Exceeding Provisioned Throughput in DynamoDB: Solutions and Fixes

Solutions for Exceeding Provisioned Throughput in DynamoDB

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Question

You have exceeded your maximum allowed provisioned throughput for a table in DynamoDB.

Which of the following approaches are correct to fix this problem? (Select Three)

Answers

Explanations

Click on the arrows to vote for the correct answer

A. B. C. D. E.

Correct Answer: A, D & E.

Option A is CORRECT because each partition is limited to 100 Reads per second.

If a partition receives more than 100 reads per second it will become a Hot Partition and the performance of the table will be reduced.

If you distribute your queries to more partition keys, you can prevent them from becoming Hot partitions.

More details: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/bp-partition-key-design.html.

Option B is incorrect because DynamoDB streams are used for stored item level modifications, it does not affect the performance or the throughput.

More details: https://aws.amazon.com/blogs/database/dynamodb-streams-use-cases-and-design-patterns/

Option C is incorrect because DynamoDB TTL is designed to reduce the data stored volume, it does not affect the performance or the throughput.

More details: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/TTL.html.

Option D is CORRECT because DAX increase the performance and throughput of repeated read queries.

More details: https://docs.amazonaws.cn/en_us/amazondynamodb/latest/developerguide/DAX.html.

Option E is CORRECT because you can manage the quantity of error retries or increase timeouts between retries.

More details: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Programming.Errors.html.

When you exceed your maximum allowed provisioned throughput for a table in DynamoDB, it means that you have reached the limit of read and write capacity units that you have provisioned for that table. Provisioned throughput is the amount of data that DynamoDB can read or write in a second, and it is determined by the amount of read and write capacity units that you have provisioned for the table.

To fix this problem, you can take the following approaches:

A. In your DynamoDB table distribute all the operations read and written across more distinct partition key values. DynamoDB partitions your data across multiple partitions to achieve scalability and high availability. Each partition has a limited amount of throughput capacity, and if you are overloading a single partition, you can distribute the load across more distinct partition key values to improve performance. By using a different partition key, you can distribute the data evenly across multiple partitions, and this will increase the overall throughput capacity of your table.

B. Enable DynamoDB Streams. DynamoDB Streams is a feature that allows you to capture changes to your DynamoDB table and then process them in real-time. By enabling DynamoDB Streams, you can create triggers to perform certain actions when specific events happen in your table. For example, you can create a trigger to notify you when a certain number of read or write capacity units are consumed, and then take appropriate actions to fix the problem.

C. Enable DynamoDB Time to Live. DynamoDB Time to Live (TTL) is a feature that allows you to automatically delete expired items from your table. By enabling DynamoDB TTL, you can reduce the amount of data that you need to store in your table, and this will free up capacity units that you can use for other operations. For example, if you have a table that stores log data, you can set a TTL to automatically delete logs that are older than a certain time period.

D. Implement DAX (DynamoDB Accelerator) as a cache solution to improve the performance of the tables. DynamoDB Accelerator (DAX) is a caching service that provides a high-performance, in-memory cache for DynamoDB tables. By implementing DAX, you can reduce the number of requests that you make to DynamoDB and improve the response time of your applications. DAX can also help you reduce the amount of provisioned throughput that you need to provision for your DynamoDB tables.

E. Implement error retries and exponential backoff in your application code. When you exceed your maximum allowed provisioned throughput for a table in DynamoDB, you may receive ProvisionedThroughputExceededException errors in your application code. To handle these errors, you can implement error retries and exponential backoff in your application code. By retrying failed requests with increasing delays between retries, you can reduce the number of failed requests and improve the overall throughput capacity of your table.

In conclusion, to fix the problem of exceeding your maximum allowed provisioned throughput for a table in DynamoDB, you can use a combination of the above approaches. You can distribute the load across more distinct partition key values, enable DynamoDB Streams and TTL, implement DAX as a cache solution, and implement error retries and exponential backoff in your application code.