Free Access Amazon Web Services DVA-C02 New Release

The response from the API call indicates that the ProvisionedThroughputExceededException exception has occurred. This exception means that the rate of incoming requests exceeds the throughput limit for one or more shards in a stream. To mitigate this exception, the developer can use one or more of the following techniques:

• Implement retries with exponential backoff. This will introduce randomness in the retry intervals and avoid overwhelming the shards with retries.
• Reduce the frequency and/or size of the requests. This will reduce the load on the shards and avoid throttling errors.
• Increase the number of shards in the stream. This will increase the throughput capacity of the stream and accommodate higher request rates.
• Use a PutRecord API instead of PutRecords. This will reduce the number of records per request and avoid exceeding the payload limit.

References:

• [ProvisionedThroughputExceededException - Amazon Kinesis Data Streams Service API Reference]
• [Best Practices for Handling Kinesis Data Streams Errors]

This solution will meet the requirements by using Amazon CloudFront, which is a content delivery network (CDN) service that speeds up the delivery of web content and APIs to end users. The developer can configure the CloudFront cache, which is a set of edge locations that store copies of popular or recently accessed content close to the viewers. The developer can also update the application to return cached content based upon the default request headers, which are a set of HTTP headers that CloudFront automatically forwards to the origin server and uses to determine whether an object in an edge location is still valid. By caching the POST requests, the developer can optimize the API resources and reduce the latency for repeated queries. Option B is not optimal because it will override the cache method in the selected stage of API Gateway, which is not possible or effective as API Gateway does not support caching for POST methods by default. Option C is not optimal because it will save the latest request response in Lambda /tmp directory, which is a local storage space that is available for each Lambda function invocation, not a cache that can be shared across multiple invocations or requests. Option D is not optimal because it will save the latest request in AWS Systems Manager Parameter Store, which is a service that provides secure and scalable storage for configuration data and secrets, not a cache for API responses.

References: [Amazon CloudFront], [Caching Content Based on Request Headers]

AWS CloudFormation is a service that enables developers to model and provision AWS resources using templates. The developer can use the following steps to avoid accidental database deletion in the future:

• Set up AWS CodeDeploy to deploy the most recent version of the application at runtime. This will ensure that the application code is always up to date and does not depend on the AMI.
• Remove any commands that perform operating system patching from the UserData script. This will reduce the time that the UserData script takes to run and speed up the instance launch process.

References:

• [What Is AWS CloudFormation? - AWS CloudFormation]
• [What Is AWS CodeDeploy? - AWS CodeDeploy]
• [Running Commands on Your Linux Instance at Launch - Amazon Elastic Compute Cloud]

The X-Ray daemon is a software that collects trace data from the X-Ray SDK and relays it to the X-Ray service. The X-Ray daemon can run on any platform that supports Go, including Linux, Windows, and macOS. The developer can install and run the X-Ray daemon on the on-premises servers to capture and relay the data to the X-Ray service with minimal configuration. The X-Ray SDK is used to instrument the application code, not to capture and relay data. The Lambda function solutions are more complex and require additional configuration.

References:

• [AWS X-Ray concepts - AWS X-Ray]
• [Setting up AWS X-Ray - AWS X-Ray]