Engineering teams lose hours in the gap between detecting a problem and getting a fix into review. An on-call engineer sees an error spike in Datadog, pivots to traces and logs to isolate the failure, opens the relevant repository, reproduces the issue, writes a fix, adds tests, waits on CI, and finally opens a pull request. Even when the problem is familiar, the workflow pulls engineers across several tools and stretches remediation from minutes into hours or days.
Bits Code closes that gap by turning high-impact Datadog findings into code changes that engineers can review. When Datadog surfaces an error, performance regression, profiling hotspot, flaky test, vulnerability, slow query, or Kubernetes issue, Bits Code can investigate the issue by using the telemetry data and service context already available in Datadog. It then generates a targeted code change, adds unit tests, iterates through CI failures, and opens a pull request in GitHub within minutes for an engineer to review.
In this post, we’ll show how Bits Code:
Turns a Datadog finding into a reviewable PRGrounds code changes in production context Handles general coding tasks through direct promptingRuns on demand, on a schedule, or based on custom trigger rules Operates within enterprise access and governance controls
