VishaalY/solutions-architect-hf-dataset huggingface dataset:
Question: Is the charge that I received on my credit card from AWS?

I received a charge from Amazon that I think might be from AWS. How can I be sure?ResolutionAWS charges are billed on your credit card using the charge description that includes your nine-digit invoice number. You can check the invoice number against the Invoice ID in the Payments  section in the AWS Billing and Cost Management console.Note: You might see "AMAZON WEB SERVICES" or "AMAZON MKTPLACE PMTS AMAZON.COM" on your credit card statement for charges related to AWS offerings.You can view your monthly AWS statements in the AWS Billing and Cost Management console.If you have questions about the charges related to an AWS account, then follow these steps:Open the AWS Support Center.Choose Create case.Select Account and billing support.Enter the required information.Choose Submit.If the charge you see doesn't have your invoice number, but it appears to be from Amazon, then contact Amazon.com.

Related informationWhat do I do if I'm receiving a bill from AWS, but can't find the resources related to the charges?How do I find the AWS account associated with an unknown Amazon Web Services charge?Report suspicious emails
Question: Why am I experiencing high latency issues with Kinesis Data Streams?

My Amazon Kinesis data stream is experiencing high latency while getting data records. Why is this happening and how do I troubleshoot this?Short DescriptionGetRecords.Latency can increase if there is an increase in record count or record size for each GET request. If you tried to restart your application while the producer was ingesting data into the stream, records can accumulate without being consumed. This increase in the record count or amount of data to be fetched increases the value for GetRecords.Latency. Additionally, if an application is unable to catch up with the ingestion rate, the IteratorAge gets increased.Note: Enabling server-side encryption on your Kinesis data stream can also increase your latency.

ResolutionMonitor the Amazon Kinesis Data Streams service with Amazon CloudWatch. Check the CloudWatch metrics such as GetRecords.Latency to verify whether the latency increase is continuous. If the latency increase is continuous, then check if there is also an increase in the IncomingRecords, IncomingBytes, GetRecords.Records, and GetRecords.Bytes metrics in CloudWatch. As data volumes increase, these metrics also increase, causing high latency. This increase occurs because GetRecords fetches more records when there are more records available in the Kinesis data stream.If your IteratorAge also increased, then there are likely more IncomingBytes put into the stream. Check the IncomingBytes metric in CloudWatch to verify whether the number of bytes increased. You can also check whether fewer GetRecords calls were made to the stream. More incoming bytes indicate that each GetRecords call is retrieving more data, which increases the value for GetRecords.Latency.If you still observe high latency (even though there is no increase in IncomingBytes or IncomingRecords), there might be too much incoming data. If the consumer application is unable to catch up with the incoming data, the data continues to accumulate in the Kinesis data stream. Even if you restart the application, more records are fetched within each GetRecords call. The increase in records or fetched data for each GetRecords call then increases the value for GetRecords.Latency.To resolve this issue, try the following troubleshooting tips:Check your application to see if enough GetRecords calls are being made to process the volume of incoming data. If you are using the Amazon Kinesis Client Library (KCL) application or AWS Lambda as a consumer, increase the number of shards in your stream. An increase in shard count increases the consumption rate from the delivery stream, while decreasing the values for the IteratorAge and GetRecords.Latency.Increase the retention period of the Kinesis data stream to avoid any data losses. A longer retention period can help your application to catch up with the data backlog.If you have your own consumer application, check the processing logic and record processing time.Check the central processing unit (CPU) and memory utilization of your system to see if you need to free up more memory.
Question: Why aren't the subnet network ACLs in my VPC allowing traffic through the transit gateway?

I allowed inbound SSH traffic on the network access control list (ACL) for the subnet of my destination Amazon Elastic Compute Cloud (Amazon EC2) instance. However, traffic is still blocked. Why aren't the subnet network ACLs in my virtual private cloud (VPC) allowing traffic through the transit gateway?ResolutionWhen you create a transit gateway attachment and then associate a subnet in your VPC, a transit gateway interface is created in that subnet. The transit gateway interface routes traffic from the Amazon EC2 instance's elastic network interface to the transit gateway. The elastic network interface for the Amazon EC2 instance and the transit gateway might be in the same subnet. However, you must consider them as separate entities when configuring the network ACLs.In the network ACL associated with the transit gateway interface at the destination's VPC, add an inbound rule to allow custom TCP on the ephemeral port. With this rule configured, return traffic on the ephemeral port is allowed.Confirm that traffic is flowing as intended by reviewing the VPC Flow Logs on the transit gateway network interface.Note: To learn more about Flow Logs, see Learn From your VPC Flow Logs with additional meta-data.Network ACL inbound and outbound rules are applied differently based on whether Amazon EC2 and the transit gateway are in the same subnet or different subnets. For more information, see How network ACLs work with transit gateways.

Related informationVPC Flow Logs - Log and view network traffic flows
Question: How can I make a private Amazon Redshift cluster publicly accessible?

I want to update my Amazon Redshift cluster so that it is publicly accessible. How can I do this?ResolutionTo modify a cluster, follow these steps:1.    From the AWS Management Console, navigate to the Amazon Redshift console.2.    On the navigation menu, choose CLUSTERS.3.    Select the cluster that you want to modify.4.    Choose Actions.5.    Choose Modify Publicly accessible setting.6.    Choose Enable.7.    Choose Save changes.Note: An Elastic IP address is required. If you do not choose one, an address will be randomly assigned to you.If you still can't connect to the cluster from the internet or a different network, then check the following settings.Security group1.    Open the Amazon Redshift console.2.    Select the cluster that you want to modify.3.    Under Properties, choose Network and security settings.4.    Choose the link next to VPC security group to open the Amazon Elastic Compute Cloud (Amazon EC2) console.5.    On the Inbound Rules tab, make sure that your IP address and the port of your Amazon Redshift cluster are allowed. The default port for Amazon Redshift is 5439, but your port might be different.Note: Although security groups are stateful, it’s a best practice to verify that the Outbound Rules allow outbound communications. By default, a security group includes an outbound rule that allows all outbound traffic. For more information, see Security group basics.VPC network access control list (network ACL)Unlike security groups, network ACLs are stateless. This means that you must configure both inbound and outbound rules. Make sure that your IP address and the port of your Amazon Redshift cluster are allowed in the inbound rules for the VPC network ACL. In the outbound rules, allow all traffic (port range: 0–65535) to your IP address. For more information, see Adding and deleting rules.VPC route tableVerify route table settings on the Amazon VPC console. To connect to a publicly accessible cluster from the public internet, an internet gateway must be attached to the route table. Confirm that the internet gateway's target is set with source 0.0.0.0/0 or a public IP CIDR. The route table must be associated with the VPC subnet where your cluster resides. For more information, see Turning on internet access.If you don’t want to make the subnet publicly accessible (because of other resources in that subnet), then use a snapshot. You can use a snapshot to restore the cluster into a public subnet.If you still have connection problems, then use network diagnostic tools such as Telnet and tcpdump for additional troubleshooting.

Related informationManaging clusters in a VPCConnecting from outside of Amazon EC2 —firewall timeout issue
Question: How do I troubleshoot a failed or stuck Spark SQL query in Amazon EMR?

I want to collect information to troubleshoot issues with my Spark SQL queries in Amazon EMR.

ResolutionSpark SQL completed queries are located on the Application User Interfaces tab of your EMR cluster's Spark History Server. For more information, see View persistent application user interfaces.To access completed Spark SQL queries, do the following:On the Spark History Server, select SQL/DataFrame to view completed Spark SQL queries.Select the query's Spark SQL job application IDs to open the completed job ID information on the Jobs tab. Note that a SQL query might have more than one job ID.The following information is available from the Jobs tab:On the Jobs tab, you can see the status of the job, the job duration, and the associated SQL query.On the Jobs tab, you can review the application ID's timeline. The timeline displays the addition and removal of the Spark executors in chronological order.Scroll down to see the DAG (Direct Acyclic Graph). The DAG is a visualization of the Spark SQL query. You can also see the chain of RDD dependencies.Scroll further to see the completed stages of the Spark SQL job.Select the stage ID description to see the query's total time across all tasks, a locality level summary, and the associated job ID. The Stages view provides details of all the RDDs that correspond to this stage. This view also provides information about the lower level RDD operation related to the high level Spark SQL operation.Expand Aggregated Metric by Executor to view the Executors log. The Executors log provides additional details about the Spark SQL job. The following is an example log:23/01/17 18:10:17 INFO Executor: Finished task 0.0 in stage 16.0 (TID 16). 1882 bytes result sent to driver23/01/17 18:10:17 INFO YarnCoarseGrainedExecutorBackend: Got assigned task 1723/01/17 18:10:17 INFO Executor: Running task 0.0 in stage 17.0 (TID 17)23/01/17 18:10:17 INFO TorrentBroadcast: Started reading broadcast variable 17 with 1 pieces (estimated total size 4.0 MiB)23/01/17 18:10:17 INFO MemoryStore: Block broadcast_17_piece0 stored as bytes in memory (estimated size 7.2 KiB, free 4.8 GiB)23/01/17 18:10:17 INFO TorrentBroadcast: Reading broadcast variable 17 took 8 ms23/01/17 18:10:17 INFO MemoryStore: Block broadcast_17 stored as values in memory (estimated size 13.8 KiB, free 4.8 GiB)23/01/17 18:10:17 INFO PythonRunner: Times: total = 52, boot = -31, init = 83, finish = 023/01/17 18:10:17 INFO Executor: Finished task 0.0 in stage 17.0 (TID 17). 1883 bytes result sent to driver23/01/17 18:11:20 ERROR CoarseGrainedExecutorBackend: RECEIVED SIGNAL TERM23/01/17 18:11:20 INFO MemoryStore: MemoryStore cleared23/01/17 18:11:20 INFO BlockManager: BlockManager stopped23/01/17 18:11:20 INFO ShutdownHookManager: Shutdown hook calledFor detailed information, see Jobs Tab in the Web UI section of the Apache Spark documentation.

Related informationExamine the log files
Question: How do I view the total storage used for my Amazon Aurora MySQL DB cluster?

I want to see the size of my Amazon Aurora MySQL-Compatible Edition DB cluster volume.

ResolutionAurora MySQL-Compatible cluster volume automatically scales up as the amount of data in your database increases. A database can be scaled up to a maximum of 128 tebibytes (TiB) in Aurora MySQL-Compatible versions 1.23.0 or higher, 2.09.0 or higher, and 3.01.0 or higher. For all previous versions, a database can be scaled up to a maximum of 64 TiB. You can review the storage that is used by the Aurora MySQL-Compatible cluster by using the following the Amazon CloudWatch metrics:AuroraVolumeBytesLeftTotal is the remaining available space for the cluster volume, as measured in bytes. As the data grows in your cluster, the value for AuroraVolumeBytesLeftTotal decreases. This value can help you identify when the cluster is approaching its size limit.Note: The AuroraVolumeBytesLeftTotal metric is available only on Aurora MySQL-Compatible version 1.19.5 or higher, and on Aurora MySQL-Compatible version 2.04.5 or higher.VolumeBytesUsed is the amount of storage used by the Aurora MySQL-Compatible DB cluster in bytes. As the data grows in your cluster, the value for VolumeBytesUsed increases.Important: Dynamically reducing the billed storage on deleting data is possible on certain Aurora MySQL-Compatible versions. For more information, see Aurora storage scaling.View the AuroraVolumeBytesLeftTotal in the CloudWatch consoleOpen the CloudWatch console.Choose Metrics from the navigation pane.In the All metrics tab, choose RDS.Choose DBClusterIdentifier.Enter AuroraVolumeBytesLeftTotal in the search box, and select the metric.For more information, see Viewing available metrics.View the VolumeBytesUsed in the RDS consoleOpen the Amazon Relational Database Service console.Choose the AWS Region where you created the Aurora MySQL-Compatible DB cluster.Choose Databases from the navigation pane, and then choose the name of the DB instance that you want to monitor.Choose the Monitoring tab.From the CloudWatch section, enter [Billed] Volume Bytes Used, or choose it from the list. The storage use appears on the graph.Note: Aurora uses separate local storage for nonpersistent temporary files. This includes database logs and files that are used for sorting large data sets during query processing and building indexes. For more information, see Temporary storage limits for Aurora MySQL and Temporary storage limits for Aurora PostgreSQL. You can monitor local storage available for a specific database instance with the FreeLocalStorage Cloudwatch metric.

Related informationAurora DB clustersMonitoring Aurora metrics with Amazon CloudWatchUpgrading the minor version or patch level of an Aurora MySQL-Compatible DB cluster
Question: How do I trace an Application Load Balancer request using X-Amzn-Trace-Id?

How do I log X-Amzn-Trace-Id to trace requests through my Application Load Balancer and web servers?Short descriptionIn Elastic Load Balancing (ELB), when an Application Load Balancer handles a request, the trace information is added to the X-Amzn-Trace-Id header. For example:X-Amzn-Trace-Id: Root=1-67891233-abcdef012345678912345678Log the identifier and then use it to troubleshoot issues with your load balancer. For example, use the X-Amzn-Trace-Id header to identify when many similar requests are received from the same client within a short time. If you have many layers in your stack, then you can also use the X-Amzn-Trace-Id header to track a request across all the layers.

ResolutionUse the following steps for common web server configurations (Apache, Tomcat, NGINX, or IIS) to log the X-Amzn-Trace-Id header:Apache1.    Open the Apache configuration file (/etc/httpd/conf/httpd.conf in Amazon Linux) in your preferred text editor.2.    In the LogFormat section, add the option  %{X-Amzn-Trace-Id}i as follows:LogFormat "%{X-Forwarded-For}i %h %l %u %t \"%r\" %>s %b %D \"%{Referer}i\" \"%{User-Agent}i\" \"%{X-Amzn-Trace-Id}i\"" combined3.    Restart the Apache service to apply your changes as follows:sudo service apache restartTomcat1.    Open the Tomcat configuration file (/etc/tomcat7/server.xml in Amazon Linux) in your preferred text editor.    2.    In the org.apache.catalina.valves.AccessLogValve class, add the option %{X-Amzn-Trace-Id}i as follows:<Valve className="org.apache.catalina.valves.AccessLogValve" directory="logs"      prefix="localhost_access_log." suffix=".txt"      pattern="%h %l %u %t &quot;%r&quot; %s %b %{X-Amzn-Trace-Id}i" />3.    Restart the Tomcat service to apply your changes as follows:sudo service tomcat7 restartNGINX1.    Open the NGINX configuration file ( /etc/nginx/nginx.conf in Amazon Linux) in your preferred text editor.2.    In the log_format section, add the option $http_x_amzn_trace_id as follows:log_format  main  '"$http_x_forwarded_for" $remote_addr - $remote_user [$time_local] "$request" '    '$status $body_bytes_sent "$http_referer" '    '"$http_user_agent" "$http_x_amzn_trace_id"';3.    Restart the NGINX service to apply your changes as follows:sudo service nginx restartInternet Information Services (IIS)1.    Open the IIS Manager.2.    Select your server’s name.3.    Choose Logging.4.    Choose Select Fields.5.    Choose Add Field.6.    In the dialog box, for Field Name, enter X-Amzn-Trace-Id. For Source Type, enter Request Header. For Source, enter X-Amzn-Trace-Id.7.    Choose Apply to apply your changes.

Related informationRequest tracing for your Application Load BalancerAccess logs for your Application Load Balancer
Question: How do I configure a Data Pipeline precondition for Amazon S3?

I want to use an AWS Data Pipeline precondition to stop a running pipeline when a specific Amazon Simple Storage Service (Amazon S3) bucket doesn't exist.

Short descriptionCreate an S3PrefixNotEmpty precondition for the S3DataNode object. S3PrefixNotEmpty is a system-managed precondition. Unless you specify a timeout (preconditionTimeout), system-managed preconditions run until their condition is true.Note: On active pipelines, preconditions incur additional charges. For more information, see AWS Data Pipeline pricing.

ResolutionYou can't configure preconditions while a pipeline is active. To add a precondition to an active pipeline, clone the pipeline and then complete the following steps:Open the AWS Data Pipeline console.Select a deactivated pipeline, and then choose Actions, Edit.Choose an existing S3DataNode object. Or, create a new one by choosing the Add dropdown list, and then choosing S3DataNode.In the Add optional field dropdown list for the S3DataNode object, choose Precondition.In the Precondition dropdown list, choose Create new: Precondition.Open the Precondition section, and then find the precondition object that you just created.In the Type dropdown list, choose S3PrefixNotEmpty.In the S3 Prefix field, enter an Amazon S3 path. For an example of how this looks in the pipeline definition JSON, see S3PrefixNotEmpty.To specify a timeout, do the following:In the Add optional field dropdown list for the S3PrefixNotEmpty object, choose Precondition Timeout.Specify the timeout conditions.When preconditionTimeout is met, the dependent nodes fail with the status CASCADE_FAILED.
Question: How can agents in my Amazon Connect contact center transfer contacts directly to another agent who isn't available?

I want agents in my Amazon Connect contact center to have the option to directly transfer customers to another agent who isn't currently available. How do I set up contact transfers to do that?Short descriptionTo allow agents in your Amazon Connect contact center to transfer contacts to another agent who isn't available, do the following:1.    Create a Transfer to agent contact flow.2.    Create an Agent quick connect that allows agents to transfer contacts to other agents.For more information, see Set up agent-to-agent transfers.Note: By default, each agent in your Amazon Connect contact center has their own agent queue. If an agent is unavailable, a contact can still be transferred to that agent's queue. For more information, see Transfer contacts to a specific agent.

ResolutionCreate a Transfer to agent contact flow1.    Log in to your Amazon Connect instance using your access URL (https://alias.awsapps.com/connect/login -or- https://domain.my.connect.aws).Important: You must log in as a user that has sufficient permissions in their security profile.2.    Follow the instructions in Set up the "Transfer to agent" contact flow.Note: It's a best practice to include Check hours of operation and Check staffing contact blocks before transferring a contact to an agent. These contact blocks verify that the incoming contact is within working hours and that agents are staffed to service the contact. For more information, see Best practices for Amazon Connect.Create an Agent quick connect that allows agents to transfer contacts to another agent1.    Create an Agent quick connect by following the instructions in Create the quick connect.2.    Add the quick connect to your agents' queues by following the instructions in Allow agents to see quick connects.3.    Confirm that the queues that include your quick connect are in a routing profile assigned to the agents who will use the quick connect. For more information, see Set up routing.For more information, see How do I allow agents in my Amazon Connect contact center to transfer contacts using the CCP?To test the setup1.    Log in to the Amazon Connect Contact Control Panel (CCP) as an agent in your contact center.Note: Make sure that you log in as an agent who can see the quick connect that you created.2.    Place an outbound call as a test.3.    Transfer the call using the quick connect.The contact is routed to the receiving agent's queue, and the first prompt plays. When the receiving agent becomes available, the call is routed to the agent.

Related informationHow routing worksProvide access to the contact control panelAdd custom agent statusHow do I change or remove the default message played when transferring a call to a queue in Amazon Connect?