Patent Publication Number: US-11645263-B2

Title: Systems and methods for managing a highly available and scalable distributed database in a cloud computing environment

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of and claims the benefit of priority to U.S. application Ser. No. 17/105,127, filed Nov. 25, 2020 (now allowed), the contents of which are hereby incorporated herein by reference. 
    
    
     TECHNICAL FIELD 
     The present disclosure generally relates to computerized methods and systems for building and maintaining a highly available and scalable distributed database in a cloud computing environment. In particular, embodiments of the present disclosure relate to inventive and unconventional systems that maximize uptime, minimize error from prolonged usage, and minimize failover time of databases by utilizing a data store to monitor the source of truth and notify the user device of any changes. 
     BACKGROUND 
     Certain systems require databases which are always available. The availability of a database is measured by the percentage of healthy time in its lifetime. Generally, highly available databases are those that are available 99.999% of the time or more. That is, they are down for fewer than 5.26 minutes per year. One method for achieving high availability in a database is to create a distributed database. This is a database where data are stored in multiple nodes in different locations. A plurality of database nodes is called a cluster. In most cases, a cluster consists of one source which serves write requests, and one or more replicas to serve read requests. 
     The idea behind distributed databases is that, should one node fail, there are others with the same data ready to take its place. Therefore, the database as a whole does not have to remain unavailable until the failed node comes back online. When a node fails, a distributed database will usually select another node to take its place and the period during which this occurs is called failover. Different systems have different failover times, but most still take minutes, which could be disastrous for certain businesses. Further, there is currently no standalone solution which can manage the distributed database and reduce failover time in a cost-effective way. Indeed, current solutions solve problems with availability by adding nodes to the distributed database, which is highly inefficient and costly. 
     Therefore, there is a need for systems and methods for managing a highly available and scalable distributed database in a cloud computing environment which reduce failover time to seconds and provide a standalone solution, with minimal redundancy for cost-efficiency. Such systems and methods would minimize failover time, lower the failure rate, and achieve greater uptime as a whole, providing businesses with a cost-effective solution which minimizes interruptions due to failures. 
     SUMMARY 
     One aspect of the present disclosure is directed to a computer-implemented system for managing a highly available distributed database in a cloud computing environment. The system may comprise a memory storing instructions; and one or more processors configured to execute the instructions to: determine that a source node, in a distributed database comprising the source node and one or more replica nodes, is not available; select a most-updated replica node from the one or more replica nodes; switch a role of the most-updated replica node from replica to source; update a data store to label the source node as unavailable and the selected replica node as being a promoted source node; send a notification to a user device connected to the distributed database to update a database topology log based on the updated data store; determine whether the user device has updated the database topology log; and upon determining the user device has not updated the database topology log, continue to send the notification to the user device until the user device has updated the database topology log. 
     Yet another aspect of the present disclosure is directed to a computer-implemented method for managing a highly available distributed database in a cloud computing environment. The method may comprise: determining that a source node, in a distributed database comprising the source node and one or more replica nodes, is not available; selecting a most-updated replica node from the one or more replica nodes; switching a role of the most-updated replica node from replica to source; updating a data store to label the source node as unavailable and the selected replica node as being a promoted source node; sending a notification to a user device connected to the distributed database to update a database topology log based on the updated data store; determining whether the user device has updated the database topology log; and upon determining the user device has not updated the database topology log, continuing to send the notification to the user device until the user device has updated the database topology log. 
     Still further, another aspect of the present disclosure is directed to a computer-implemented system for managing a highly available distributed database in a cloud computing environment. The system may comprise: a memory storing instructions; and one or more processors configured to execute the instructions to: determine that a source node, in a distributed database existing in a cloud computing environment comprising the source node and one or more replica nodes, is not available; select a most-updated replica node from the one or more replica nodes; switch a role of the most-updated replica node from replica to source; update a data store to label the source node as unavailable and the selected replica node as being a promoted source node; send a notification to a user device connected to the distributed database to update a database topology log based on the updated data store; determine whether the user device has updated the database topology log by checking the data store from a confirmation from the user device; upon determining the user device has not updated the database topology log, continue to send the notification to the user device until the user device has updated the database topology; and upon determining the user device has updated the database topology log, terminating the previous connection with the user device. 
     Other systems, methods, and computer-readable media are also discussed herein. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1 A  is a schematic block diagram illustrating an exemplary embodiment of a network comprising computerized systems for communications enabling shipping, transportation, and logistics operations, consistent with the disclosed embodiments. 
         FIG.  1 B  depicts a sample Search Result Page (SRP) that includes one or more search results satisfying a search request along with interactive user interface elements, consistent with the disclosed embodiments. 
         FIG.  1 C  depicts a sample Single Display Page (SDP) that includes a product and information about the product along with interactive user interface elements, consistent with the disclosed embodiments. 
         FIG.  1 D  depicts a sample Cart page that includes items in a virtual shopping cart along with interactive user interface elements, consistent with the disclosed embodiments. 
         FIG.  1 E  depicts a sample Order page that includes items from the virtual shopping cart along with information regarding purchase and shipping, along with interactive user interface elements, consistent with the disclosed embodiments. 
         FIG.  2    is a diagrammatic illustration of an exemplary fulfillment center configured to utilize disclosed computerized systems, consistent with the disclosed embodiments. 
         FIG.  3    is a schematic block diagram illustrating an exemplary embodiment of a cloud environment comprising a distributed database and a system for managing the distributed database, consistent with the disclosed embodiments. 
         FIG.  4 A  is a flowchart of an exemplary computerized method for replacing a source node with a replica node following a failure of the source node, consistent with the disclosed embodiments. 
         FIG.  4 B  is a flowchart of an exemplary computerized method for replacing a replica node following a failure of the replica node, consistent with the disclosed embodiments. 
         FIG.  5    is a flowchart of an exemplary computerized method for replacing a connection from a user device to a database after a change in the topology of the database, consistent with the disclosed embodiments. 
         FIG.  6    is a flowchart of an exemplary computerized method for ensuring the database topology is consistent with a data store, consistent with the disclosed embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     The following detailed description refers to the accompanying drawings. Wherever possible, the same reference numbers are used in the drawings and the following description to refer to the same or similar parts. While several illustrative embodiments are described herein, modifications, adaptations and other implementations are possible. For example, substitutions, additions, or modifications may be made to the components and steps illustrated in the drawings, and the illustrative methods described herein may be modified by substituting, reordering, removing, or adding steps to the disclosed methods. Accordingly, the following detailed description is not limited to the disclosed embodiments and examples. Instead, the proper scope of the invention is defined by the appended claims. 
     Embodiments of the present disclosure are directed to computerized methods and systems that manage a highly available and scalable distributed database, where constant uptime and minimal error rate are desired. 
     Referring to  FIG.  1 A , a schematic block diagram  100  illustrating an exemplary embodiment of a system comprising computerized systems for communications enabling shipping, transportation, and logistics operations is shown. As illustrated in  FIG.  1 A , system  100  may include a variety of systems, each of which may be connected to one another via one or more networks. The systems may also be connected to one another via a direct connection, for example, using a cable. The depicted systems include a shipment authority technology (SAT) system  101 , an external front end system  103 , an internal front end system  105 , a transportation system  107 , mobile devices  107 A,  107 B, and  107 C, seller portal  109 , shipment and order tracking (SOT) system  111 , fulfillment optimization (FO) system  113 , fulfillment messaging gateway (FMG)  115 , supply chain management (SCM) system  117 , warehouse management system  119 , mobile devices  119 A,  119 B, and  119 C (depicted as being inside of fulfillment center (FC)  200 ), 3rd party fulfillment systems  121 A,  121 B, and  121 C, fulfillment center authorization system (FC Auth)  123 , and labor management system (LMS)  125 . 
     SAT system  101 , in some embodiments, may be implemented as a computer system that monitors order status and delivery status. For example, SAT system  101  may determine whether an order is past its Promised Delivery Date (PDD) and may take appropriate action, including initiating a new order, reshipping the items in the non-delivered order, canceling the non-delivered order, initiating contact with the ordering customer, or the like. SAT system  101  may also monitor other data, including output (such as a number of packages shipped during a particular time period) and input (such as the number of empty cardboard boxes received for use in shipping). SAT system  101  may also act as a gateway between different devices in system  100 , enabling communication (e.g., using store-and-forward or other techniques) between devices such as external front end system  103  and FO system  113 . 
     External front end system  103 , in some embodiments, may be implemented as a computer system that enables external users to interact with one or more systems in system  100 . For example, in embodiments where system  100  enables the presentation of systems to enable users to place an order for an item, external front end system  103  may be implemented as a web server that receives search requests, presents item pages, and solicits payment information. For example, external front end system  103  may be implemented as a computer or computers running software such as the Apache HTTP Server, Microsoft Internet Information Services (IIS), NGINX, or the like. In other embodiments, external front end system  103  may run custom web server software designed to receive and process requests from external devices (e.g., mobile device  102 A or computer  102 B), acquire information from databases and other data stores based on those requests, and provide responses to the received requests based on acquired information. 
     In some embodiments, external front end system  103  may include one or more of a web caching system, a database, a search system, or a payment system. In one aspect, external front end system  103  may comprise one or more of these systems, while in another aspect, external front end system  103  may comprise interfaces (e.g., server-to-server, database-to-database, or other network connections) connected to one or more of these systems. 
     An illustrative set of steps, illustrated by  FIGS.  1 B,  1 C,  1 D, and  1 E , will help to describe some operations of external front end system  103 . External front end system  103  may receive information from systems or devices in system  100  for presentation and/or display. For example, external front end system  103  may host or provide one or more web pages, including a Search Result Page (SRP) (e.g.,  FIG.  1 B ), a Single Detail Page (SDP) (e.g.,  FIG.  1 C ), a Cart page (e.g.,  FIG.  1 D ), or an Order page (e.g.,  FIG.  1 E ). A user device (e.g., using mobile device  102 A or computer  102 B) may navigate to external front end system  103  and request a search by entering information into a search box. External front end system  103  may request information from one or more systems in system  100 . For example, external front end system  103  may request information from FO System  113  that satisfies the search request. External front end system  103  may also request and receive (from FO System  113 ) a Promised Delivery Date or “PDD” for each product included in the search results. The PDD, in some embodiments, may represent an estimate of when a package containing the product will arrive at the user&#39;s desired location or a date by which the product is promised to be delivered at the user&#39;s desired location if ordered within a particular period of time, for example, by the end of the day (11:59 PM). (PDD is discussed further below with respect to FO System  113 .) 
     External front end system  103  may prepare an SRP (e.g.,  FIG.  1 B ) based on the information. The SRP may include information that satisfies the search request. For example, this may include pictures of products that satisfy the search request. The SRP may also include respective prices for each product, or information relating to enhanced delivery options for each product, PDD, weight, size, offers, discounts, or the like. External front end system  103  may send the SRP to the requesting user device (e.g., via a network). 
     A user device may then select a product from the SRP, e.g., by clicking or tapping a user interface, or using another input device, to select a product represented on the SRP. The user device may formulate a request for information on the selected product and send it to external front end system  103 . In response, external front end system  103  may request information related to the selected product. For example, the information may include additional information beyond that presented for a product on the respective SRP. This could include, for example, shelf life, country of origin, weight, size, number of items in package, handling instructions, or other information about the product. The information could also include recommendations for similar products (based on, for example, big data and/or machine learning analysis of customers who bought this product and at least one other product), answers to frequently asked questions, reviews from customers, manufacturer information, pictures, or the like. 
     External front end system  103  may prepare an SDP (Single Detail Page) (e.g.,  FIG.  1 C ) based on the received product information. The SDP may also include other interactive elements such as a “Buy Now” button, a “Add to Cart” button, a quantity field, a picture of the item, or the like. The SDP may further include a list of sellers that offer the product. The list may be ordered based on the price each seller offers such that the seller that offers to sell the product at the lowest price may be listed at the top. The list may also be ordered based on the seller ranking such that the highest ranked seller may be listed at the top. The seller ranking may be formulated based on multiple factors, including, for example, the seller&#39;s past track record of meeting a promised PDD. External front end system  103  may deliver the SDP to the requesting user device (e.g., via a network). 
     The requesting user device may receive the SDP which lists the product information. Upon receiving the SDP, the user device may then interact with the SDP. For example, a user of the requesting user device may click or otherwise interact with a “Place in Cart” button on the SDP. This adds the product to a shopping cart associated with the user. The user device may transmit this request to add the product to the shopping cart to external front end system  103 . 
     External front end system  103  may generate a Cart page (e.g.,  FIG.  1 D ). The Cart page, in some embodiments, lists the products that the user has added to a virtual “shopping cart.” A user device may request the Cart page by clicking on or otherwise interacting with an icon on the SRP, SDP, or other pages. The Cart page may, in some embodiments, list all products that the user has added to the shopping cart, as well as information about the products in the cart such as a quantity of each product, a price for each product per item, a price for each product based on an associated quantity, information regarding PDD, a delivery method, a shipping cost, user interface elements for modifying the products in the shopping cart (e.g., deletion or modification of a quantity), options for ordering other product or setting up periodic delivery of products, options for setting up interest payments, user interface elements for proceeding to purchase, or the like. A user at a user device may click on or otherwise interact with a user interface element (e.g., a button that reads “Buy Now”) to initiate the purchase of the product in the shopping cart. Upon doing so, the user device may transmit this request to initiate the purchase to external front end system  103 . 
     External front end system  103  may generate an Order page (e.g.,  FIG.  1 E ) in response to receiving the request to initiate a purchase. The Order page, in some embodiments, re-lists the items from the shopping cart and requests input of payment and shipping information. For example, the Order page may include a section requesting information about the purchaser of the items in the shopping cart (e.g., name, address, e-mail address, phone number), information about the recipient (e.g., name, address, phone number, delivery information), shipping information (e.g., speed/method of delivery and/or pickup), payment information (e.g., credit card, bank transfer, check, stored credit), user interface elements to request a cash receipt (e.g., for tax purposes), or the like. External front end system  103  may send the Order page to the user device. 
     The user device may enter information on the Order page and click or otherwise interact with a user interface element that sends the information to external front end system  103 . From there, external front end system  103  may send the information to different systems in system  100  to enable the creation and processing of a new order with the products in the shopping cart. 
     In some embodiments, external front end system  103  may be further configured to enable sellers to transmit and receive information relating to orders. 
     Internal front end system  105 , in some embodiments, may be implemented as a computer system that enables internal users (e.g., employees of an organization that owns, operates, or leases system  100 ) to interact with one or more systems in system  100 . For example, in embodiments where system  100  enables the presentation of systems to enable users to place an order for an item, internal front end system  105  may be implemented as a web server that enables internal users to view diagnostic and statistical information about orders, modify item information, or review statistics relating to orders. For example, internal front end system  105  may be implemented as a computer or computers running software such as the Apache HTTP Server, Microsoft Internet Information Services (IIS), NGINX, or the like. In other embodiments, internal front end system  105  may run custom web server software designed to receive and process requests from systems or devices depicted in system  100  (as well as other devices not depicted), acquire information from databases and other data stores based on those requests, and provide responses to the received requests based on acquired information. 
     In some embodiments, internal front end system  105  may include one or more of a web caching system, a database, a search system, a payment system, an analytics system, an order monitoring system, or the like. In one aspect, internal front end system  105  may comprise one or more of these systems, while in another aspect, internal front end system  105  may comprise interfaces (e.g., server-to-server, database-to-database, or other network connections) connected to one or more of these systems. 
     Transportation system  107 , in some embodiments, may be implemented as a computer system that enables communication between systems or devices in system  100  and mobile devices  107 A- 107 C. Transportation system  107 , in some embodiments, may receive information from one or more mobile devices  107 A- 107 C (e.g., mobile phones, smart phones, PDAs, or the like). For example, in some embodiments, mobile devices  107 A- 107 C may comprise devices operated by delivery workers. The delivery workers, who may be permanent, temporary, or shift employees, may utilize mobile devices  107 A- 107 C to effect delivery of packages containing the products ordered by users. For example, to deliver a package, the delivery worker may receive a notification on a mobile device indicating which package to deliver and where to deliver it. Upon arriving at the delivery location, the delivery worker may locate the package (e.g., in the back of a truck or in a crate of packages), scan or otherwise capture data associated with an identifier on the package (e.g., a barcode, an image, a text string, an RFID tag, or the like) using the mobile device, and deliver the package (e.g., by leaving it at a front door, leaving it with a security guard, handing it to the recipient, or the like). In some embodiments, the delivery worker may capture photo(s) of the package and/or may obtain a signature using the mobile device. The mobile device may send information to transportation system  107  including information about the delivery, including, for example, time, date, GPS location, photo(s), an identifier associated with the delivery worker, an identifier associated with the mobile device, or the like. Transportation system  107  may store this information in a database (not pictured) for access by other systems in system  100 . Transportation system  107  may, in some embodiments, use this information to prepare and send tracking data to other systems indicating the location of a particular package. 
     In some embodiments, certain users may use one kind of mobile device (e.g., permanent workers may use a specialized PDA with custom hardware such as a barcode scanner, stylus, and other devices) while other users may use other kinds of mobile devices (e.g., temporary or shift workers may utilize off-the-shelf mobile phones and/or smartphones). 
     In some embodiments, transportation system  107  may associate a user with each device. For example, transportation system  107  may store an association between a user (represented by, e.g., a user identifier, an employee identifier, or a phone number) and a mobile device (represented by, e.g., an International Mobile Equipment Identity (IMEI), an International Mobile Subscription Identifier (IMSI), a phone number, a Universal Unique Identifier (UUID), or a Globally Unique Identifier (GUID)). Transportation system  107  may use this association in conjunction with data received on deliveries to analyze data stored in the database in order to determine, among other things, a location of the worker, an efficiency of the worker, or a speed of the worker. 
     Seller portal  109 , in some embodiments, may be implemented as a computer system that enables sellers or other external entities to electronically communicate with one or more systems in system  100 . For example, a seller may utilize a computer system (not pictured) to upload or provide product information, order information, contact information, or the like, for products that the seller wishes to sell through system  100  using seller portal  109 . 
     Shipment and order tracking system  111 , in some embodiments, may be implemented as a computer system that receives, stores, and forwards information regarding the location of packages containing products ordered by customers (e.g., by a user using devices  102 A- 102 B). In some embodiments, shipment and order tracking system  111  may request or store information from web servers (not pictured) operated by shipping companies that deliver packages containing products ordered by customers. 
     In some embodiments, shipment and order tracking system  111  may request and store information from systems depicted in system  100 . For example, shipment and order tracking system  111  may request information from transportation system  107 . As discussed above, transportation system  107  may receive information from one or more mobile devices  107 A- 107 C (e.g., mobile phones, smart phones, PDAs, or the like) that are associated with one or more of a user (e.g., a delivery worker) or a vehicle (e.g., a delivery truck). In some embodiments, shipment and order tracking system  111  may also request information from warehouse management system (WMS)  119  to determine the location of individual products inside of a fulfillment center (e.g., fulfillment center  200 ). Shipment and order tracking system  111  may request data from one or more of transportation system  107  or WMS  119 , process it, and present it to a device (e.g., user devices  102 A and  102 B) upon request. 
     Fulfillment optimization (FO) system  113 , in some embodiments, may be implemented as a computer system that stores information for customer orders from other systems (e.g., external front end system  103  and/or shipment and order tracking system  111 ). FO system  113  may also store information describing where particular items are held or stored. For example, certain items may be stored only in one fulfillment center, while certain other items may be stored in multiple fulfillment centers. In still other embodiments, certain fulfilment centers may be designed to store only a particular set of items (e.g., fresh produce or frozen products). FO system  113  stores this information as well as associated information (e.g., quantity, size, date of receipt, expiration date, etc.). 
     FO system  113  may also calculate a corresponding PDD (promised delivery date) for each product. The PDD, in some embodiments, may be based on one or more factors. For example, FO system  113  may calculate a PDD for a product based on a past demand for a product (e.g., how many times that product was ordered during a period of time), an expected demand for a product (e.g., how many customers are forecast to order the product during an upcoming period of time), a network-wide past demand indicating how many products were ordered during a period of time, a network-wide expected demand indicating how many products are expected to be ordered during an upcoming period of time, one or more counts of the product stored in each fulfillment center  200 , which fulfillment center stores each product, expected or current orders for that product, or the like. 
     In some embodiments, FO system  113  may determine a PDD for each product on a periodic basis (e.g., hourly) and store it in a database for retrieval or sending to other systems (e.g., external front end system  103 , SAT system  101 , shipment and order tracking system  111 ). In other embodiments, FO system  113  may receive electronic requests from one or more systems (e.g., external front end system  103 , SAT system  101 , shipment and order tracking system  111 ) and calculate the PDD on demand. 
     Fulfilment messaging gateway (FMG)  115 , in some embodiments, may be implemented as a computer system that receives a request or response in one format or protocol from one or more systems in system  100 , such as FO system  113 , converts it to another format or protocol, and forward it in the converted format or protocol to other systems, such as WMS  119  or 3rd party fulfillment systems  121 A,  121 B, or  121 C, and vice versa. 
     Supply chain management (SCM) system  117 , in some embodiments, may be implemented as a computer system that performs forecasting functions. For example, SCM system  117  may forecast a level of demand for a particular product based on, for example, based on a past demand for products, an expected demand for a product, a network-wide past demand, a network-wide expected demand, a count products stored in each fulfillment center  200 , expected or current orders for each product, or the like. In response to this forecasted level and the amount of each product across all fulfillment centers, SCM system  117  may generate one or more purchase orders to purchase and stock a sufficient quantity to satisfy the forecasted demand for a particular product. 
     Warehouse management system (WMS)  119 , in some embodiments, may be implemented as a computer system that monitors workflow. For example, WMS  119  may receive event data from individual devices (e.g., devices  107 A- 107 C or  119 A- 119 C) indicating discrete events. For example, WMS  119  may receive event data indicating the use of one of these devices to scan a package. As discussed below with respect to fulfillment center  200  and  FIG.  2   , during the fulfillment process, a package identifier (e.g., a barcode or RFID tag data) may be scanned or read by machines at particular stages (e.g., automated or handheld barcode scanners, RFID readers, high-speed cameras, devices such as tablet  119 A, mobile device/PDA  1198 , computer  119 C, or the like). WMS  119  may store each event indicating a scan or a read of a package identifier in a corresponding database (not pictured) along with the package identifier, a time, date, location, user identifier, or other information, and may provide this information to other systems (e.g., shipment and order tracking system  111 ). 
     WMS  119 , in some embodiments, may store information associating one or more devices (e.g., devices  107 A- 107 C or  119 A- 119 C) with one or more users associated with system  100 . For example, in some situations, a user (such as a part- or full-time employee) may be associated with a mobile device in that the user owns the mobile device (e.g., the mobile device is a smartphone). In other situations, a user may be associated with a mobile device in that the user is temporarily in custody of the mobile device (e.g., the user checked the mobile device out at the start of the day, will use it during the day, and will return it at the end of the day). 
     WMS  119 , in some embodiments, may maintain a work log for each user associated with system  100 . For example, WMS  119  may store information associated with each employee, including any assigned processes (e.g., unloading trucks, picking items from a pick zone, rebin wall work, packing items), a user identifier, a location (e.g., a floor or zone in a fulfillment center  200 ), a number of units moved through the system by the employee (e.g., number of items picked, number of items packed), an identifier associated with a device (e.g., devices  119 A- 119 C), or the like. In some embodiments, WMS  119  may receive check-in and check-out information from a timekeeping system, such as a timekeeping system operated on a device  119 A- 119 C. 
     3rd party fulfillment (3PL) systems  121 A- 121 C, in some embodiments, represent computer systems associated with third-party providers of logistics and products. For example, while some products are stored in fulfillment center  200  (as discussed below with respect to  FIG.  2   ), other products may be stored off-site, may be produced on demand, or may be otherwise unavailable for storage in fulfillment center  200 . 3PL systems  121 A- 121 C may be configured to receive orders from FO system  113  (e.g., through FMG  115 ) and may provide products and/or services (e.g., delivery or installation) to customers directly. In some embodiments, one or more of 3PL systems  121 A- 121 C may be part of system  100 , while in other embodiments, one or more of 3PL systems  121 A- 121 C may be outside of system  100  (e.g., owned or operated by a third party provider). 
     Fulfillment Center Auth system (FC Auth)  123 , in some embodiments, may be implemented as a computer system with a variety of functions. For example, in some embodiments, FC Auth  123  may act as a single-sign on (SSO) service for one or more other systems in system  100 . For example, FC Auth  123  may enable a user to log in via internal front end system  105 , determine that the user has similar privileges to access resources at shipment and order tracking system  111 , and enable the user to access those privileges without requiring a second log in process. FC Auth  123 , in other embodiments, may enable users (e.g., employees) to associate themselves with a particular task. For example, some employees may not have an electronic device (such as devices  119 A- 119 C) and may instead move from task to task, and zone to zone, within a fulfillment center  200 , during the course of a day. FC Auth  123  may be configured to enable those employees to indicate what task they are performing and what zone they are in at different times of day. 
     Labor management system (LMS)  125 , in some embodiments, may be implemented as a computer system that stores attendance and overtime information for employees (including full-time and part-time employees). For example, LMS  125  may receive information from FC Auth  123 , WMS  119 , devices  119 A- 119 C, transportation system  107 , and/or devices  107 A- 107 C. 
     The particular configuration depicted in  FIG.  1 A  is an example only. For example, while  FIG.  1 A  depicts FC Auth system  123  connected to FO system  113 , not all embodiments require this particular configuration. Indeed, in some embodiments, the systems in system  100  may be connected to one another through one or more public or private networks, including the Internet, an Intranet, a WAN (Wide-Area Network), a MAN (Metropolitan-Area Network), a wireless network compliant with the IEEE 802.11a/b/g/n Standards, a leased line, or the like. In some embodiments, one or more of the systems in system  100  may be implemented as one or more virtual servers implemented at a data center, server farm, or the like. 
       FIG.  2    depicts a fulfillment center  200 . Fulfillment center  200  is an example of a physical location that stores items for shipping to customers when ordered. Fulfillment center (FC)  200  may be divided into multiple zones, each of which are depicted in  FIG.  2   . These “zones,” in some embodiments, may be thought of as virtual divisions between different stages of a process of receiving items, storing the items, retrieving the items, and shipping the items. So while the “zones” are depicted in  FIG.  2   , other divisions of zones are possible, and the zones in  FIG.  2    may be omitted, duplicated, or modified in some embodiments. 
     Inbound zone  203  represents an area of FC  200  where items are received from sellers who wish to sell products using system  100  from  FIG.  1 A . For example, a seller may deliver items  202 A and  202 B using truck  201 . Item  202 A may represent a single item large enough to occupy its own shipping pallet, while item  202 B may represent a set of items that are stacked together on the same pallet to save space. 
     A worker will receive the items in inbound zone  203  and may optionally check the items for damage and correctness using a computer system (not pictured). For example, the worker may use a computer system to compare the quantity of items  202 A and  202 B to an ordered quantity of items. If the quantity does not match, that worker may refuse one or more of items  202 A or  2026 . If the quantity does match, the worker may move those items (using, e.g., a dolly, a handtruck, a forklift, or manually) to buffer zone  205 . Buffer zone  205  may be a temporary storage area for items that are not currently needed in the picking zone, for example, because there is a high enough quantity of that item in the picking zone to satisfy forecasted demand. In some embodiments, forklifts  206  operate to move items around buffer zone  205  and between inbound zone  203  and drop zone  207 . If there is a need for items  202 A or  202 B in the picking zone (e.g., because of forecasted demand), a forklift may move items  202 A or  202 B to drop zone  207 . 
     Drop zone  207  may be an area of FC  200  that stores items before they are moved to picking zone  209 . A worker assigned to the picking task (a “picker”) may approach items  202 A and  202 B in the picking zone, scan a barcode for the picking zone, and scan barcodes associated with items  202 A and  202 B using a mobile device (e.g., device  119 B). The picker may then take the item to picking zone  209  (e.g., by placing it on a cart or carrying it). 
     Picking zone  209  may be an area of FC  200  where items  208  are stored on storage units  210 . In some embodiments, storage units  210  may comprise one or more of physical shelving, bookshelves, boxes, totes, refrigerators, freezers, cold stores, or the like. In some embodiments, picking zone  209  may be organized into multiple floors. In some embodiments, workers or machines may move items into picking zone  209  in multiple ways, including, for example, a forklift, an elevator, a conveyor belt, a cart, a handtruck, a dolly, an automated robot or device, or manually. For example, a picker may place items  202 A and  202 B on a handtruck or cart in drop zone  207  and walk items  202 A and  202 B to picking zone  209 . 
     A picker may receive an instruction to place (or “stow”) the items in particular spots in picking zone  209 , such as a particular space on a storage unit  210 . For example, a picker may scan item  202 A using a mobile device (e.g., device  119 B). The device may indicate where the picker should stow item  202 A, for example, using a system that indicate an aisle, shelf, and location. The device may then prompt the picker to scan a barcode at that location before stowing item  202 A in that location. The device may send (e.g., via a wireless network) data to a computer system such as WMS  119  in  FIG.  1 A  indicating that item  202 A has been stowed at the location by the user using device  1196 . 
     Once a user places an order, a picker may receive an instruction on device  119 B to retrieve one or more items  208  from storage unit  210 . The picker may retrieve item  208 , scan a barcode on item  208 , and place it on transport mechanism  214 . While transport mechanism  214  is represented as a slide, in some embodiments, transport mechanism may be implemented as one or more of a conveyor belt, an elevator, a cart, a forklift, a handtruck, a dolly, a cart, or the like. Item  208  may then arrive at packing zone  211 . 
     Packing zone  211  may be an area of FC  200  where items are received from picking zone  209  and packed into boxes or bags for eventual shipping to customers. In packing zone  211 , a worker assigned to receiving items (a “rebin worker”) will receive item  208  from picking zone  209  and determine what order it corresponds to. For example, the rebin worker may use a device, such as computer  119 C, to scan a barcode on item  208 . Computer  119 C may indicate visually which order item  208  is associated with. This may include, for example, a space or “cell” on a wall  216  that corresponds to an order. Once the order is complete (e.g., because the cell contains all items for the order), the rebin worker may indicate to a packing worker (or “packer”) that the order is complete. The packer may retrieve the items from the cell and place them in a box or bag for shipping. The packer may then send the box or bag to a hub zone  213 , e.g., via forklift, cart, dolly, handtruck, conveyor belt, manually, or otherwise. 
     Hub zone  213  may be an area of FC  200  that receives all boxes or bags (“packages”) from packing zone  211 . Workers and/or machines in hub zone  213  may retrieve package  218  and determine which portion of a delivery area each package is intended to go to, and route the package to an appropriate camp zone  215 . For example, if the delivery area has two smaller sub-areas, packages will go to one of two camp zones  215 . In some embodiments, a worker or machine may scan a package (e.g., using one of devices  119 A- 119 C) to determine its eventual destination. Routing the package to camp zone  215  may comprise, for example, determining a portion of a geographical area that the package is destined for (e.g., based on a postal code) and determining a camp zone  215  associated with the portion of the geographical area. 
     Camp zone  215 , in some embodiments, may comprise one or more buildings, one or more physical spaces, or one or more areas, where packages are received from hub zone  213  for sorting into routes and/or sub-routes. In some embodiments, camp zone  215  is physically separate from FC  200  while in other embodiments camp zone  215  may form a part of FC  200 . 
     Workers and/or machines in camp zone  215  may determine which route and/or sub route a package  220  should be associated with, for example, based on a comparison of the destination to an existing route and/or sub-route, a calculation of workload for each route and/or sub-route, the time of day, a shipping method, the cost to ship the package  220 , a PDD associated with the items in package  220 , or the like. In some embodiments, a worker or machine may scan a package (e.g., using one of devices  119 A- 119 C) to determine its eventual destination. Once package  220  is assigned to a particular route and/or sub route, a worker and/or machine may move package  220  to be shipped. In exemplary  FIG.  2   , camp zone  215  includes a truck  222 , a car  226 , and delivery workers  224 A and  224 B. In some embodiments, truck  222  may be driven by delivery worker  224 A, where delivery worker  224 A is a full-time employee that delivers packages for FC  200  and truck  222  is owned, leased, or operated by the same company that owns, leases, or operates FC  200 . In some embodiments, car  226  may be driven by delivery worker  224 B, where delivery worker  224 B is a “flex” or occasional worker that is delivering on an as-needed basis (e.g., seasonally). Car  226  may be owned, leased, or operated by delivery worker  224 B. 
       FIG.  3    is a schematic block diagram illustrating an exemplary embodiment of a cloud environment  300  comprising a distributed database and a system for managing the distributed database. Cloud environment  300  may comprise a variety of computerized systems, each of which may be connected to each other via one or more networks. In some embodiments, each of the elements depicted in  FIG.  3    may represent a group of systems, individual systems in a network of systems, functional units or modules inside a system, or any combination thereof. And in some embodiments, each of the elements may communicate with each other via one or more public or private network connections including the Internet, an intranet, a WAN (Wide-Area Network), a MAN (Metropolitan-Area Network), a wireless network compliant with the IEEE 802.11a/b/g/n Standards, a wired network, or the like. The individual systems may also be located within one geographical location or be geographically dispersed. 
     In some embodiments, the depicted systems may include an orchestrator  310 , a distributed consistent store  320 , a database cluster  330  including a source node  331  and a plurality of replica nodes  332  (depicted are two replica nodes  332   a  and  332   b ), a health checker  340 , and a user device  350 . While only two replica nodes  332   a  and  332   b  are depicted in  FIG.  3   , the number is only exemplary and fewer or additional replica nodes may be implemented. 
     Each system depicted in  FIG.  3    may take the form of a server, general-purpose computer, a mainframe computer, a special-purpose computing device such as a graphical processing unit (GPU), laptop, or any combination of these computing devices. In other embodiments, each system or a subset of the systems may be implemented as one or more functional units of a single system. Additionally or alternatively, each system or a subset thereof may be a standalone system, or a part of a subsystem, which may be part of a larger system. 
     Orchestrator  310 , in some embodiments, may be any computerized system configured to manage the topology of database cluster  330 . The topology of a database cluster refers to the arrangement of the elements (i.e., nodes) in a network of connected databases. For example, the topology of database cluster  330  may be described as three nodes, with a source node which serves write queries (i.e., source node  331 ) and two replica nodes which serve read queries (i.e., replica nodes  332   a  and  332   b ). In some embodiments, orchestrator  310  may determine that source node  331  and/or one or more replica nodes  332  are not available. Upon this determination, orchestrator  310  may trigger a failover method which may replace the failed nodes with healthy nodes and update consistent store  320  with the new topology of database cluster  330 . Orchestrator  310  may be a relational database management system (RDBMS) such as, but not limited to, Oracle Database, MySQL, Microsoft SQL Server, and IBM DB2. In some embodiments, orchestrator  310  may be distributed such that should one server endpoint of orchestrator  310  fail, one or more endpoints remain to continue managing database cluster  330 . 
     Distributed consistent store  320 , in some embodiments, may be any computerized system configured to store information relating to the topology of database cluster  330  and also configured to send notifications regarding the topology of database cluster  330  to user device  350 . Consistent store  320  may be a relational database where data stored therein is organized in one or more data sets. For example, consistent store  320  may contain information labeling source node  331  as the source node and replica nodes  332   a  and  332   b  as replica nodes. Additionally, consistent store  320  may contain information regarding the current connections user device  350  maintains with database cluster  330 , user device  350  data and statistics, and a last seen time corresponding to the last time either orchestrator  310 , health checker  340 , and/or user device  350  interacted with consistent store  320 . In some embodiments, consistent store  320  may be equipped to send a notification to user device  350  to record the new database topology of database cluster  330 . 
     In other embodiments, consistent store  320  may be able to detect whether user device  350  has updated its database topology following the notification. This detection may be the result of consistent store  320  retrieving data from user device  350  and/or user device  350  sending data of its current database topology to consistent store  320 . Consistent store  320  may be distributed such that one or more nodes store the same or complementary data relating to the topology of database cluster  330 . This may prevent data loss in the event of node failure. The nodes of consistent store  320  may all be configured to read and write, or these tasks may be distributed among the plurality of nodes. Compared to conventional databases, separating the read and write functionalities into dedicated nodes allows each functionality to take place without being intermingled with the other, thus lowering the risk of write or read errors. 
     Database cluster  330 , in some embodiments, may be a computerized system configured to collect, organize, and store various data. Database cluster  330  may be a relational database where data stored therein is organized in one or more data sets. Database cluster  330  may include data such as that stored in or accessed by SAT system  101 , external front end system  103 , internal front end system  105 , transportation system  107 , SOT system  111 , FO system  113 , SCM system  117 , warehouse management system  119 , 3rd party fulfillment systems  121 A,  121 B, and  121 C, FC Auth  123 , and/or LMS  125 . 
     Database cluster  330  may include a source node  331  and one or more replica nodes  332   a  and  332   b . Source node  331  may be configured to process write requests sent by user device  350 , while replica nodes  332   a  and  332   b  may be configured to process read requests sent by user device  350 . Contrary to conventional nodes that are configured to both accept new data for storage and make the data available for client devices (e.g., user device  350 ), source node  331  may be configured solely to collect and maintain the latest data set by accepting new data from user device  350 . Each replica node  332   a / 332   b  may further be configured to store data identical to those stored in source node  331 . For example, if source node  331  includes data sets 1-10 (i.e., a master set), each replica node  332  may be configured to replicate and store data sets 1-10. As discussed above, separating the read and write functionalities into dedicated nodes lowers the risk of write or read errors. Each replica node  332  has the ability to be promoted to a source node should source node  331  fail and orchestrator  310  trigger a failover. 
     Health checker  340 , in some embodiments, may be any computerized system configured to ensure the topology of database cluster  330  matches the topology of database cluster  330  stored in consistent store  320  and to check the health of source node  331  and replica nodes  332   a / 332   b . For example, health checker  340  may monitor consistent store  320  and database cluster  330  in a specific time interval to ensure that both the topology of database cluster  330  and the labeling in consistent store  320  matches. If health checker  340  determines that these data do not match—this may occur, for example, if there is a network error between orchestrator  310  switching the role of one of replica nodes  332   a  or  332   b  in database cluster  330  and updating consistent store  320 —health checker  340  may update consistent store  320  itself, without going through orchestrator  310 , to reflect the current topology of database cluster  330 . Health checker  340  increases the resiliency of a system which is expected to be available continuously as it reduces the possibility of a rare error (e.g., network failure) impacting the performance of the system. 
     User device  350 , in some embodiments, may be any computerized system configured to allow a user to read and/or write data in database cluster  330 . User device  350  may be one or more of mobile device  102 A, computer  1026 , mobile devices  107 A,  107 B, and  107 C, external front end system  103 , internal front end system  105 , mobile devices  119 A,  119 B, and  119 C, or any other system depicted in  FIG.  1 A . 
     In some embodiments, user device  350  may be configured to receive notifications from consistent store  320 , automatically update source and replica endpoints based on the notification, and replace the connections to consistent store  320  using the updated endpoints. In other embodiments, the update of the source and replica endpoints may take place only following user input. In yet other embodiments, user device  350  may be configured to send a confirmation receipt to consistent store  320  once user device  350  has updated its log of the topology of database cluster  330  following a notification from consistent store  320 . User device  350  may be a personal computing device including, but not limited to, a smartphone, a laptop or notebook computer, a tablet, a multifunctional watch, a pair of multifunctional glasses, any mobile or wearable device with computing ability, or any combination of these computers and/or affiliated components. 
       FIG.  4 A  is a flowchart of an exemplary computerized method  400  for replacing source node  331  with a replica node following a failure of source node  331 . Method  400  may be performed in 1-10 seconds, a substantial improvement from previous solutions. Method  400  may be implemented utilizing data stored in any server that must service a large number of queries such as, for example, SAT system  101 , external front end system  103 , internal front end system  105 , transportation system  107 , SOT system  111 , FO system  113 , SCM system  117 , warehouse management system 119, 3rd party fulfillment systems  121 A,  121 B, and  121 C, FC Auth  123 , and/or LMS  125 . Such server may comprise networked systems such as those described above in  FIG.  3   . Method  400  is described below with reference to the networked systems of  FIG.  3   , but any other configuration of systems, subsystems, or modules may be used to perform method  400 . 
     At step  410 , orchestrator  310  and/or health checker  340  may check the availability of source node  331 . Checking the availability of source node  331  and/or one or more replica nodes  332   a  and  332   b  may be accomplished by a detecting a number of failure scenarios, such as a failed source node, a failed source node and failed replica nodes, a failed source node and some failed replica nodes, an unreachable source node, an unreachable source node with lagging replica nodes, not all replica nodes are replicating the source node data, not all replica nodes are replicating the source node data or have failed, a failed co-source node (should the system have more than one source node), a failed co-source node and failed replica nodes, a failed replica node which itself has replicas, a failed replica node which itself has one replica which is failing to connect, a failed replica node which itself has one replica, a failed replica node which itself has one or more replicas which have failed, a failed replica node which itself has one or more replicas—some of which have failed, all replica nodes which themselves have one or more replicas have failed or are unable to connect, an unreachable replica node which itself has one or more replicas is unreachable, an unreachable replica node which itself has one or more replicas which are lagging is unreachable. 
     The failure scenarios may be detected by attempting to reach and/or access source node  331  and/or one or more replica nodes  332   a  and  332   b , determining one or more replica nodes is failing replication, determining source node  331  and/or one or more replica nodes  332   a  and  332   b  are lagging, and other methods for detecting failure scenarios. 
     In other embodiments, orchestrator  310  and/or health checker  340  may use synthetic monitoring to simulate an action or path that a user using user device  350  may take on each node in database cluster  330  to check the availability of source node  321  and/or one or more replica nodes. The actions or paths may then be continuously monitored at predetermined intervals to test the availability of each node. Should the actions or paths be completed successfully, orchestrator  310  and/or health checker  340  may determine that the node is available. Further, depending on the scale and the desired availability of the system, the predetermined intervals could range anywhere from milliseconds to hours. Other methods for checking the availability of the nodes include attempting to open a connection to the nodes, executing a read query against the nodes, executing a non-cached write query against the nodes, executing a prewritten function or procedure that checks for the availability of the nodes, and/or any other method for checking the availability of a database. 
     At step  420 , orchestrator  310  and/or health checker  340  may determine whether source node  331  is available from the data collected at step  410 . Should source node  331  be available, method  400  may proceed to step  422 , where orchestrator  310  and/or health checker  340  may update a last seen time in consistent store  320  and wait for a specific interval of time before checking the availability of source node  331  once again. 
     However, if source node  331  is not available, method  400  may proceed to step  430 , where orchestrator  310  may select a most-updated replica node from the one or more replica nodes  332 . If health checker  340  determined that source node  331  is not available, health checker  340  may notify orchestrator  310  that source node  331  is not available, also triggering step  430 . The most-updated replica node may be, as its name would suggest, the last replica node  332   a  or  332   b  to have been updated with the data from source node  331  before it failed. Orchestrator  310  may store an instance or list identifying the most-updated replica node and/or may pull data relating to the most-updated replica node from SAT system  101 , external front end system  103 , internal front end system  105 , transportation system  107 , SOT system  111 , FO system  113 , SCM system  117 , warehouse management system  119 , 3rd party fulfillment systems  121 A,  121 B, and  121 C, FC Auth  123 , and/or LMS  125 . 
     At step  440 , orchestrator  310  may check to see whether it has selected a replica node  332  before continuing to ensure the failover process is carried out correctly. Should orchestrator  310  determine that no replica node  332  has been selected, method  400  may proceed to step  442 , where orchestrator  310  may alert a system administrator (e.g., by sending a text message, email message, push notification, or other message/notification), exit method  400 , and potentially begin method  400  again at step  410  or step  430 . 
     Alternatively, orchestrator  310  may determine that a replica node  332  has indeed been selected and method  400  may proceed to step  450 . For the purpose of this illustration, we may assume that the most-updated replica node in this case was  332   a . At step  450 , orchestrator  310  may switch the role of replica node  332   a  from “replica” to “source,” also known as source or master promotion, converting replica node  332   a  into promoted source node  332   a . This may take place by executing one or more “set” commands in SQL or a similar function in whichever language is being utilized. For example, orchestrator  310  may use a “set” command to set replica node  322   a  as “writable.” Additionally or alternatively, orchestrator  310  may remove the role of source node  331  by using a “set” command to set source node  331  to be “read-only” or “super-read-only,” converting source node  331  into demoted source node  331 . 
     At step  460 , orchestrator  310  may update the labels in consistent store  320  to reflect the updated topology of database cluster  330 . For example, orchestrator  310  may modify the labels in consistent store  320  as follows: label demoted source node  331  as “not available,” label promoted source node  332   a  (i.e., previously replica node  332   a ) as “source,” and label replica node  332   b  as “replica.” Orchestrator  310  may also update the last seen time in consistent store  320  at this time. In some embodiments, orchestrator  310  may update the domain name system (DNS) of promoted source node  332   a  and record this in consistent store  320  to let user device  350  know that the Internet protocol (IP) of the source node it may connect to has changed. 
     At step  470 , consistent store  320  may send a notification to user device  350  to update its log of the topology of database cluster  330  based on the update received from orchestrator  310 . Consistent store  320  may determine whether user device  350  has updated its log of the database cluster  330  topology based on the most recent update. If the determination shows that user device  350  has not yet updated its log of the database cluster  330  topology after a specific time interval, consistent store  320  may send another notification instructing user device  350  once again to update its log of the database cluster  330  topology. Before, during, or after receiving the confirmation from user device  350 , method  400  may proceed to step  480 , where orchestrator  310  may terminate the connection between user device  350  and demoted source node  331  and restart the connection between user device  350  and promoted source node  332   a  by executing a “set” command and a “start” command, respectively, in SQL or the like. Orchestrator  310  may also terminate the connections by, for example, forcing demoted source node  331  offline, creating a dynamic KILL statement for each connection, and/or altering demoted source node  331  to having a single or restricted user. An additional and/or alternative method for updating the log of the topology on user device  350  is explained in more detail below with reference to  FIG.  5   . 
     Similarly,  FIG.  4 B  is a flowchart of an exemplary computerized method  405  for replacing replica node  332   a  with another replica node following a failure of replica node  332   a . Method  405  may be performed in 1-10 seconds, a substantial improvement from previous solutions. Method  405  may be implemented utilizing data stored in any server that must service a large number of queries such as, for example, SAT system  101 , external front end system  103 , internal front end system  105 , transportation system  107 , SOT system  111 , FO system  113 , SCM system  117 , warehouse management system  119 , 3rd party fulfillment systems  121 A,  121 B, and  121 C, FC Auth  123 , and/or LMS  125 . Such server may comprise networked systems such as those described above in  FIG.  3   . Method  405  is described below with reference to the networked systems of  FIG.  3   , but any other configuration of systems, subsystems, or modules may be used to perform method  405 . 
     At step  415 , orchestrator  310  and/or health checker  340  may check the availability of replica node  332   a . Checking the availability of source node  331  and/or one or more replica nodes  332   a  and  332   b  may be accomplished by a detecting a number of failure scenarios, such as a failed source node, a failed source node and failed replica nodes, a failed source node and some failed replica nodes, an unreachable source node, an unreachable source node with lagging replica nodes, not all replica nodes are replicating the source node data, not all replica nodes are replicating the source node data or have failed, a failed co-source node (should the system have more than one source node), a failed co-source node and failed replica nodes, a failed replica node which itself has replicas, a failed replica node which itself has one replica which is failing to connect, a failed replica node which itself has one replica, a failed replica node which itself has one or more replicas which have failed, a failed replica node which itself has one or more replicas—some of which have failed, all replica nodes which themselves have one or more replicas have failed or are unable to connect, an unreachable replica node which itself has one or more replicas is unreachable, an unreachable replica node which itself has one or more replicas which are lagging is unreachable. 
     The failure scenarios may be detected by attempting to reach and/or access source node  331  and/or one or more replica nodes  332   a  and  332   b , determining one or more replica nodes is failing replication, determining source node  331  and/or one or more replica nodes  332   a  and  332   b  are lagging, and other methods for detecting failure scenarios. 
     In other embodiments, orchestrator  310  and/or health checker  340  may use synthetic monitoring to simulate an action or path that a user using user device  350  may take on each node in database cluster  330  to check the availability of source node  321  and/or one or more replica nodes. The actions or paths may then be continuously monitored at predetermined intervals to test the availability of each node. Should the actions or paths be completed successfully, orchestrator  310  and/or health checker  340  may determine that the node is available. Further, depending on the scale and the desired availability of the system, the predetermined intervals could range anywhere from milliseconds to hours. Other methods for checking the availability of the nodes include attempting to open a connection to the nodes, executing a read query against the nodes, executing a non-cached write query against the nodes, executing a prewritten function or procedure that checks for the availability of the nodes, and/or any other method for checking the availability of a database. 
     At step  425 , orchestrator  310  and/or health checker  340  may determine whether replica node  332   a  is available from the data collected at step  415 . Should replica node  332   a  be available, method  405  may proceed to step  427 , where orchestrator  310  and/or health checker  340  may update a last seen time in consistent store  320  and wait for a specific interval of time before checking the availability of replica node  332   a  once again. 
     However, if replica node  332   a  is not available, method  405  may proceed to step  435 , where orchestrator  310  may select a most-updated replica node from the one or more replica nodes  332 , excluding replica node  332   a . If health checker  340  determined that replica node  332   a  is not available, health checker  340  may notify orchestrator  310  that replica node  332   a  is not available, also triggering step  435 . The most-updated replica node may be, as its name would suggest, the last replica node  332  to have been updated with the data from source node  331  before or after replica node  332   a  failed. Orchestrator  310  may store an instance or list identifying the most-updated replica node and/or may pull data relating to the most-updated replica node from SAT system  101 , external front end system  103 , internal front end system  105 , transportation system  107 , SOT system  111 , FO system  113 , SCM system  117 , warehouse management system  119 , 3rd party fulfillment systems  121 A,  121 B, and  121 C, FC Auth  123 , and/or LMS  125 . 
     At step  445 , orchestrator  310  may check to see whether it has selected a replica node  332  before continuing to ensure the failover process is carried out correctly. Should orchestrator  310  determine that no replica node  332  has been selected, method  405  may proceed to step  447 , where orchestrator  310  may alert a system administrator (e.g., by sending a text message, email message, push notification, or other message/notification), exit method  405 , and potentially begin method  405  again at step  415  or step  435 . 
     Alternatively, orchestrator  310  may determine that a replica node  332  has indeed been selected and method  405  may proceed to step  455 . For the purpose of this illustration, we may assume that the most-updated replica node in this case was  332   b . At step  455 , orchestrator  310  may update the labels in consistent store  320  to reflect the updated topology of database cluster  330 . For example, orchestrator  310  may modify the labels in consistent store  320  as follows: label replica node  332   a  as “not available,” label source node  331  as “source,” and label replica node  332   b  as “replica.” Orchestrator  310  may also update the last seen time in consistent store  320  at this time. In some embodiments, orchestrator  310  may update the domain name system (DNS) of replica node  332   b  and record this in consistent store  320  to let user device  350  know that the Internet protocol (IP) of the replica node it may connect to has changed. 
     At step  465 , consistent store  320  may send a notification to user device  350  to update its log of the topology of database cluster  330  based on the update received from orchestrator  310 . Consistent store  320  may determine whether user device  350  has updated its log of the database cluster  330  topology based on the most recent update. If the determination shows that user device  350  has not yet updated its log of the database cluster  330  topology after a specific time interval, consistent store  320  may send another notification instructing user device  350  once again to update its log of the database cluster  330  topology. 
     Before, during, or after receiving the confirmation from user device  350 , method  405  may proceed to step  475 , where orchestrator  310  may terminate the connection between user device  350  and replica node  332   a  and start a new connection between user device  350  and replica node  332   b  by executing a “set” command and a “start” command, respectively, in SQL or the like. Orchestrator  310  may also terminate the connections by, for example, forcing source node  331  offline, creating a dynamic KILL statement for each connection, and/or altering source node  331  to having a single or restricted user. This step may ensure that user device  350  remains connected to a node which serves read commands. 
       FIG.  5    is a flowchart of an exemplary computerized method  500  for replacing a connection from user device  350  to database cluster  330  after a change in the topology of database cluster  330 . Method  500  may be implemented utilizing data stored in any server that must service a large number of queries such as, for example, SAT system  101 , external front end system  103 , internal front end system  105 , transportation system  107 , SOT system  111 , FO system  113 , SCM system  117 , warehouse management system  119 , 3rd party fulfillment systems  121 A,  121 B, and  121 C, FC Auth  123 , and/or LMS  125 . Such server may comprise networked systems such as those described above in  FIG.  3   . Method  500  is described below with reference to the networked systems of  FIG.  3   , but any other configuration of systems, subsystems, or modules may be used to perform method  500 . 
     At step  510 , user device  350  may monitor consistent store  320  looking for any updates which may show a change in the topology of database cluster  330 . If, at step  520 , user device  350  determines that there have not been any updates to consistent store  320 , user device  350  may wait for a predetermined time interval and method  500  may return to step  510 . However, if user device  350  determines that consistent store  320  has been updated to reflect a change in the topology of database cluster  330 , method  500  may proceed to step  530 . 
     At step  530 , user device  350  may update the source and replica endpoints identifying which nodes in database cluster  330  serve which role. For example, if consistent store  320  has been updated to label source node  331  as “not available,” replica node  332   a  as a “source” node, and replica node  332   b  as a “replica” node, then user device  350  will modify its endpoint data to identify each node consistently with consistent store  320 . 
     At step  540 , user device  350  may use the updated endpoints to replace the previous connection (e.g., connected to source node  331  to serve write requests and to replica node  332   a  to serve read requests) with a new connection (e.g., connected to replica node  332   a  to serve write requests and to replica node  332   b  to serve read requests). The replacement may take place automatically or following user input. 
     Following step  540 , user device  350  may perform checks to ensure the connection replacement was a success. At step  550 , if the connection to the promoted source node (e.g., replica node  332   a ) was not successful, user device  350  may attempt to connect to the promoted source node (e.g., replica node  332   a ) until the connection is successful. And at step  560 , if the connection to the replica node (e.g., replica node  332   b ) was not successful, user device  350  may connect to the promoted source node (e.g., replica node  332   a ) instead and allow it to serve both write and read requests. At step  570 , user device  350  may notify consistent store  350  of the successful update and supply consistent store  350  with device statistics. 
       FIG.  6    is a flowchart of an exemplary computerized method  600  for ensuring the database topology is consistent with consistent store  320 , and by extension, user device  350 . Method  600  may be implemented utilizing data stored in any server that must service a large number of queries such as, for example, SAT System  101 , SOT system  111 , and/or FO system  113 . Such server may comprise networked systems such as those described above in  FIG.  3   . Method  600  is described below with reference to the networked systems of  FIG.  3   , but any other configuration of systems, subsystems, or modules may be used to perform method  600 . 
     At step  610 , health checker  340  may determine the current topology of database cluster  330  by checking the role of each node in database cluster  330 . 
     At step  620 , health checker  340  may check the topology of database cluster  330  against the labeling in consistent store  320  to determine whether the labeling in consistent store  320  is up-to-date and consistent with the database topology. 
     At step  630 , if the determination is that the labeling and the topology are consistent, health checker  340  may wait for a predetermined time interval and method  600  may return to step  610 . However, if the labeling and the topology are not consistent, i.e., at least one node is incorrectly labeled, method  600  may proceed to step  640 , where health checker  340  may update consistent store  320  to reflect the current topology of database cluster  330 . The aforementioned may happen, for example, if there is an error between orchestrator  310  switching the role of one or more nodes in database cluster  330  and updating consistent store  320  with the new labels. 
     At step  650 , consistent store  320  sends a notification to user device  350  to update its log of the topology of database cluster  330  based on the update received from health checker  340 . Consistent store  320  may determine whether user device  350  has updated its log of the database cluster  330  topology based on the most recent update. If the determination shows that user device  350  has not yet updated its log of the database cluster  330  topology after a specific time interval, consistent store  320  may send another notification instructing user device  350  once again to update its log of the database cluster  330  topology. At the same time, before, or after receiving the confirmation from user device  350 , method  600  may proceed to step  660 , where orchestrator  480  may terminate a connection between user device  350  and a failed node (i.e., a demoted source node  331  or a failed replica node  332   a  or  332   b ) and restart a connection between user device  350  and an appropriate node, as determined by the database topology in consistent store  320 , by executing a “set” command and a “start” command, respectively, in SQL or the like. Orchestrator  310  may also terminate the connection by, for example, forcing source node  331  offline, creating a dynamic KILL statement for each connection, and/or altering source node  331  to having a single or restricted user. 
     While the present disclosure has been shown and described with reference to particular embodiments thereof, it will be understood that the present disclosure can be practiced, without modification, in other environments. The foregoing description has been presented for purposes of illustration. It is not exhaustive and is not limited to the precise forms or embodiments disclosed. Modifications and adaptations will be apparent to those skilled in the art from consideration of the specification and practice of the disclosed embodiments. Additionally, although aspects of the disclosed embodiments are described as being stored in memory, one skilled in the art will appreciate that these aspects can also be stored on other types of computer readable media, such as secondary storage devices, for example, hard disks or CD ROM, or other forms of RAM or ROM, USB media, DVD, Blu-ray, or other optical drive media. 
     Computer programs based on the written description and disclosed methods are within the skill of an experienced developer. Various programs or program modules can be created using any of the techniques known to one skilled in the art or can be designed in connection with existing software. For example, program sections or program modules can be designed in or by means of .Net Framework, .Net Compact Framework (and related languages, such as Visual Basic, C, etc.), Java, C++, Objective-C, HTML, HTML/AJAX combinations, XML, or HTML with included Java applets. 
     Moreover, while illustrative embodiments have been described herein, the scope of any and all embodiments having equivalent elements, modifications, omissions, combinations (e.g., of aspects across various embodiments), adaptations and/or alterations as would be appreciated by those skilled in the art based on the present disclosure. The limitations in the claims are to be interpreted broadly based on the language employed in the claims and not limited to examples described in the present specification or during the prosecution of the application. The examples are to be construed as non-exclusive. Furthermore, the steps of the disclosed methods may be modified in any manner, including by reordering steps and/or inserting or deleting steps. It is intended, therefore, that the specification and examples be considered as illustrative only, with a true scope and spirit being indicated by the following claims and their full scope of equivalents.