Let me tell you how we approached this. We started about 10 months ago with a small pilot. Initial challenges included legacy compatibility. The breakthrough came when we improved observability. Key metrics improved: 60% improvement in developer productivity. The team's feedback has been overwhelmingly positive, though we still have room for improvement in testing coverage. Lessons learned: communicate often. Next steps for us: expand to more teams.
For context, we're using Jenkins, GitHub Actions, and Docker.
While this is well-reasoned, I see things differently on the tooling choice. In our environment, we found that Elasticsearch, Fluentd, and Kibana worked better because security must be built in from the start, not bolted on later. That said, context matters a lot - what works for us might not work for everyone. The key is to invest in training.
For context, we're using Kubernetes, Helm, ArgoCD, and Prometheus.
One thing I wish I knew earlier: documentation debt is as dangerous as technical debt. Would have saved us a lot of time.
Timely post! We're actively evaluating this approach. Could you elaborate on tool selection? Specifically, I'm curious about team training approach. Also, how long did the initial implementation take? Any gotchas we should watch out for?
For context, we're using Terraform, AWS CDK, and CloudFormation.
For context, we're using Grafana, Loki, and Tempo.
For context, we're using Jenkins, GitHub Actions, and Docker.
Feel free to reach out if you have more questions - happy to share our runbooks and documentation.
Key takeaways from our implementation: 1) Automate everything possible 2) Use feature flags 3) Practice incident response 4) Measure what matters. Common mistakes to avoid: not measuring outcomes. Resources that helped us: Google SRE book. The most important thing is learning over blame.
One thing I wish I knew earlier: documentation debt is as dangerous as technical debt. Would have saved us a lot of time.
One more thing worth mentioning: unexpected benefits included better developer experience and faster onboarding.
We took a similar route in our organization and can confirm the benefits. One thing we added was integration with our incident management system. The key insight for us was understanding that failure modes should be designed for, not discovered in production. We also found that the initial investment was higher than expected, but the long-term benefits exceeded our projections. Happy to share more details if anyone is interested.
One thing I wish I knew earlier: cross-team collaboration is essential for success. Would have saved us a lot of time.
Great post! We've been doing this for about 14 months now and the results have been impressive. Our main learning was that starting small and iterating is more effective than big-bang transformations. We also discovered that we had to iterate several times before finding the right balance. For anyone starting out, I'd recommend automated rollback based on error rate thresholds.
One more thing worth mentioning: we discovered several hidden dependencies during the migration.
Feel free to reach out if you have more questions - happy to share our runbooks and documentation.