How Medium monitors DynamoDB performance

Medium, a popular blogging platform, uses Amazon DynamoDB as one of its primary data stores to handle rapid scaling. Monitoring and managing the performance of DynamoDB is crucial for maintaining an optimal user experience. The main challenge faced by Medium is throttling, which can cause high latency and user-facing errors. To tackle this issue, Medium uses Datadog to track whole-table capacity usage and compares it with provisioned capacity. They also calculate the number of partitions per table and estimate the throughput limit for each partition. By tracking hot keys and throttling events, Medium can take action to increase capacity when needed. Additionally, they use Redis as a cache in front of DynamoDB to reduce throttling frequency and lower costs. Proper alerting is essential for resolving issues quickly, and Medium uses Datadog's alerting features to notify the right people with the appropriate channels and messages. Monitoring also helps Medium identify when they can scale down their provisioned throughput, optimizing infrastructure expenses.

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