a span indicates an implicit priority of “high” (1) for root spans and “medium” (2) for child spans. A span (identified by SpanImpl) is created and returned and messages are emitted normally. If a span has been proxied, then a SpanProxy object is created instead. The SpanProxy object can be interacted with like any other Span object, but the fields and methods of SpanProxy will delegate to the active span. For instance, in the example above, span proxy B  734  corresponds to an object SpanProxy and the methods and fields therein will default to those corresponding to the object of Span A  732 . In this manner, the application runtime environment need not be adjusted because as far as the application is concerned it is always receiving a span. 
     In some implementations, a priority value is represented by a positive number, with a higher value indicating a lower priority. For instance, priority level 0 can be the highest priority, then level 1, then level 2, and so forth. Therefore, in this implementation, any spans with priorities higher in value than the threshold priority are converted into proxy spans. But a different numbering scheme is possible, e.g., higher value indicating higher priority. In some cases the priority is represented aliases, for instance “critical” is assigned to level zero, “high” to level 1, “medium” to level 2, and “low” to level 3. By default, root spans can have a priority of 1, and child spans have a priority of 2. 
     In some cases, a priority threshold can be modified by a fleetwide sampling algorithm. This algorithm requires that each priority be assigned a percentage and a random number selected to fall into one of the percentages. Higher percentages will be typically be assigned to higher priorities, to ensure that most users of the application emit the minimum amount of telemetry (for capacity and performance reasons). A smaller percentage might be assigned to lower priorities, indicating that a smaller number of users will emit more telemetry, in order to get deeper information on user journeys or other higher granularity information. The percentages can be applied on the tracer configuration, or by a server-side profile option. 
     In some cases, priority boosting can occur. Priority boosting refers to increasing the priority of a proxied span at runtime. This can occur if the span turns out to have interesting instrumentation data. Examples of priority boosting include when duration is taking too long and the span does not have children that would form the majority of the duration of the span or if an error occurs. 
     The tracer system can be configured to adjust the priority threshold dynamically, for instance if too requests are received and/or a payload is too large (also referred to as “ingestion service backpressure”). For instance, the ingestion service (CLS) that collects the spans and logs can respond with an HTTP error code (for example, “429 Too Many Requests” or “413 Payload Too Large”) that indicates too many spans and/or logs have been sent. The system can then respond by dynamically altering the priority threshold so that fewer logs are sent in subsequent requests. 
     The following table illustrates example priorities of spans for different events: 
     
       
         
           
               
             
               
                 TABLE 1 
               
             
            
               
                   
               
               
                 Examples of priorities for different spans 
               
            
           
           
               
               
               
            
               
                   
                 Span Operation Name 
                 Priority 
               
               
                   
                   
               
               
                   
                 pageLoad 
                 1 
               
               
                   
                 componentEvent (ie. user events) 
                 1 
               
               
                   
                 runtimeEvent (ie. enter/exit) 
                 1 
               
               
                   
                 variableEvent 
                 2 
               
               
                   
                 fetch 
                 1 
               
               
                   
                 sdp.fetch 
                 2 
               
               
                   
                 fetchFirst, fetchNext 
                 2 
               
               
                   
                 action 
                 2 
               
               
                   
                 actionChain 
                 2 
               
               
                   
                 spans for unhandled exceptions 
                 1 
               
               
                   
                 componentEvent with 
                 3 
               
               
                   
                 container.event=‘onFndNotificationPoll’ 
               
               
                   
                 pageLoad with container.id=‘shell’ 
                 3 
               
               
                   
                 runtimeEvent with container.event 
                 3 
               
               
                   
                 !=‘vbExit’ or ‘vbEnter’ 
               
               
                   
                   
               
            
           
         
       
     
       FIG.  8    depicts an example of a process  800  for prioritizing spans, according to certain aspects of the disclosure. Process  800  can be performed by one or more of developer computing device  110  and servers  140   a - n.    
     At block  802 , process  800  involves identifying, from code of a web application, that the web application includes an event that is triggered by a user interaction. For instance, during instrumentation, developer IDE  112  executing on developer computing device  110  determines that web application  134  includes an event that is triggered by a user interaction. 
     At block  804 , process  800  involves associating the event with a first span. Developer IDE  112  configures the tracer to log tracing information based on an execution of a first set of operations caused by (corresponding to execution of) the event. The tracer is configured to obtain a first measurement of performance of a first span. The span refers to the first set of operations. Examples of measurements of performance include cycles, processing time, memory usage, latency, etc. 
     At block  806 , process  800  involves identifying, in the code, that the execution of the first set of operations causes a request to be made to a server. For instance, the first set of operations can involve a REST call. 
     At block  808 , process  800  involves associating the request with a second span. Based on the identified request, the tracer is configured to log tracing information based on an execution of a second set of operations caused by the request. The tracer is configured to obtain a second measurement of performance of the second span. The second span is a child span of the first span. 
     At block  810 , process  800  involves receiving a priority for the first span. For example, at runtime when the web browser  132  is executing web application  134 , a developer can adjust the priority for the first span. The priority can be adjusted upward or downward. 
     At block  812 , process  800  involves determining that the priority is outside a priority tolerance. In some cases, a threshold value can be used instead of a tolerance. 
     At block  814 , process  800  involves labeling the first span as a proxy span based on the determining. Continuing the example, the web browser  132  labels the first span as proxy span such that instrumentation data is not gathered. At runtime, when the web application is executing, the tracer does not log information based on the execution of the first set of operations that correspond to the first span. 
     Instrumenting Threads 
     Traditionally, web-based applications can use a main browser thread for user interface operations. For instance, improvements to asynchronous Javascript programming have made the main browser thread a viable way of creating applications that are responsive. But for certain long-running background processes, an application developer would may choose to use of the Web Worker API, which allows for creating actual native threads for executing application logic. 
     However, in a standard distributed tracing application, a separate thread (such as via the Worker API) is considered out of process or at least on a different scope than a tracer that is executing on the main thread. Consequently, a tracer needs to be configured within the code to operate on the worker thread. 
     By contrast, certain aspects can automatically instrument threads. For instance, a TraceWorker class abstracts the work of configuring a Tracer in application code by encapsulating it in a subclass of a standard Worker class. The TraceWorker class uses an algorithm to automatically create the Worker thread, configure a Tracer, and then load the application code which will then automatically be telemetry-enabled. The TraceWorker can then optionally be configured to override the native Web Worker API so that anytime the application attempts to create a Worker thread it will be a TraceWorker which is wrapping a standard Worker&#39;s functionality. 
     Advantages to this approach include transparent operation to the developer and user and enabling telemetry for out-of-thread code while preserving span hierarchy between threads. Additionally, no requirement exists for duplicate configuration data because configuration data for each thread will inherit the main thread&#39;s configuration automatically. 
       FIG.  9    depicts an example of a distributing tracing environment with a traceworker client, according to certain aspects of the disclosure.  FIG.  9    depicts main browser thread  910  and worker thread  920 . In the example depicted in  FIG.  9   , main browser thread  910  calls worker thread  920 , which provides instrumentation data back to main browser thread  910 . 
     Main browser thread  910  includes main application  912 , tracer  914 , and TraceWorker client  917 . Worker thread  920  includes TraceWorker shim code  922 , application worker script  924 , and tracer  925 . Worker thread  920  is an object that is created using TraceWorker client  917  and can be written in JavaScript. 
     The worker thread  920  can run in a context that is different from the main browser operations such as the browser window. In this manner, a more responsive user interface can be maintained, for instance, if the tasks to be performed by the worker thread  920  are time consuming or complex. 
     TraceWorker client  917  can manage threads such as worker thread  920 , such as by configuring worker thread  920  using traceworker shim code  922 . Adding the traceworker shim code  922  facilitates obtaining span context and trace context. The constructor of the wrapper will be wrapped with a span, which will be a child of a current span&#39;s context if applicable. Worker threads are initialized with an application script that runs upon creation and have a communication port. 
     The TraceWorker client  917  generates and executes shim code  922  that performs the following actions: (1) temporarily installs message handlers to handle all incoming messages from the main thread, (2) loads all distributed tracing dependencies, and (3) replies with a message indicating success (or failure). 
     If successful, the TraceWorker client  917  will get the active span context and Tracer configuration, and send to the shim. The shim will receive the Tracer configuration, initialize a Tracer, and create a child span of the received span context. The shim will then inject the application worker code and remove its message handlers. In turn the application and worker threads perform various operations. 
     Once created, the worker thread  920  may create a tracer and copy one or more configuration parameters from the worker thread  920  to the tracer  925 . The worker thread  920  may also extract the span context associated with the span created by main application  912 . The worker thread  920  may create a child span of the span created by main application  912  including the span context. During execution of the application worker script  924  by the worker thread  920 , child spans may be created and captured by the tracer  925  for further processing. The worker thread  920  may communicate that the application worker script  924  has been completed successfully to the TraceWorker client  917 . The TraceWorker client  917  may subsequently communicate to the main application  912  that the worker thread was successful. The main application  912  may communicate to the tracer  914  that the span is completed and terminate the span. 
     In one example, data can be sent between worker threads and the main application via a system of messages in which both sides send their messages. The messages may be sent using a method such as postMessage( ), and respond to received messages may be communicated using an on message event handler such that the message is contained within the message event&#39;s data property. In this particular configuration, the message data is copied rather than shared between the main application and worker threads. Worker threads may spawn subsidiary workers (e.g., subsidiary threads) where workers are hosted within the same origin as the parent page. 
     The following example code illustrates how a developer may use the TraceWorker thread: 
     
       
         
           
               
             
               
                   
               
             
            
               
                 // import the Trace-Client API 
               
               
                 require([‘trace’, ‘trace/util/worker_utils’], (Trace, WorkerUtils) =&gt; { 
               
               
                  // Assumes a Tracer was initialized 
               
               
                  // (Note that Visual Builder applications wouldn&#39;t require tracer 
               
               
                  creation) 
               
               
                  const tracer = Trace.initTracer({...}); 
               
               
                  let workerSpan = tracer.startSpan({ 
               
               
                   operationName: ‘workerSpan’ 
               
               
                  }); 
               
               
                 // Option 1. Create the worker 
               
               
                  const worker = new WorkerUtils.TraceWorker([‘my_worker_script.js’, 
               
               
                 ‘my_referenced_script.js’], /* other Worker options */); 
               
               
                 // Or Option 2. Use optionally overriden window.Worker API 
               
               
                  // const worker = new window.Worker([‘my_worker_script.js’, 
               
               
                 ‘my_referenced_script.js’], /* other Worker options */); 
               
               
                  // ... install a message handler per normal Worker thread usage 
               
               
                  worker.oncomplete = (msg) =&gt; { 
               
               
                   // Once worker is done, finish the span, and that&#39;s it. 
               
               
                   workerSpan.finish( ); 
               
               
                  }; 
               
               
                  // Current tracer config and span context is automatically injected 
               
               
                 before app scripts are run 
               
               
                  worker.run( ); 
               
               
                 }); 
               
               
                   
               
            
           
         
       
     
       FIG.  10    depicts an example of a process  1000  for instrumenting threads, according to certain aspects of the disclosure. Process  1000  can be performed by one or more of developer computing device  110  and servers  140   a - n.    
     At block  1002 , process  1000  involves providing a web page application to a web browser on a client device. For instance, server  140   a  provides web application  134  to web browser  132  on end user computing device  130 . 
     At block  1004 , process  1000  involves creating, from the web page application, a global tracer configured to log tracing data for the web page application. Similar to as described with respect to block  206  of process  200 , a global tracer is created. 
     At block  1006 , process  1000  involves instantiating, from the web page application, a wrapper for a subsidiary thread. The wrapper is configured to execute shim code before executing the subsidiary thread. 
     At block  1008 , process  1000  involves passing, from the wrapper to the shim code, configuration data of the global tracer. 
     At block  1010 , process  1000  involves creating a subsidiary tracer from the shim code. The subsidiary tracer is configured to log tracing data for the subsidiary thread. The tracing data of the web page application and the subsidiary thread are associated through the configuration data of the global tracer. 
     At block  1012 , process  1000  involves executing, from the shim code, the subsidiary thread. 
     Instrumenting Spans Across Server Calls 
       FIG.  11    depicts an example of a process  1100  for propagating tracing across a distributed software application, according to certain aspects of the disclosure. Process  1100  can be implemented by a computing system such as the end user computing device  140  and can be part of the tracer application  136 . Process  1100  involves creating an appropriate request for a remote server to obtain a resource (e.g., web page, image, or file). The request can be in hypertext transfer protocol (HTTP). For illustrative purposes, process  1100  is discussed in conjunction with  FIG.  12   . 
       FIG.  12    depicts an example of propagating span context across a services in a distributed system, according to certain aspects of the disclosure. Examples of services include REST calls to servers. For example, rendering a particular web page may require multiple REST calls, each with a specific purpose. A first REST call may cause the web browser to render the page, a second REST call may obtain an image that is located on a server (the REST endpoint) to be displayed on the page, or a third REST call may be a database query to obtain some information such as an employee&#39;s manager&#39;s name. A REST call can also cause one or more child REST calls to execute. 
     REST calls can be cross-origin calls. Cross origin calls request information from a server that is not the original server (e.g., the server that serves the web page). For example, the original server can be on oracle.com, whereas the second server can be on google.com. In some cases, process  1100  is executed after determining that the web page from the original server requires a request to an external server outside a domain of the original server. The determining can be compatible with cross-origin resource sharing (CORS). 
       FIG.  12    includes service  1210  and service  1220 . Service  1210  can execute the browser and service  1220  executes on a server identified by the REST endpoint. Service  1210  includes parent span  1212 , child span  1214 , and child span  1216 . Service  1220  includes child span  1222 , which is after the REST call. In an example, child span  1214  and  1216  represent processing that needed to happen before the REST call and the context of child span  1222  is sent over the network to the server. In turn, the server can propagate its span context to another server if it makes such a request. Each server collects its respective traces and sends them to the appropriate location. 
     As discussed, the span context includes a root span or trace identifier, which indicates an overall objective trying to be accomplished (e.g., load the page). The complete span context includes a trace identifier (ID) that is typically a 128-bit representation and child ID that is typically a 64-bit random number. From each span context, a graph can be constructed from each all of the span contexts that point to their respective parents. 
     Returning to  FIG.  11   , at block  1101 , process  1100  starts. Tracer application  136  can log tracing data for a web page from an original server. The tracing data can include previous requests and their successes and failures. From the tracing data, tracer application  136  can form a deny list that includes destination servers that did not accept requests with tracing headers and/or an allow list that includes destination servers that did accept requests with tracing headers. In some cases, process  1100  executes if a cross-domain request is detected. 
     Instrumentation can be achieved via injecting tracing headers into requests to servers for resources (e.g., as part of a web page loading). But tracing headers can often be rejected, for example, for security reasons. Accordingly, process  1100  involves working around such security measures to facilitate telemetry. For example, considering  FIG.  12   , service  1210  executes on the original server and service  1220  on the external server. Parent span  1212  (e.g. for a first process) therefore executes on the original server. Using techniques disclosed herein, tracer application  136  can analyze not only parent span  1212 , but also child span  1214  and child span  1216 , derived from child span  1214 . But as can be seen, parent span  1212  is also related to child span  1222 , which executes on service  1220  (therefore on the external server). Process  1100  can be used to propagate the span context from parent span  1212  to child span  1222 , thereby facilitating instrumentation. 
     At block  1102 , process  1100  involves determining whether CORS is active (e.g., a cross-domain request is detected). If CORS is active, then process  1100  proceeds to block  1103 . In this case, then if CORS is not needed, then process  1100  proceeds to block  1108 , where a header is injected. 
     At block  1103 , process  1100  involves determining whether the request for the resource is idempotent. Idempotent means that an intended effect on the server of multiple identical requests with that method is the same as the effect for a single such request. Accordingly, if the intended effect on the server of the request is not idempotent, i.e., will not have the same as a previous request, then process  1100  proceeds to block  1104 . Otherwise, if the request is idempotent, process  1100  proceeds to block  1115 . 
     At block  1104 , process  1100  involves determining whether the destination of the request is on a server deny list. For example, tracer application  136  searches a deny list for whether the external server disallows tracing headers in requests from the original server. The server deny list includes servers that are identified as denying requests that include extra headers (e.g., as created by requests identified by block  1112  of process  1100 ). The deny server list is useful because given a choice between having the REST call fail and simply not having the telemetry information, simply not having the telemetry information is preferable. 
     If a request to a service does not support propagation headers, the request is added to a deny-list, which will prevent any further automatic attempts to inject context for this user session, and perform the request without injected headers. In an aspect, the deny-list is not cached in local storage, so that an incomplete configuration does not cause a block of future requests. An destination can be on both allow and deny lists, but if so, the deny-list will take precedence. 
     Allow-lists and deny-lists are implemented as associative arrays to improve lookup time. The lists are keyed by the URL origin of the failed request (without any parameters) or the individual service. This might be determined by the configuration of the request. The value of the map can be null but might later include the actual failure or other metadata about the reason for being added to the list. 
     Examples of calls include: 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 { ‘http://example.com/’: null, // allow-deny whole origin 
               
               
                   
                 ‘http://someurl.com/myservice’: ‘additional metadata’ , // 
               
               
                   
                 allow-deny individual service } 
               
               
                   
                   
               
            
           
         
       
     
     If the server is deny listed, then process  1100  proceeds to block  1114 . If the server is not deny listed, then process  1100  moves to block  1105 . 
     At block  1105 , process  1100  involves determining whether the destination of the request is a server on an allow list. For example, tracer application  136  searches an allow list for whether the external server allows tracing headers in requests from the original server. 
     The allow list includes servers that are identified as accepting requests with extra headers (e.g., as created by requests in block  1112  of process  1100 ). 
     Once the propagation headers are determined to be supported, the particular destination is added to the allow-list. The allow list can be cached in local storage so that no additional OPTIONS calls will need to be made. This approach removes a need for user interface support to explicitly allow-list service endpoints. If the destination is on the allow list then process  1100  continues to inject headers at block  1108 . If the destination is not on the allow list then, process  1100  continues to block  1106 . 
     At block  1106 , process  1100  involves performing an HTTP OPTIONS call. An OPTIONS call requests permitted communication options from a server. Under the CORS protocol, a preflight request is sent with the OPTIONS method so that the server can respond if it is acceptable to send the request. The OPTIONS call results in a determination of whether injecting tracing headers would be accepted or not. In some cases, at block  1106 , process  1100  involves performing a preflight request before the browser has automatically performed such a check. Process  1100  continues to block  1107 . 
     At block  1107 , process  1100  involves determining from the result of the OPTIONS call, whether tracing headers will be supported by the server. In some cases, the OPTIONS call can send back a list of permissible (or accepted) headers. If tracing headers are supported, then process  1100  moves to block  1108 , where headers are injected. If tracing headers are not supported, then process  1100  moves to block  1113 , where the server is added to the server deny list. 
     Below are some sample OPTIONS requests/responses (note that some headers have been omitted for brevity). For instance, an OPTIONS request detecting propagation is shown: 
     OPTIONS/myendpoint/myservice HTTP/1.1 Host: bar.other
 
Origin: http://foo.example
 
     Access-Control-Request-Method: POST 
     Access-Control-Request-Headers: Content-Type, x-b3-trace-id, x-b3-span-id, x-b3-parentspanid, x-b3-sampled, ecid-context
 
In another example, a response when a service endpoint configured for propagation is shown:
 
     HTTP/1.1 204 No Content 
     Access-Control-Allow-Origin: https://foo.example Access-Control-Allow-Methods: POST, GET, OPTIONS
 
Access-Control-Allow-Headers: Content-Type, x-b3-trace-id, x-b3-span-id, x-b3-parentspanid, x-b3-sampled, ecid-context Access-Control-Max-Age: 86400
 
In another example, a response with no propagation configured is shown:
 
     HTTP/1.1 204 No Content 
     Access-Control-Allow-Origin: https://foo.example Access-Control-Allow-Methods: POST, GET, OPTIONS 
     Access-Control-Allow-Headers: 
     Content-Type Access-Control-Max-Age: 86400 
     At block  1108 , process  1100  involves injecting headers into the request. The injecting a tracing header in the request is based on a result of a determination that the external server allows tracing headers in the request. Examples of the contents of tracing headers include a span context. 
     In an example, two sets of headers are injected into outgoing requests using Zipkin and/or Execution Context (ECID). These protocols provide coverage for preserving context with minimal work on the side of the service developers. 
     In an example, the Zipkin B3 HTTP header scheme is used due to its wide support. Examples of B3 headers include: 
     x-b3-traceid: {TraceId}
 
x-b3-parentspanid: {ParentSpanId}
 
x-b3-spanId: {SpanId}
 
x-b3-sampled: {Sampled}
 
     TraceId is a unique 32-character UUID string, SpanId is a unique 16 character string indicating the enclosing span, ParentSpanId is the unique id of the span&#39;s parent (if applicable), and Sampled is a flag indicating whether to report span telemetry. 
     In another example, an Oracle-specific ECID-Context header is used: ECID-Context: 1. {TraceId}@@{SpanId};&lt;RID&gt; 
     RID is an encoded string of bytes that indicates the path of the context; from the browser this string will be “kXjE” which when decoded indicates the root of a request. 
     Once it is determined that headers can be injected, the injection is performed with the Tracer.inject( ) API call. This call injects the HTTP headers into the outgoing request before it is sent to the server. 
       FIG.  13    depicts an example of headers, according to certain aspects of the disclosure.  FIG.  13    depicts headers  1310 , which are the HTTP headers without the instrumentation and headers  1320 , which are the same HTTP headers as headers  1310  but with the added instrumentation (shown in bold text). 
     Returning to  FIG.  11   , process  1100  continues to block  1109 . 
     At block  1109 , process  1100  involves making the request to the server. The web browser sends the request with the tracing header to the external header. The external server is configured to log tracing data based on the tracing header. 
     At block  1110 , process  1100  involves determining whether the request to the server was successful. If the request was successful, then process  1100  moves to block  1111 , at which the process ends. If the request was not successful, then process  1100  moves to block  1112 . 
     At block  1111 , process  1100  involves ending the process for the request. At block  1111 , the extra header is successfully sent to the server, which results in the span context being propagated to the destination server, which then assists with the instrumentation. 
     At block  1112 , process  1100  involves determining whether the failure identified at block  1110  was due to the headers as opposed to some other error. If the failure was not due to the headers, then process  1100  moves to block  1116 , during which normal failover/retry procedures can be performed. If the failure was due to the headers, then process  1100  moves to block  1113  and adds the server to the server deny list. 
     At block  1113 , process  1100  involves adding the destination server to the server deny list. In this manner, if a request is identified that has the same destination server, then process  1100  does not attempt to send a request with a tracing header to the same server which denied it. After completion of block  1113 , process  1100  moves to block  1114 , where an uninjected request is made. 
     At block  1114 , process  1100  involves making an uninjected request, e.g., a normal REST call without the tracing header. In some cases, timing the time for the request to be handled can be used for the telemetry. After block  1114 , process  1100  continues to block  1118 , which involves handling the response normally. 
     At block  1115 , process  1100  involves determining whether the request is in the cached request list. A request may be stored in a cache to improve performance and reduce failure. If the request is cached, then process  1100  proceeds to block  1117 . If the request is not cached, then process  1100  proceeds to block  1104 . The request can include the span context. 
     At block  1116 , process  1100  involves performing a failover process or retrying the request. In this case, given that having a page fail to load or complete is a less than optimal user experience, at block  1116 , process  1100  involves retrying the failed operations to ensure that the tracing header injection attempts have not caused a failure. In some cases, developers may have not added sufficient error checking or graceful exits. Therefore, in this respect, block  1116  helps ensure that a custom application does not fail due to the telemetry. The request can include the span context. 
     At block  1117 , process  1100  involves proceeding with the cached response. The cached response is used to service the request. The request can include the span context. The spans and the logs are sent to the span logging library as discussed with respect to  FIGS.  4  and  5   . 
       FIG.  14    depicts a simplified diagram of a distributed system  1400  for implementing one of the aspects. In the illustrated aspect, distributed system  1400  includes one or more client computing devices  1402 ,  1404 ,  1406 , and  1408 , which are configured to execute and operate a client application such as a web browser, proprietary client (e.g., Oracle Forms), or the like over one or more network(s)  1410 . Server  1412  may be communicatively coupled with client computing devices  1402 ,  1404 ,  1406 , and  1408  via network(s)  1410 . 
     In various aspects, server  1412  may be adapted to run one or more services or software applications provided by one or more of the components of the system. The services or software applications can include nonvirtual and virtual environments. Virtual environments can include those used for virtual events, tradeshows, simulators, classrooms, shopping exchanges, and enterprises, whether two- or three-dimensional (4D) representations, page-based logical environments, or otherwise. In some aspects, these services may be offered as web-based or cloud services or under a Software as a Service (SaaS) model to the users of client computing devices  1402 ,  1404 ,  1406 , and/or  1408 . Users operating client computing devices  1402 ,  1404 ,  1406 , and/or  1408  may in turn utilize one or more client applications to interact with server  1412  to utilize the services provided by these components. 
     In the configuration depicted in the figure, the software components  1418 ,  1420  and  1422  of distributed system  1400  are shown as being implemented on server  1412 . In other aspects, one or more of the components of distributed system  1400  and/or the services provided by these components may also be implemented by one or more of the client computing devices  1402 ,  1404 ,  1406 , and/or  1408 . Users operating the client computing devices may then utilize one or more client applications to use the services provided by these components. These components may be implemented in hardware, firmware, software, or combinations thereof. It should be appreciated that various different system configurations are possible, which may be different from distributed system  1400 . The aspect shown in the figure is thus one example of a distributed system for implementing an aspect system and is not intended to be limiting. 
     Client computing devices  1402 ,  1404 ,  1406 , and/or  1408  may be portable handheld devices (e.g., an iPhone®, cellular telephone, an iPad®, computing tablet, a personal digital assistant (PDA)) or wearable devices (e.g., a Google Glass® head mounted display), running software such as Microsoft Windows Mobile®, and/or a variety of mobile operating systems such as iOS, Windows Phone, Android, BlackBerry  15 , Palm OS, and the like, and being Internet, e-mail, short message service (SMS), Blackberry®, or other communication protocol enabled. The client computing devices can be general purpose personal computers including, by way of example, personal computers and/or laptop computers running various versions of Microsoft Windows®, Apple Macintosh®, and/or Linux operating systems. The client computing devices can be workstation computers running any of a variety of commercially-available UNIX® or UNIX-like operating systems, including without limitation the variety of GNU/Linux operating systems, such as for example, Google Chrome OS. Alternatively, or in addition, client computing devices  1402 ,  1404 ,  1406 , and  1408  may be any other electronic device, such as a thin-client computer, an Internet-enabled gaming system (e.g., a Microsoft Xbox gaming console with or without a Kinect® gesture input device), and/or a personal messaging device, capable of communicating over network(s)  1410 . 
     Although distributed system  1400  is shown with four client computing devices, any number of client computing devices may be supported. Other devices, such as devices with sensors, etc., may interact with server  1412 . 
     Network(s)  1410  in distributed system  1400  may be any type of network familiar to those skilled in the art that can support data communications using any of a variety of commercially-available protocols, including without limitation TCP/IP (transmission control protocol/Internet protocol), SNA (systems network architecture), IPX (Internet packet exchange), AppleTalk, and the like. Merely by way of example, network(s)  1410  can be a local area network (LAN), such as one based on Ethernet, Token-Ring and/or the like. Network(s)  1410  can be a wide-area network and the Internet. It can include a virtual network, including without limitation a virtual private network (VPN), an intranet, an extranet, a public switched telephone network (PSTN), an infra-red network, a wireless network (e.g., a network operating under any of the Institute of Electrical and Electronics (IEEE) 802.14 suite of protocols, Bluetooth®, and/or any other wireless protocol); and/or any combination of these and/or other networks. 
     Server  1412  may be composed of one or more general purpose computers, specialized server computers (including, by way of example, PC (personal computer) servers, UNIX® servers, mid-range servers, mainframe computers, rack-mounted servers, etc.), server farms, server clusters, or any other appropriate arrangement and/or combination. Server  1412  can include one or more virtual machines running virtual operating systems, or other computing architectures involving virtualization. One or more flexible pools of logical storage devices can be virtualized to maintain virtual storage devices for the server. Virtual networks can be controlled by server  1412  using software defined networking. In various aspects, server  1412  may be adapted to run one or more services or software applications described in the foregoing disclosure. For example, server  1412  may correspond to a server for performing processing described above according to an aspect of the present disclosure. 
     Server  1412  may run an operating system including any of those discussed above, as well as any commercially available server operating system. Server  1412  may also run any of a variety of additional server applications and/or mid-tier applications, including HTTP (hypertext transport protocol) servers, FTP (file transfer protocol) servers, CGI (common gateway interface) servers, JAVA® servers, database servers, and the like. Exemplary database servers include without limitation those commercially available from Oracle, Microsoft, Sybase, IBM (International Business Machines), and the like. 
     In some implementations, server  1412  may include one or more applications to analyze and consolidate data feeds and/or event updates received from users of client computing devices  1402 ,  1404 ,  1406 , and  1408 . As an example, data feeds and/or event updates may include, but are not limited to, Twitter® feeds, Facebook® updates or real-time updates received from one or more third party information sources and continuous data streams, which may include real-time events related to sensor data applications, financial tickers, network performance measuring tools (e.g., network monitoring and traffic management applications), clickstream analysis tools, automobile traffic monitoring, and the like. Server  1412  may also include one or more applications to display the data feeds and/or real-time events via one or more display devices of client computing devices  1402 ,  1404 ,  1406 , and  1408 . 
     Distributed system  1400  may also include one or more databases  1414  and  1416 . Databases  1414  and  1416  may reside in a variety of locations. By way of example, one or more of databases  1414  and  1416  may reside on a non-transitory storage medium local to (and/or resident in) server  1412 . Alternatively, databases  1414  and  1416  may be remote from server  1412  and in communication with server  1412  via a network-based or dedicated connection. In one set of aspects, databases  1414  and  1416  may reside in a storage-area network (SAN). Similarly, any necessary files for performing the functions attributed to server  1412  may be stored locally on server  1412  and/or remotely, as appropriate. In one set of aspects, databases  1414  and  1416  may include relational databases, such as databases provided by Oracle, that are adapted to store, update, and retrieve data in response to SQL-formatted commands. 
       FIG.  15    is a simplified block diagram of one or more components of a system environment  1500  by which services provided by one or more components of an aspect system may be offered as cloud services in accordance with an aspect of the present disclosure. In the illustrated aspect, system environment  1500  includes one or more client devices  1504 ,  1506 , and  1508  that may be used by users to interact with a cloud infrastructure system  1502  that provides cloud services. The client computing devices may be configured to operate a client application such as a web browser, a proprietary client application (e.g., Oracle Forms), or some other application, which may be used by a user of the client computing device to interact with cloud infrastructure system  1502  to use services provided by cloud infrastructure system  1502 . 
     It should be appreciated that cloud infrastructure system  1502  depicted in the figure may have other components than those depicted. Further, the aspect shown in the figure is only one example of a cloud infrastructure system that may incorporate an aspect of the invention. In some other aspects, cloud infrastructure system  1502  may have more or fewer components than shown in the figure, may combine two or more components, or may have a different configuration or arrangement of components. 
     Client devices  1504 ,  1506 , and  1508  may be devices similar to those described above for  1402 ,  1404 ,  1406 , and  1408 . 
     Although exemplary system environment  1500  is shown with three client computing devices, any number of client computing devices may be supported. Other devices such as devices with sensors, etc. may interact with cloud infrastructure system  1502 . 
     Network(s)  1510  may facilitate communications and exchange of data between client devices  1504 ,  1506 , and  1508  and cloud infrastructure system  1502 . Each network may be any type of network familiar to those skilled in the art that can support data communications using any of a variety of commercially-available protocols, including those described above for network(s)  1410 . 
     Cloud infrastructure system  1502  may comprise one or more computers and/or servers that may include those described above for server  1412 . 
     In certain aspects, services provided by the cloud infrastructure system may include a host of services that are made available to users of the cloud infrastructure system on demand, such as online data storage and backup solutions, Web-based e-mail services, hosted office suites and document collaboration services, database processing, managed technical support services, and the like. Services provided by the cloud infrastructure system can dynamically scale to meet the needs of its users. A specific instantiation of a service provided by cloud infrastructure system is referred to herein as a “service instance.” In general, any service made available to a user via a communication network, such as the Internet, from a cloud service provider&#39;s system is referred to as a “cloud service.” Typically, in a public cloud environment, servers and systems that make up the cloud service provider&#39;s system are different from the customer&#39;s own on-premises servers and systems. For example, a cloud service provider&#39;s system may host an application, and a user may, via a communication network such as the Internet, on demand, order and use the application. 
     In some examples, a service in a computer network cloud infrastructure may include protected computer network access to storage, a hosted database, a hosted web server, a software application, or other service provided by a cloud vendor to a user, or as otherwise known in the art. For example, a service can include password-protected access to remote storage on the cloud through the Internet. As another example, a service can include a web service-based hosted relational database and a script-language middleware engine for private use by a networked developer. As another example, a service can include access to an email software application hosted on a cloud vendor&#39;s web site. 
     In certain aspects, cloud infrastructure system  1502  may include a suite of applications, middleware, and database service offerings that are delivered to a customer in a self-service, subscription-based, elastically scalable, reliable, highly available, and secure manner. An example of such a cloud infrastructure system is the Oracle Public Cloud provided by the present assignee. 
     Large volumes of data, sometimes referred to as big data, can be hosted and/or manipulated by the infrastructure system on many levels and at different scales. Such data can include data sets that are so large and complex that it can be difficult to process using typical database management tools or traditional data processing applications. For example, terabytes of data may be difficult to store, retrieve, and process using personal computers or their rack-based counterparts. Such sizes of data can be difficult to work with using most current relational database management systems and desktop statistics and visualization packages. They can require massively parallel processing software running thousands of server computers, beyond the structure of commonly used software tools, to capture, curate, manage, and process the data within a tolerable elapsed time. 
     Extremely large data sets can be stored and manipulated by analysts and researchers to visualize large amounts of data, detect trends, and/or otherwise interact with the data. Tens, hundreds, or thousands of processors linked in parallel can act upon such data in order to present it or simulate external forces on the data or what it represents. These data sets can involve structured data, such as that organized in a database or otherwise according to a structured model, and/or unstructured data (e.g., emails, images, data blobs (binary large objects), web pages, complex event processing). By leveraging an ability of an aspect to relatively quickly focus more (or fewer) computing resources upon an objective, the cloud infrastructure system may be better available to carry out tasks on large data sets based on demand from a business, government agency, research organization, private individual, group of like-minded individuals or organizations, or other entity. 
     In various aspects, cloud infrastructure system  1502  may be adapted to automatically provision, manage and track a customer&#39;s subscription to services offered by cloud infrastructure system  1502 . Cloud infrastructure system  1502  may provide the cloud services via different deployment models. For example, services may be provided under a public cloud model in which cloud infrastructure system  1502  is owned by an organization selling cloud services (e.g., owned by Oracle) and the services are made available to the general public or different industry enterprises. As another example, services may be provided under a private cloud model in which cloud infrastructure system  1502  is operated solely for a single organization and may provide services for one or more entities within the organization. The cloud services may also be provided under a community cloud model in which cloud infrastructure system  1502  and the services provided by cloud infrastructure system  1502  are shared by several organizations in a related community. The cloud services may also be provided under a hybrid cloud model, which is a combination of two or more different models. 
     In some aspects, the services provided by cloud infrastructure system  1502  may include one or more services provided under Software as a Service (SaaS) category, Platform as a Service (PaaS) category, Infrastructure as a Service (IaaS) category, or other categories of services including hybrid services. A customer, via a subscription order, may order one or more services provided by cloud infrastructure system  1502 . Cloud infrastructure system  1502  then performs processing to provide the services in the customer&#39;s subscription order. 
     In some aspects, the services provided by cloud infrastructure system  1502  may include, without limitation, application services, platform services and infrastructure services. In some examples, application services may be provided by the cloud infrastructure system via a SaaS platform. The SaaS platform may be configured to provide cloud services that fall under the SaaS category. For example, the SaaS platform may provide capabilities to build and deliver a suite of on-demand applications on an integrated development and deployment platform. The SaaS platform may manage and control the underlying software and infrastructure for providing the SaaS services. By utilizing the services provided by the SaaS platform, customers can utilize applications executing on the cloud infrastructure system. Customers can acquire the application services without the need for customers to purchase separate licenses and support. Various different SaaS services may be provided. Examples include, without limitation, services that provide solutions for sales performance management, enterprise integration, and business flexibility for large organizations. 
     In some aspects, platform services may be provided by the cloud infrastructure system via a PaaS platform. The PaaS platform may be configured to provide cloud services that fall under the PaaS category. Examples of platform services may include without limitation services that enable organizations (such as Oracle) to consolidate existing applications on a shared, common architecture, as well as the ability to build new applications that leverage the shared services provided by the platform. The PaaS platform may manage and control the underlying software and infrastructure for providing the PaaS services. Customers can acquire the PaaS services provided by the cloud infrastructure system without the need for customers to purchase separate licenses and support. Examples of platform services include, without limitation, Oracle Java Cloud Service (JCS), Oracle Database Cloud Service (DBCS), and others. 
     By utilizing the services provided by the PaaS platform, customers can employ programming languages and tools supported by the cloud infrastructure system and also control the deployed services. In some aspects, platform services provided by the cloud infrastructure system may include database cloud services, middleware cloud services (e.g., Oracle Fusion Middleware services), and Java cloud services. In one aspect, database cloud services may support shared service deployment models that enable organizations to pool database resources and offer customers a Database as a Service in the form of a database cloud. Middleware cloud services may provide a platform for customers to develop and deploy various business applications, and Java cloud services may provide a platform for customers to deploy Java applications, in the cloud infrastructure system. 
     Various different infrastructure services may be provided by an IaaS platform in the cloud infrastructure system. The infrastructure services facilitate the management and control of the underlying computing resources, such as storage, networks, and other fundamental computing resources for customers utilizing services provided by the SaaS platform and the PaaS platform. 
     In certain aspects, cloud infrastructure system  1502  may also include infrastructure resources  1530  for providing the resources used to provide various services to customers of the cloud infrastructure system. In one aspect, infrastructure resources  1530  may include pre-integrated and optimized combinations of hardware, such as servers, storage, and networking resources to execute the services provided by the PaaS platform and the SaaS platform. 
     In some aspects, resources in cloud infrastructure system  1502  may be shared by multiple users and dynamically re-allocated per demand. Additionally, resources may be allocated to users in different time zones. For example, cloud infrastructure system  1502  may enable a first set of users in a first time zone to utilize resources of the cloud infrastructure system for a specified number of hours and then enable the re-allocation of the same resources to another set of users located in a different time zone, thereby maximizing the utilization of resources. 
     In certain aspects, a number of internal shared services  1532  may be provided that are shared by different components or modules of cloud infrastructure system  1502  and by the services provided by cloud infrastructure system  1502 . These internal shared services may include, without limitation, a security and identity service, an integration service, an enterprise repository service, an enterprise manager service, a virus scanning and white list service, a high availability, backup and recovery service, service for enabling cloud support, an email service, a notification service, a file transfer service, and the like. 
     In certain aspects, cloud infrastructure system  1502  may provide comprehensive management of cloud services (e.g., SaaS, PaaS, and IaaS services) in the cloud infrastructure system. In one aspect, cloud management functionality may include capabilities for provisioning, managing and tracking a customer&#39;s subscription received by cloud infrastructure system  1502 , and the like. 
     In one aspect, as depicted in the figure, cloud management functionality may be provided by one or more modules, such as an order management module  1520 , an order orchestration module  1522 , an order provisioning module  1524 , an order management and monitoring module  1526 , and an identity management module  1528 . These modules may include or be provided using one or more computers and/or servers, which may be general purpose computers, specialized server computers, server farms, server clusters, or any other appropriate arrangement and/or combination. 
     In operation  1534 , a customer using a client device, such as client device  1504 ,  1506  or  1508 , may interact with cloud infrastructure system  1502  by requesting one or more services provided by cloud infrastructure system  1502  and placing an order for a subscription for one or more services offered by cloud infrastructure system  1502 . In certain aspects, the customer may access a cloud User Interface (UI), cloud UI  1512 , cloud UI  1514  and/or cloud UI  1516  and place a subscription order via these UIs. The order information received by cloud infrastructure system  1502  in response to the customer placing an order may include information identifying the customer and one or more services offered by the cloud infrastructure system  1502  that the customer intends to subscribe to. 
     After an order has been placed by the customer, the order information is received via the cloud UIs,  1512 ,  1514  and/or  1516 . 
     At operation  1536 , the order is stored in order database  1518 . Order database  1518  can be one of several databases operated by cloud infrastructure system  1502  and operated in conjunction with other system elements. 
     At operation  1538 , the order information is forwarded to an order management module  1520 . In some instances, order management module  1520  may be configured to perform billing and accounting functions related to the order, such as verifying the order, and upon verification, booking the order. 
     At operation  1540 , information regarding the order is communicated to an order orchestration module  1522 . Order orchestration module  1522  may utilize the order information to orchestrate the provisioning of services and resources for the order placed by the customer. In some instances, order orchestration module  1522  may orchestrate the provisioning of resources to support the subscribed services using the services of order provisioning module  1524 . 
     In certain aspects, order orchestration module  1522  enables the management of business processes associated with each order and applies business logic to determine whether an order should proceed to provisioning. At operation  1542 , upon receiving an order for a new subscription, order orchestration module  1522  sends a request to order provisioning module  1524  to allocate resources and configure those resources needed to fulfill the subscription order. Order provisioning module  1524  enables the allocation of resources for the services ordered by the customer. Order provisioning module  1524  provides a level of abstraction between the cloud services provided by system environment  1500  and the physical implementation layer that is used to provision the resources for providing the requested services. Order orchestration module  1522  may thus be isolated from implementation details, such as whether or not services and resources are actually provisioned on the fly or pre-provisioned and only allocated/assigned upon request. 
     At operation  1542 , once the services and resources are provisioned, a notification of the provided service may be sent to customers on client devices  1504 ,  1506  and/or  1508  by order provisioning module  1524  of cloud infrastructure system  1502 . 
     At operation  1546 , the customer&#39;s subscription order may be managed and tracked by an order management and monitoring module  1526 . In some instances, order management and monitoring module  1526  may be configured to collect usage statistics for the services in the subscription order, such as the amount of storage used, the amount data transferred, the number of users, and the amount of system up time and system down time. 
     In certain aspects, cloud infrastructure system  1502  may include an identity management module  1528 . Identity management module  1528  may be configured to provide identity services, such as access management and authorization services in cloud infrastructure system  1502 . In some aspects, identity management module  1528  may control information about customers who wish to utilize the services provided by cloud infrastructure system  1502 . Such information can include information that authenticates the identities of such customers and information that describes which actions those customers are authorized to perform relative to various system resources (e.g., files, directories, applications, communication ports, memory segments, etc.). Identity management module  1528  may also include the management of descriptive information about each customer and about how and by whom that descriptive information can be accessed and modified. 
       FIG.  16    illustrates an exemplary computer system  1600 , in which various aspects of the present invention may be implemented. The computer system  1600  may be used to implement any of the computer systems described above. As shown in the figure, computer system  1600  includes a processing unit  1604  that communicates with a number of peripheral subsystems via a bus subsystem  1602 . These peripheral subsystems may include a processing acceleration unit  1606 , an I/O subsystem  1608 , a storage subsystem  1618  and a communications subsystem  1624 . Storage subsystem  1618  includes tangible computer-readable storage media  1620  and a system memory  1610 . 
     Bus subsystem  1602  provides a mechanism for letting the various components and subsystems of computer system  1600  communicate with each other as intended. Although bus subsystem  1602  is shown schematically as a single bus, alternative aspects of the bus subsystem may utilize multiple buses. Bus subsystem  1602  may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. For example, such architectures may include an Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus, which can be implemented as a Mezzanine bus manufactured to the IEEE P1686.1 standard. 
     Processing unit  1604 , which can be implemented as one or more integrated circuits (e.g., a conventional microprocessor or microcontroller), controls the operation of computer system  1600 . One or more processors may be included in processing unit  1604 . These processors may include single core or multicore processors. In certain aspects, processing unit  1604  may be implemented as one or more independent processing units  1632  and/or  1634  with single or multicore processors included in each processing unit. In other aspects, processing unit  1604  may also be implemented as a quad-core processing unit formed by integrating two dual-core processors into a single chip. 
     In various aspects, processing unit  1604  can execute a variety of programs in response to program code and can maintain multiple concurrently executing programs or processes. At any given time, some or all of the program code to be executed can be resident in processing unit  1604  and/or in storage subsystem  1618 . Through suitable programming, processing unit  1604  can provide various functionalities described above. Computer system  1600  may additionally include a processing acceleration unit  1606 , which can include a digital signal processor (DSP), a special-purpose processor, and/or the like. 
     I/O subsystem  1608  may include user interface input devices and user interface output devices. User interface input devices may include a keyboard, pointing devices such as a mouse or trackball, a touchpad or touch screen incorporated into a display, a scroll wheel, a click wheel, a dial, a button, a switch, a keypad, audio input devices with voice command recognition systems, microphones, and other types of input devices. User interface input devices may include, for example, motion sensing and/or gesture recognition devices such as the Microsoft Kinect® motion sensor that enables users to control and interact with an input device, such as the Microsoft Xbox® 460 game controller, through a natural user interface using gestures and spoken commands. User interface input devices may also include eye gesture recognition devices such as the Google Glass® blink detector that detects eye activity (e.g., ‘blinking’ while taking pictures and/or making a menu selection) from users and transforms the eye gestures as input into an input device (e.g., Google Glass®). Additionally, user interface input devices may include voice recognition sensing devices that enable users to interact with voice recognition systems (e.g., Siri® navigator), through voice commands. 
     User interface input devices may also include, without limitation, three dimensional (4D) mice, joysticks or pointing sticks, gamepads and graphic tablets, and audio/visual devices such as speakers, digital cameras, digital camcorders, portable media players, webcams, image scanners, fingerprint scanners, barcode reader 4D scanners, 4D printers, laser rangefinders, and eye gaze tracking devices. Additionally, user interface input devices may include, for example, medical imaging input devices such as computed tomography, magnetic resonance imaging, position emission tomography, medical ultrasonography devices. User interface input devices may also include, for example, audio input devices such as MIDI keyboards, digital musical instruments and the like. 
     User interface output devices may include a display subsystem, indicator lights, or non-visual displays such as audio output devices, etc. The display subsystem may be a cathode ray tube (CRT), a flat-panel device, such as that using a liquid crystal display (LCD) or plasma display, a projection device, a touch screen, and the like. In general, use of the term “output device” is intended to include all possible types of devices and mechanisms for outputting information from computer system  1600  to a user or other computer. For example, user interface output devices may include, without limitation, a variety of display devices that visually convey text, graphics and audio/video information such as monitors, printers, speakers, headphones, automotive navigation systems, plotters, voice output devices, and modems. 
     Computer system  1600  may comprise a storage subsystem  1618  that comprises software elements, shown as being currently located within a system memory  1610 . System memory  1610  may store program instructions that are loadable and executable on processing unit  1604 , as well as data generated during the execution of these programs. 
     Depending on the configuration and type of computer system  1600 , system memory  1610  may be volatile (such as random access memory (RAM)) and/or non-volatile (such as read-only memory (ROM), flash memory, etc.) The RAM typically contains data and/or program modules that are immediately accessible to and/or presently being operated and executed by processing unit  1604 . In some implementations, system memory  1610  may include multiple different types of memory, such as static random access memory (SRAM) or dynamic random access memory (DRAM). In some implementations, a basic input/output system (BIOS), containing the basic routines that help to transfer information between elements within computer system  1600 , such as during start-up, may typically be stored in the ROM. By way of example, and not limitation, system memory  1610  also illustrates application programs  1612 , which may include client applications, Web browsers, mid-tier applications, relational database management systems (RDBMS), etc., program data  1614 , and an operating system  1616 . By way of example, operating system  1616  may include various versions of Microsoft Windows®, Apple Macintosh®, and/or Linux operating systems, a variety of commercially-available UNIX® or UNIX-like operating systems (including without limitation the variety of GNU/Linux operating systems, the Google Chrome® OS, and the like) and/or mobile operating systems such as iOS, Windows® Phone, Android® OS, BlackBerry® 15 OS, and Palm® OS operating systems. 
     Storage subsystem  1618  may also provide a tangible computer-readable storage medium for storing the basic programming and data constructs that provide the functionality of some aspects. Software (programs, code modules, instructions) that when executed by a processor provide the functionality described above may be stored in storage subsystem  1618 . These software modules or instructions may be executed by processing unit  1604 . Storage subsystem  1618  may also provide a repository for storing data used in accordance with the present invention. 
     Storage subsystem  1618  may also include a computer-readable storage media reader  1620  that can further be connected to computer-readable storage media  1642 . Together and, optionally, in combination with system memory  1610 , computer-readable storage media  1642  may comprehensively represent remote, local, fixed, and/or removable storage devices plus storage media for temporarily and/or more permanently containing, storing, transmitting, and retrieving computer-readable information. 
     Computer-readable storage media  1642  containing code, or portions of code, can also include any appropriate media known or used in the art, including storage media and communication media, such as but not limited to, volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage and/or transmission of information. This can include tangible, non-transitory computer-readable storage media such as RAM, ROM, electronically erasable programmable ROM (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disk (DVD), or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or other tangible computer readable media. When specified, this can also include nontangible, transitory computer-readable media, such as data signals, data transmissions, or any other medium which can be used to transmit the desired information and which can be accessed by computer system  1600 . 
     By way of example, computer-readable storage media  1622  may include a hard disk drive that reads from or writes to non-removable, nonvolatile magnetic media, a magnetic disk drive that reads from or writes to a removable, nonvolatile magnetic disk, and an optical disk drive that reads from or writes to a removable, nonvolatile optical disk such as a CD ROM, DVD, and Blu-Ray® disk, or other optical media. Computer-readable storage media  1620  may include, but is not limited to, Zip® drives, flash memory cards, universal serial bus (USB) flash drives, secure digital (SD) cards, DVD disks, digital video tape, and the like. Computer-readable storage media  1620  may also include, solid-state drives (SSD) based on non-volatile memory such as flash-memory based SSDs, enterprise flash drives, solid state ROM, and the like, SSDs based on volatile memory such as solid state RAM, dynamic RAM, static RAM, DRAM-based SSDs, magnetoresistive RAM (MRAM) SSDs, and hybrid SSDs that use a combination of DRAM and flash memory based SSDs. The disk drives and their associated computer-readable media may provide non-volatile storage of computer-readable instructions, data structures, program modules, and other data for computer system  1600 . 
     Communications subsystem  1624  provides an interface to other computer systems and networks. Communications subsystem  1624  serves as an interface for receiving data from and transmitting data to other systems from computer system  1600 . For example, communications subsystem  1624  may enable computer system  1600  to connect to one or more devices via the Internet. In some aspects, communications subsystem  1624  can include radio frequency (RF) transceiver components for accessing wireless voice and/or data networks (e.g., using cellular telephone technology, advanced data network technology, such as 4G, 4G or EDGE (enhanced data rates for global evolution), WiFi (IEEE 802.28 family standards, or other mobile communication technologies, or any combination thereof), global positioning system (GPS) receiver components, and/or other components. In some aspects, communications subsystem  1624  can provide wired network connectivity (e.g., Ethernet) in addition to or instead of a wireless interface. 
     In some aspects, communications subsystem  1624  may also receive input communication in the form of structured and/or unstructured data feeds  1626 , event streams  1628 , event updates  1630 , and the like on behalf of one or more users who may use computer system  1600 . 
     By way of example, communications subsystem  1624  may be configured to receive unstructured data feeds  1626  in real-time from users of social media networks and/or other communication services such as Twitter® feeds, Facebook® updates, web feeds such as Rich Site Summary (RSS) feeds, and/or real-time updates from one or more third party information sources. 
     Additionally, communications subsystem  1624  may also be configured to receive data in the form of continuous data streams, which may include event streams  1628  of real-time events and/or event updates  1630 , that may be continuous or unbounded in nature with no explicit end. Examples of applications that generate continuous data may include, for example, sensor data applications, financial tickers, network performance measuring tools (e.g. network monitoring and traffic management applications), clickstream analysis tools, automobile traffic monitoring, and the like. 
     Communications subsystem  1624  may also be configured to output the structured and/or unstructured data feeds  1626 , event streams  1628 , event updates  1630 , and the like to one or more databases that may be in communication with one or more streaming data source computers coupled to computer system  1600 . 
     Computer system  1600  can be one of various types, including a handheld portable device (e.g., an iPhone® cellular phone, an iPad® computing tablet, a PDA), a wearable device (e.g., a Google Glass® head mounted display), a PC, a workstation, a mainframe, a kiosk, a server rack, or any other data processing system. 
     Due to the ever-changing nature of computers and networks, the description of computer system  1600  depicted in the figure is intended only as a specific example. Many other configurations having more or fewer components than the system depicted in the figure are possible. For example, customized hardware might also be used and/or particular elements might be implemented in hardware, firmware, software (including applets), or a combination. Further, connection to other computing devices, such as network input/output devices, may be employed. Based on the disclosure and teachings provided herein, a person of ordinary skill in the art will appreciate other ways and/or methods to implement the various aspects. 
     In the foregoing specification, aspects of the invention are described with reference to specific aspects thereof, but those skilled in the art will recognize that the invention is not limited thereto. Various features and aspects of the above-described invention may be used individually or jointly. Further, aspects can be utilized in any number of environments and applications beyond those described herein without departing from the broader spirit and scope of the specification. The specification and drawings are, accordingly, to be regarded as illustrative rather than restrictive.