Here are some operational tips that worked for uss we've developed: Monitoring - CloudWatch with custom metrics. Alerting - custom Slack integration. Documentation - Notion for team wikis. Training - pairing sessions. These have helped us maintain high reliability while still moving fast on new features.
I'd recommend checking out the community forums for more details.
One thing I wish I knew earlier: observability is not optional - you can't improve what you can't measure. Would have saved us a lot of time.
This helps! Our team is evaluating this approach. Could you elaborate on success metrics? Specifically, I'm curious about how you measured success. Also, how long did the initial implementation take? Any gotchas we should watch out for?
Additionally, we found that documentation debt is as dangerous as technical debt.
I'd recommend checking out the community forums for more details.
One thing I wish I knew earlier: the human side of change management is often harder than the technical implementation. Would have saved us a lot of time.
This happened to us! Symptoms: frequent timeouts. Root cause analysis revealed memory leaks. Fix: fixed the leak. Prevention measures: better monitoring. Total time to resolve was 15 minutes but now we have runbooks and monitoring to catch this early.
For context, we're using Terraform, AWS CDK, and CloudFormation.
Additionally, we found that failure modes should be designed for, not discovered in production.
One more thing worth mentioning: unexpected benefits included better developer experience and faster onboarding.
Great post! We've been doing this for about 11 months now and the results have been impressive. Our main learning was that failure modes should be designed for, not discovered in production. We also discovered that we underestimated the training time needed but it was worth the investment. For anyone starting out, I'd recommend chaos engineering tests in staging.
The end result was 60% improvement in developer productivity.
For context, we're using Kubernetes, Helm, ArgoCD, and Prometheus.
One more thing worth mentioning: we discovered several hidden dependencies during the migration.
Looking at the engineering side, there are some things to keep in mind. First, data residency. Second, backup procedures. Third, performance tuning. We spent significant time on testing and it was worth it. Code samples available on our GitHub if anyone wants to take a look. Performance testing showed 10x throughput increase.
I'd recommend checking out the official documentation for more details.
One more thing worth mentioning: team morale improved significantly once the manual toil was automated away.