devops

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I Accidentally Became the DevOps Guy
2 months ago
- The author used a SaaS/PaaS stack (Supabase, Vercel, Render) for over three years without traditional cloud providers like AWS or GCP.
- Changes in Render's pricing (reduced bandwidth from 100GB to 5GB) and higher costs for managed compute prompted a migration to AWS.
- Terraform was adopted from the start to manage multi-project, multi-environment infrastructure repeatably.
- Backend services moved from Render to ECS on Fargate, with GitHub Actions for CI/CD and RDS for the database.
- A key issue was RDS automatic password rotation causing production outages because the application used a static DATABASE_URL instead of the managed secret.
- The database experience on RDS was inferior to Supabase's table viewer and SQL editor, making casual data inspection cumbersome.
- The migration saved about $15-20 per month but introduced significant time spent on learning, debugging, and maintaining infrastructure.
- The author concludes that moving to a cloud provider is only worthwhile when the team has enough bandwidth to own the infrastructure long-term.
Ihatedevops.com – because DevOps separates vibe coder from engineer
2 months ago
- The skill 'ihatedevops' automatically injects 10 atomic DevOps best practices into every Claude session.
- When asking for a Dockerfile, it provides secure Chainguard images, multi-stage builds, and non-root user configurations.
- When asking for a CI pipeline, it gives SHA-pinned actions and least-privilege tokens.
- Installation is done via the Claude plugin marketplace with specific add and install commands.
DORA? I barely know her!
2 months ago
- The DORA metrics are used to understand and monitor team performance in terms of maintainability, reliability, and efficiency.
- These metrics are second-order data derived from first-order data such as deployment timestamps, feature lists, and failure events.
- Deployment frequency can be tracked by tagging deployed commits in Git or using CI tools to record deployment timestamps.
- Mean time to deployment requires tracking feature lifecycle through Git history with labeled commits and release tags.
- Change failure rate needs manual identification of failures and associating them with the causing deployment, using bug-tracking systems.
- Time to restore service is obtained from monitoring systems by recording failure start and restoration times.
- Automated data extraction from version control, bug tracking, and monitoring systems is essential to avoid manual overhead.
- Clear upfront definitions of terms like 'failure', 'deployment', and 'feature' are necessary for meaningful data analysis.
Using Nix with Dockerfiles
2 months ago
- Nix provides a consistent environment across development (Linux and Mac), CI, and production, eliminating the need for separate configurations.
- Using Nix as a single source of truth prevents common issues like mismatched dependencies or environments that break after updates.
- The Dockerfile approach uses Nix to build the application and copies only the minimal closure of dependencies into a scratch image, resulting in small, reproducible images.
- A practical example with Python and Flask demonstrates how to define a Nix flake and a Dockerfile for building and running the application.
- Downsides include the learning curve of Nix and suboptimal Docker layer caching, but benefits compound when reusing the configuration for development and CI.
Understanding ECS from Kubernetes Perspective
3 months ago
- Containerizing a small team's app often leads to adopting Kubernetes by default, resulting in maintenance overhead and delayed app development.
- ECS is a container orchestrator with fewer moving parts than Kubernetes, offering similar functionality with fewer operational decisions and defaults.
- The core concept of both ECS and Kubernetes involves declaring desired state and using a control loop to enforce it, enabling features like rolling deployments.
- ECS reduces operational burden by eliminating version upgrades, deprecation cycles, and many management layers, making it suitable for small teams.
- Key benefits of ECS include no control plane costs, less engineering time spent on maintenance, and a focus on app debugging over platform issues.
- Drawbacks of ECS include limited operator ecosystem, less tooling support, potential hiring challenges, and a control ceiling for advanced features.
- EKS is recommended for teams with dedicated platform operators, need for stateful infrastructure not offered by AWS, multi-cloud requirements, or existing Kubernetes expertise.
- For small teams (under 10 engineers) shipping web products, ECS minimizes operational complexity, allowing focus on product development rather than infrastructure management.
Show HN: Grade your code's post-quantum crypto exposure A–F, free, in-browser
3 months ago
- A Cryptographic Bill of Materials (CBOM) is crucial for identifying quantum-vulnerable cryptography in your stack as part of PQC migration.
- An open-source scanner provides a full scan in CI/CD workflows, generating a CycloneDX 1.6 CBOM, SARIF report, and an A–F grade badge without uploading data.
- The scan can be run locally via npm or integrated into GitHub Actions, with options to fail builds on broken classical cryptography.
- For audit readiness, an Evidence Pack Express offers a cryptographically signed deliverable including an executive summary, findings, CBOM, and migration plan.
- Note: The scanner is lexical, findings are leads to verify, not a complete inventory, and it does not guarantee quantum safety or certification.
Show HN: Mirrors – test AI agent changes by replaying production traces
3 months ago
- Mirrors converts production traces into an isolated copy of an agent's environment for safe testing.
- It rebuilds schemas, discovers tools, and provides a runnable copy with seeded databases and scored tool matches.
- Enables replaying agents consistently to measure accuracy, catch regressions, and ensure changes work before deployment.
- Offers deterministic, byte-identical worlds for reliable failure reproduction without touching production systems.
- Supports on-demand launch, scaling to zero, per-minute metering, and integration via a versioned API and workspace keys.
- Provides free building with deterministic seeding, with Custom plans for unlimited sandboxes, API access, and SSO.

devops

I Accidentally Became the DevOps Guy

Ihatedevops.com – because DevOps separates vibe coder from engineer

DORA? I barely know her!

Using Nix with Dockerfiles

Understanding ECS from Kubernetes Perspective

Show HN: Grade your code's post-quantum crypto exposure A–F, free, in-browser

Show HN: Mirrors – test AI agent changes by replaying production traces