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How to manage feature flags without making performance worse

How to manage feature flags without making performance worse

Adam McKerlie

Sarah Guthals

The ProblemJump To Solution

Using libraries like Flagr to help maintain feature flags had a negative performance impact; it was taking 900ms to only check 50 flags.

Flagr took 900ms to check 50 flags, 500ms specifically on evaluation

Using Sentry performance monitoring, we discovered the majority of the time was spent deserializing the Flagr response.

The Solution

Digging into the client, we noticed that deserialization was turning the entire JSON blob (i.e. the flag results) into a Python object. While deserializing JSON is convenient from a development perspective, because we were only using a few JSON fields, the cost just wasn’t worth it.

After removing caching and patching our own deserializer with a simple json.loads(response.data) we saw a huge improvement in speed — so much so that other areas began to look slow by comparison:

Flagr is now only taking 200ms

Further Reading

  • Sentry BlogPython Performance Testing: A Comprehensive Guide
  • Sentry BlogLogging in Python: A Developer’s Guide
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