Some practical ops guidance that might helps we've developed: Monitoring - CloudWatch with custom metrics. Alerting - PagerDuty with intelligent routing. Documentation - Notion for team wikis. Training - monthly lunch and learns. These have helped us maintain low incident count while still moving fast on new features.
One more thing worth mentioning: team morale improved significantly once the manual toil was automated away.
For context, we're using Elasticsearch, Fluentd, and Kibana.
Solid work putting this together! I have a few questions: 1) How did you handle authentication? 2) What was your approach to migration? 3) Did you encounter any issues with costs? We're considering a similar implementation and would love to learn from your experience.
Feel free to reach out if you have more questions - happy to share our runbooks and documentation.
I'd recommend checking out the community forums for more details.
The end result was 60% improvement in developer productivity.
For context, we're using Datadog, PagerDuty, and Slack.
For context, we're using Kubernetes, Helm, ArgoCD, and Prometheus.
Feel free to reach out if you have more questions - happy to share our runbooks and documentation.
One more thing worth mentioning: team morale improved significantly once the manual toil was automated away.
Additionally, we found that automation should augment human decision-making, not replace it entirely.
For context, we're using Istio, Linkerd, and Envoy.
For context, we're using Datadog, PagerDuty, and Slack.
Adding my two cents here - focusing on maintenance burden. We learned this the hard way when the initial investment was higher than expected, but the long-term benefits exceeded our projections. Now we always make sure to include in design reviews. It's added maybe a few hours to our process but prevents a lot of headaches down the line.
Additionally, we found that failure modes should be designed for, not discovered in production.
The end result was 90% decrease in manual toil.
Here's the technical breakdown of our implementation. Architecture: hybrid cloud setup. Tools used: Elasticsearch, Fluentd, and Kibana. Configuration highlights: GitOps with ArgoCD apps. Performance benchmarks showed 50% latency reduction. Security considerations: container scanning in CI. We documented everything in our internal wiki - happy to share snippets if helpful.
Additionally, we found that starting small and iterating is more effective than big-bang transformations.
Feel free to reach out if you have more questions - happy to share our runbooks and documentation.
One thing I wish I knew earlier: cross-team collaboration is essential for success. Would have saved us a lot of time.
One more thing worth mentioning: integration with existing tools was smoother than anticipated.
I'd recommend checking out relevant blog posts for more details.
Additionally, we found that automation should augment human decision-making, not replace it entirely.
I'd recommend checking out conference talks on YouTube for more details.
Nice! We did something similar in our organization and can confirm the benefits. One thing we added was drift detection with automated remediation. The key insight for us was understanding that cross-team collaboration is essential for success. We also found that we discovered several hidden dependencies during the migration. Happy to share more details if anyone is interested.
I'd recommend checking out the community forums for more details.
For context, we're using Jenkins, GitHub Actions, and Docker.