🏭 I built a small #tutorial that illustrates how sidecar containers can transform observability and control in any Kubernetes‐based service. Instead of embedding metrics, logging, and networking logic directly into your app, you simply “bolt on” three dedicated sidecars:

1. Prometheus – Collects application and infrastructure metrics out of the box.

2. Promtail → Grafana Loki – Streams logs in real time without changing your app code.

3. Envoy Proxy – Handles TLS termination, request filtering, and even simulates network failures.

✅ Why this Matters

- Separation of Concerns: All observability (metrics + logs) and networking (TLS, filters, chaos testing) live outside the main container. Your app stays lightweight and focused solely on business logic.

- Consistency Across Services: You can reuse the exact same Prometheus/Promtail/Envoy configuration for every microservice. No more “one‐off” instrumentation code in each repo.

- Faster Development & Onboarding: Developers don’t need to spend time wiring in monitoring libraries or custom proxy code—sidecars handle it for you automatically.

- Easier Upgrades and Troubleshooting: When you need to tweak logging formats or experiment with TLS settings, you update the sidecar image, not dozens of disparate applications.

⚠️ Considerations

- Resource Overhead: Each sidecar adds CPU/memory usage. In lightweight deployments, be mindful of your node capacity and pod limits.

- Operational Complexity: More containers per Pod means more YAML to manage and additional network hops. You’ll need to ensure your CI/CD and Helm charts stay up to date.

- Sidecar Lifecycle: When you roll out a new version of your app, the sidecar versions may need to stay in sync (e.g., Promtail pipelines). Establish clear versioning and testing practices.

Ultimately, moving observability and networking logic into reusable sidecars makes your main application image lighter, speeds up developer onboarding, and enforces a consistent control plane across all services. If you’re evaluating how to standardize monitoring, logging, and network policies at scale, consider a sidecar‐centric approach. It’s a small shift in architecture that can pay big dividends in maintainability and speed.

https://github.com/creotiv/sidecar-demo

Machine Learning World

🏭 I built a small #tutorial that illustrates how sidecar containers can transform observability and control in any Kubernetes‐based service. Instead of embedding metrics, logging, and networking logic directly into your app, you simply “bolt on” three dedicated sidecars:

1. Prometheus – Collects application and infrastructure metrics out of the box.

2. Promtail → Grafana Loki – Streams logs in real time without changing your app code.

3. Envoy Proxy – Handles TLS termination, request filtering, and even simulates network failures.

✅ Why this Matters

- Separation of Concerns: All observability (metrics + logs) and networking (TLS, filters, chaos testing) live outside the main container. Your app stays lightweight and focused solely on business logic.

- Consistency Across Services: You can reuse the exact same Prometheus/Promtail/Envoy configuration for every microservice. No more “one‐off” instrumentation code in each repo.

- Faster Development & Onboarding: Developers don’t need to spend time wiring in monitoring libraries or custom proxy code—sidecars handle it for you automatically.

- Easier Upgrades and Troubleshooting: When you need to tweak logging formats or experiment with TLS settings, you update the sidecar image, not dozens of disparate applications.

⚠️ Considerations

- Resource Overhead: Each sidecar adds CPU/memory usage. In lightweight deployments, be mindful of your node capacity and pod limits.

- Operational Complexity: More containers per Pod means more YAML to manage and additional network hops. You’ll need to ensure your CI/CD and Helm charts stay up to date.

- Sidecar Lifecycle: When you roll out a new version of your app, the sidecar versions may need to stay in sync (e.g., Promtail pipelines). Establish clear versioning and testing practices.

Ultimately, moving observability and networking logic into reusable sidecars makes your main application image lighter, speeds up developer onboarding, and enforces a consistent control plane across all services. If you’re evaluating how to standardize monitoring, logging, and network policies at scale, consider a sidecar‐centric approach. It’s a small shift in architecture that can pay big dividends in maintainability and speed.

https://github.com/creotiv/sidecar-demo

GitHub

GitHub - creotiv/sidecar-demo: Simple project to show how to use sidecar containers inside K8S to make life easier

Simple project to show how to use sidecar containers inside K8S to make life easier - creotiv/sidecar-demo

hottg.com/ml_world/1089

1.1K viewsAndrey Nikishaev, Jun 2 at 16:56