VishaalY/solutions-architect-hf-dataset huggingface dataset:
Question: How do I assign a static private IP address to the master node of my Amazon EMR cluster?

I want to create a static private IP address and associate it with the master node of an Amazon EMR cluster using a bootstrap action.

ResolutionConfirm that your AWS Identity and Access Management (IAM) policy allows permissions for EMR_EC2_DefaultRole and ec2:AssignPrivateIpAddresses.Sign in to GitHub.Download the assign_private_ip.py script from AWS Labs.Save the script in an Amazon Simple Storage Service (Amazon S3) bucket.Specify the script as a custom bootstrap action while launching an Amazon EMR cluster. You can also run the script as an Amazon EMR step. The script requires an argument, which is a private IP address from the CIDR range of your subnet. The script attaches that private IP address to the network interface (eth0) of the master node. The script also configures the network settings to redirect all traffic from the secondary IP address to the primary IP address.To find the new IP address, open the Amazon Elastic Compute Cloud (Amazon EC2) console. Then, select the EC2 instance that's acting as the master node of the EMR cluster. The new IP address appears on the Description tab, in the Secondary private IPs field.

Related informationHow do I determine whether to use a bootstrap action or a step in my Amazon EMR cluster?
Question: How do I perform an in-place upgrade for my EC2 Windows instance?

I want to upgrade my operating system files while keeping my existing configuration and data intact. How can I perform an in-place OS upgrade for my Amazon Elastic Compute Cloud (Amazon EC2) instance?Short descriptionThere are two methods for performing an in-place upgrade:Manual in-place upgrade.Automated in-place upgrade using the AWS Systems Manager Service.To minimize downtime, plan your upgrade before you start the upgrade. It's a best practice to maintain backups of your instances and data. Before you upgrade, consider  creating an AMI or  creating snapshots of your Amazon EBS volumes.Note: An in-place upgrade can be faster, but software incompatibilities might produce errors.

ResolutionManual in-place upgrade1.    Review and understand the upgrade options, requirements, and prerequisites to confirm that you're ready to upgrade your current version of Windows. Make sure that you're running the latest version of AWS drivers on the EC2 Windows instance that you're upgrading.2.    Based on the network drivers running on your EC2 instance, choose the in-place upgrade steps:Upgrade an instance in-place with AWS PV, Intel Network Adapter, or the Enhanced Networking driversUpgrade an instance in-place with Citrix PV driversNote: To verify which driver your Windows instance uses, select Control Panel, Network Connections and then view Local Area Connection.Alternatively, you can check the output from the pnputil -e command to determine the driver type.3.    Perform required post upgrade tasks.Important Note:During the Windows in-place upgrade process, Windows Server Setup copies and processes files. Several minutes after you trigger the in-place upgrade setup, your Remote Desktop session closes. The length of time to upgrade depends on the number of applications and server roles running on your Windows Server instance. Instance status check 1 of 2 fails until the upgrade process completes.If you have problems upgrading, or the instance continues to fail status checks several hours after initiating the upgrade process, see Troubleshoot an upgrade.Automated in-place upgradeAutomated in-place upgrading using AWS Systems Manager Automation documents is available for Windows Server 2008 R2, Windows Server 2012 R2, Windows Server 2016, and SQL Server 2008 R2 with Service Pack 3.For more information, see Perform an automated upgrade.

Related informationUpgrade an Amazon EC2 Windows instance to a newer version of Windows ServerHow can I upgrade my EC2 Windows Server instance OS to a newer version?Upgrade and migrate roles and features in Windows Server
Question: How do I allow the IP address for my API Gateway API to access my integration firewall?

I want to allow an Amazon API Gateway IP address or address range to access the internet through my firewall.

Short descriptionUse an AWS Lambda function or Amazon Elastic Compute Cloud (Amazon EC2) instance to allow your IP address to access the internet through your firewall.Complete the steps in the Set up Lambda proxy integration in API Gateway section if:You require less control over your servers.You don't want to allow your proxy to bypass API Gateway and be invoked externally.You require exponential scalability.You don't want to manually manage runtimes and apply security patches.Complete the steps in the Set up EC2 proxy integration in API Gateway section if:You must have more control over your servers.You want to allow your proxy to bypass API Gateway and be invoked externally.You must overcome the memory, timeout, and payload quotas of Lambda.

ResolutionSet up Lambda proxy integration in API GatewayUse a Lambda function to set up a proxy between API Gateway and your API Gateway integration.Assign a static IP address to your Lambda function.Build the Lambda proxy integration in API Gateway.Allow the static IP address of the NAT Gateway on the integration firewall.Set up EC2 proxy integration in API GatewayYou must use an EC2 instance to set up a proxy integration between API Gateway and your API Gateway integration.Allocate an Elastic IP address.Associate your Elastic IP address with an instance or network interface.Build an HTTP proxy integration in your API Gateway integration.Important: For Endpoint URL, enter http://YOUR_ELASTIC_IP_ADDRESS/{proxy}. This option allows the request from API Gateway to be proxied to the EC2 instance and then to your integration.Allow your Elastic IP address on the integration firewall.
Question: How do I cache content in CloudFront based on HTTP headers?

I want to cache content in Amazon CloudFront based on HTTP headers. How can I do this?Short descriptionTo configure your distribution to cache content based on HTTP headers, do one of the following:Create a cache policy and attach it to a behavior in the distributionEdit the settings of an existing legacy cache behavior in the distributionIt's a best practice to create a new cache policy to cache content. You can customize your configuration more with a new cache policy instead of editing a legacy distribution.Important: You can’t configure CloudFront to cache based on request header value for header types Connection, Host (for Amazon S3 origins), Proxy-Authorization, TE, or Upgrade. For more information, see Selecting the headers to base caching on.

ResolutionCreate a cache policyCreate a cache policy using the CloudFront console.Under TTL settings, enter the values for Minimum TTL, Maximum TTL, and Default TTL to manage the amount of time that CloudFront caches objects. By default, the cached files will automatically expire after 24 hours.Under Cache key settings, for Headers, choose Include the following headers.From the Add header dropdown list, select your headers, or select Add custom to add a custom header.Complete all other settings of the cache policy based on the requirements of the behavior that you're attaching the policy to. Then, choose Create.After you create the cache policy, follow the steps to attach the policies to the relevant behavior of your CloudFront distribution.Editing the settings of an existing behaviorOpen CloudFront console, and then choose your distribution.Choose the Behaviors tab. Then, choose the path that you want to cache the content based on selected HTTP headers.Choose Edit.Under Cache key and origin requests, confirm that Legacy cache settings is selected.If Legacy cache settings isn't selected, follow the steps in the previous section to create a cache policy.-or-If Legacy cache settings is selected, do the following:For Headers, select Include the following headers.From the Add header dropdown list, select the headers that you want to cache.To manage the cache duration for the CloudFront cache, under Object Caching, choose Customize. Then specify values in the Minimum TTL, Default TTL, and Maximum TTL fields. For more information, see Object caching.Choose Save Changes.Note: To change the cache duration for an individual file, configure your origin to add a Cache-Control max-age directive, Cache-Control s-maxage directive, or Expires header. For more information, see Using headers to control cache duration for individual objects.For Amazon Simple Storage Service (Amazon S3) origins, add metadata for header values to manage the cache expiration of individual objects. For more information, see Adding headers to your objects using the Amazon S3 console.

Related informationWorking with policiesCaching content based on request headersManaging how long content stays in the cache (expiration)
Question: How do I monitor my Lambda function's memory usage?

I want to monitor the memory usage of my AWS Lambda functions. How do I do that?ResolutionYou can use the following AWS services and tools to monitor your Lambda functions' memory usage. For more information on monitoring function metrics, see Monitoring and observability in the Lambda operator guide.Note: To optimize your Lambda function's memory usage, see Profiling functions with AWS Lambda Power Tuning.Amazon CloudWatch Logs InsightsCloudWatch Logs Insights allows you to search and analyze log data for memory usage metrics using a specialized query syntax. For more information and example tutorials, see Analyzing log data with CloudWatch Logs Insights.For an example query that determines the amount of overprovisioned memory, see the Queries for Lambda logs section of Sample queries.Note: Running CloudWatch Logs Insights queries incurs charges to your AWS account. For more information, see Amazon CloudWatch pricing.CloudWatch Lambda InsightsCloudWatch Lambda Insights automatically collects memory usage metrics from the Lambda functions where it's installed. For more information and example tutorials, see Using Lambda Insights.For an example workflow to track and analyze memory usage, see Example workflow to detect function anomalies in the Lambda Developer Guide.For an example log event, see the Example telemetry event in the Using Lambda Insights section of the CloudWatch User Guide.Note: Installing the CloudWatch Lambda extension that's required for CloudWatch Lambda Insights incurs charges to your AWS account. For more information, see the Pricing section of Using Lambda Insights.Amazon CodeGuru Profiler (compatible with Python and Java)The Amazon CodeGuru Profiler integration for AWS Lambda collects performance data on your applications. It's compatible with applications written in Java, Python 3.6 through 3.9, and JVM languages such as Scala and Kotlin.By profiling your applications, you can monitor their metrics and receive recommendations to make them more efficient. For more information on Amazon CodeGuru Profiler, see Profiling your applications that run on AWS Lambda.

Related informationOperating Lambda: Using CloudWatch Logs InsightsUnderstanding AWS Lambda behavior using Amazon CloudWatch Logs Insights
Question: Can I push server access logs about an Amazon S3 bucket into the same bucket?

I turned on server access logging for my Amazon Simple Storage Service (Amazon S3) bucket. I want to send the logs to the same bucket.

ResolutionIt's not a best practice to push server access logs about a bucket into the same bucket. If you configured your server access logs this way, then there would be an infinite loop of logs. This is because when you write a log file to a bucket, the bucket is also accessed, which then generates another log. A log file would be generated for every log written to the bucket, which creates a loop. This would create many logs and increase your storage costs.
Question: Why do I receive a "No Invocations to Execute" message from my Systems Manager maintenance window?

I created a maintenance window that runs an AWS Systems Manager Automation targeting Amazon Elastic Compute Cloud (Amazon EC2) instance tags. When the automation runs, I receive a "No Invocations to Execute" message.

Short descriptionWhen you run a maintenance window that targets instances that use Amazon EC2 instance tags, the instance IDs for managed instances resolve when the Automation runs. The instance ID won't resolve as a target if either of the following is true:The target instance isn't reporting as a managed instance when the Automation runsThe target instance is stopped when the maintenance window runsWhen an instance ID can't resolve as a target, then the "No Invocations to Execute" message appears in the output.

ResolutionTo target a non-managed instance or an instance that is stopped when the maintenance window runs, follow these steps:Create a new resource group that is limited to Amazon EC2 instances, and then specify your tags. For more information and for instructions to create a tag-based group, see Creating query-based groups in AWS Resource Groups.Update the AWS Identity and Access Management (IAM) policies attached to the Automation role to include read-only access for the resource group.Register the target to a maintenance window. For Targets, choose the tag-based resource group that you created in step 1 of this article.Update the maintenance window Automation task to target the resource group target that you created in the previous step.For the Automation task InstanceId input parameter, enter the pseudo parameter {{RESOURCE_ID}}.

Related informationWhy is my EC2 instance not displaying as a managed node or showing a "Connection lost" status in Systems Manager?AWS Resource Groups identity-based policy examplesWhy do I receive a "No Instances in Tag" message from my Systems Manager maintenance window?
Question: "When other AWS accounts upload objects to my Amazon S3 bucket, how can I require that they grant me full control of the objects?"

I want users from other AWS accounts to be able to upload objects to my Amazon Simple Storage Service (Amazon S3) bucket. However, I want to require that users grant me full control of those objects. How can I do that?ResolutionAdd a bucket policy that requires users to include the bucket-owner-full-control access control list (ACL) when they upload objects to your bucket.For example, this bucket policy specifies that ExampleUser can upload objects to DOC-EXAMPLE-BUCKET only when the object's ACL is set to bucket-owner-full-control:{    "Id": "Policy1541018284691",    "Version": "2012-10-17",    "Statement": [        {            "Sid": "Stmt1541018283275",            "Action": [                "s3:PutObject",                "s3:PutObjectAcl"            ],            "Effect": "Allow",            "Resource": "arn:aws:s3:::DOC-EXAMPLE-BUCKET/*",            "Condition": {                "StringEquals": {                    "s3:x-amz-acl": "bucket-owner-full-control"                }            },            "Principal": {                "AWS": [                    "arn:aws:iam::111122223333:user/ExampleUser"                ]            }        }    ]}After you add this bucket policy, users must include the required ACL as part of the upload request, similar to the following:aws s3 cp example.jpg s3://DOC-EXAMPLE-BUCKET --acl bucket-owner-full-controlIf users fail to meet the ACL requirement in their upload request, then they receive the error message "An error occurred (AccessDenied) when calling the PutObject operation: Access Denied".For existing objects in your bucket that are owned by other accounts, the object owner can run a put-object-acl command to grant you full control:aws s3api put-object-acl --bucket DOC-EXAMPLE-BUCKET --key example.jpg --acl bucket-owner-full-controlThe bucket-owner-full-control ACL grants the bucket owner full access to an object uploaded by another account, but this ACL alone doesn't grant ownership of the object. To automatically get ownership of objects uploaded with the bucket-owner-full-control ACL, set S3 Object Ownership to bucket owner preferred. After you update S3 Object Ownership, new objects uploaded with the bucket-owner-full-control ACL are automatically owned by the bucket's account.

Related informationWhy can't I access an object that was uploaded to my Amazon S3 bucket by another AWS account?Granting cross-account permissions to upload objects while ensuring the bucket owner has full controlTutorial: Delegate access across AWS accounts using IAM rolesMapping of ACL permissions and access policy permissions
Question: Why does the MSCK REPAIR TABLE command take a long time to run?

When I run the MSCK REPAIR TABLE command, a long time elapses before the results appear.-or-When I run the MSCK REPAIR TABLE command, the query times out.

ResolutionYou get this error because Amazon Athena recursively lists prefixes and objects in Amazon Simple Storage Service (Amazon S3) when running the MSCK REPAIR TABLE command. If you have too many Amazon S3 prefixes or objects, then the command might take a long time to complete or time out.To resolve this error, do either of the following:Use an AWS Glue Crawler to add partitions to your Athena tables. For more information, see How crawlers work. Using an AWS Glue Crawler can reduce the time taken to load partitions if you have many Amazon S3 prefixes. For more information, see Incremental crawls in AWS Glue.Add partitions to the table using the ALTER TABLE ADD PARTITION command.Consider using partition projection if your partitions follow predictable patterns. Athena generates partitions in-memory without needing to add them to the AWS Glue Data Catalog or retrieve them from the Data Catalog. Therefore, query processing times might reduce for heavily partitioned tables.

Related informationWhy do my Athena queries take a long time to run?Creating tables, updating schema, and adding new partitions in the Data Catalog from AWS Glue ETL jobs
Question: How do I reduce the amount of logs generated by my AWS Glue job?

My AWS Glue job is generating too many logs in Amazon CloudWatch. I want to reduce the number of logs generated.

ResolutionWith AWS Glue-Spark ETL jobs, you can't control the verbosity of the logs generated by the instances that the AWS Glue jobs run on. The logs are verbose so that they can be used to monitor internal failures and help in diagnosing job failures. However, you can define the Spark logging levels by following the steps presented here.Choose the standard filter setting for continuous loggingIf you turned on continuous logging for your job, choose the Standard filter for Log filtering option. This filter can help you prune the non-useful Apache Spark driver/executor and Apache Hadoop YARN heartbeat log messages. To change the log filter setting for your AWS Glue job, do the following:Open the AWS Glue console.In the navigation pane, choose Jobs.Select the job that you want to update.Choose Action, and then choose Edit job.Expand the Monitoring options section.Select Continuous logging.Under Log filtering, select Standard filter.Choose Save.To change this setting from the AWS Command Line Interface (AWS CLI), use the following command:'--enable-continuous-cloudwatch-log': 'true''--enable-continuous-log-filter': 'true'Note: If you receive errors when running AWS CLI commands, make sure that you’re using the most recent version of the AWS CLI.For more information, see Enabling continuous logging for AWS Glue jobs.Important: Even with the standard filter setting, the application master logs for the Spark jobs are still pushed to /aws-glue/jobs/output and /aws-glue/jobs/error log groups.Set the logging level using Spark context method setLogLevelYou can set the logging level for your job using the setLogLevel method of pyspark.context.SparkContext. Valid logging levels include ALL, DEBUG, ERROR, FATAL, INFO, OFF, TRACE, and WARN. For more information, see Spark documentation for setLogLevel.Use the following code to import the Spark context method and set the logging level for your job:from pyspark.context import SparkContextsc = SparkContext()sc.setLogLevel("new-log-level")Note: Be sure to replace new-log-level with the logging level that you want to set for your job.For more information, see Spark documentation for Configuring logging.Use a custom log4j.properties file to define the logging levelSpark uses log4j configurations for logging. You can include the logging preferences in a log4j.properties file, upload the file to Amazon Simple Storage Service (Amazon S3), and use the file in the AWS Glue job.To reference the Amazon S3 file in the job, do the following:Open the AWS Glue console.In the navigation pane, choose Jobs.Select the job where you want to reference the file.Choose Actions, and then choose Edit job.Expand the Security configuration, script libraries, and job parameters (optional) section.For Referenced files path, paste the full S3 path where you stored the log4j.properties file.For more information, see Providing your own custom scripts.

Related informationMonitoring with Amazon CloudWatch
Question: How do I configure my local printer in my Windows WorkSpace?

Setting up a local printer can be challenging in Amazon WorkSpaces. How can I set up or confirm settings for a local printer in a WorkSpace?ResolutionAmazon WorkSpaces printing capabilities depend on the operating system that the WorkSpace client runs on:Windows and macOS clients support local printers and cloud printing services.Other clients support network printing and cloud printing services.Depending on your WorkSpaces protocol or your local printer, you might have only basic printing options available. In your WorkSpace, open Print Management to see the available options. To use device-specific features, you might need to download and install a model-specific printer driver to your WorkSpace.To install a Windows printer driver in your WorkSpace:Download the correct local printer driver. It's a best practice to download printer drivers from the printer manufacturer's official website. You might have to unzip the downloaded file to access the driver file (.inf).Open Printers & scanners.Choose the Add a printer or scanner option and choose The printer I want isn't listed.In the Add Printer dialog box, choose Add a local printer or network printer with manual settings and choose Next.For Use an existing port, select LPT1: (Printer Port). This makes the driver available in dropdown list for later selection.For Install the printer driver, select a manufacturer and a printer, and then choose Have Disk.Choose Browse to navigate to the location of the driver file (.inf). When you find the file, choose Open and OK. Then, select the correct driver and choose Next.Don't share the printer and don't print a test page.To select a local printer driver in your WorkSpace:In Print Management, choose All Printers. Right-click the redirected local printer and choose Properties.Note: Local printers use the following naming conventions:PCoIP: <local-printer-name> (Local - <username>.<computername>)WorkSpaces Streaming Protocol (WSP): <local-printer-name> - Redirected (<-computername>)In the printer's Properties dialog box, choose the Advanced tab. For Driver, select the installed driver to assign the new driver to your redirected printer. Choose OK.After you finish changing the printer, review the printer's Properties to confirm the new option. You might need to restart the WorkSpace to see the changes.Note: When you print to a local printer, you can monitor the print job in your local printer queue.Instead of using a local printer, you can use the Microsoft Print to PDF option for your local Windows or macOS system.

Related informationPrint from a WorkSpaceConfigure printer support for PCoIPConfigure printer support for WSPWhen I print from a Windows WorkSpace to a local printer, why do I experience document formatting or printer feature issues?How can I set the default printer on Amazon Windows WorkSpaces and prevent the settings from reverting?