CI/CD Cost Engineering
📰 Dev.to · SoftwareDevs mvpfactory.io
Optimize CI/CD costs by replacing GitHub-hosted runners with self-hosted runners on AWS/GCP spot instances, and learn how to measure cost-per-build metrics
Action Steps
- Replace GitHub-hosted runners with self-hosted runners on AWS/GCP spot instances using actions-runner-controller
- Configure persistent Gradle/Docker layer caches on shared NVMe volumes for improved performance
- Implement matrix build parallelism tuning to optimize build times
- Set up a cost-per-build metrics framework to track and measure CI/CD costs
- Orchestrate job preemption handling to ensure seamless build interruptions
Who Needs to Know This
DevOps teams and engineers can benefit from this article to reduce CI/CD costs and improve efficiency, while also providing a measurable cost center for stakeholders
Key Insight
💡 Treating CI/CD as a measurable engineering cost center can help optimize costs and improve efficiency
Share This
🚀 Reduce CI/CD costs with self-hosted runners on AWS/GCP spot instances and measure cost-per-build metrics! 📊
Key Takeaways
Optimize CI/CD costs by replacing GitHub-hosted runners with self-hosted runners on AWS/GCP spot instances, and learn how to measure cost-per-build metrics
Full Article
Deep dive into replacing GitHub-hosted runners with self-hosted runners on AWS/GCP spot instances orchestrated by actions-runner-controller, covering graceful job preemption handling, persistent Gradle/Docker layer caches on shared NVMe volumes, matrix build parallelism tuning, and the cost-per-build metrics framework that lets you treat CI/CD as a measurable engineering cost center rather than a blank check
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