Typorithm · hard

Service Mesh & Observability

service-mesharchitecturetracingobservability

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Step 1 of 8 · intro card

Learn Service Mesh & Observability

Distributed Data & Ops

A service mesh uses sidecar proxies to handle mTLS, traffic routing, and retries outside the app. Observability layers on top: distributed tracing with propagated trace ids, per-service RED metrics, correlation-id logging, and liveness/readiness health checks.

A service mesh inserts a sidecar proxy beside every service instance. The proxies handle mutual TLS, traffic routing, retries, and timeouts so that cross-cutting network concerns live in the platform instead of being re-implemented in each service.

Because a single request now hops through many services, you cannot debug from one log file. Distributed tracing propagates a trace id along the whole path so you can reconstruct the request end to end, and correlation ids tie together every log line emitted while handling it.

RED metrics — Rate, Errors, Duration — give each service a uniform health signal, and health checks let the orchestrator manage instances: a liveness probe restarts a hung process, while a readiness probe gates traffic until the service is actually ready to serve.

A service mesh uses sidecar proxies for mTLS, routing, and retries.

Distributed tracing propagates a trace id across services.

RED = Rate, Errors, Duration, per service.

ops:
  mesh: sidecar-proxy-mtls
  tracing: distributed-trace-ids
  metrics: per-service-red
  logging: correlation-ids
  health: liveness-readiness

Read the implementation

Connect each part of the code to the concept before you type.

1. Sidecar proxy mesh

A service mesh runs a sidecar proxy next to each service to handle mTLS, traffic routing, and retries outside the application code.

mesh: sidecar-proxy-mtls

2. Distributed tracing

A trace id is propagated across every service a request touches so you can follow one request end to end.

tracing: distributed-trace-ids

3. RED metrics

RED metrics — Rate, Errors, Duration — are collected per service to show its health at a glance.

metrics: per-service-red

4. Correlation-id logging

Correlation ids in log lines let you stitch together all the logs produced while handling one request.

logging: correlation-ids

5. Health probes

Liveness probes detect a hung process to restart; readiness probes tell the platform when a service is ready to receive traffic.

health: liveness-readiness

A complete learning loop

Understand

Read the concept map and follow the code breakdown.

Reconstruct

Type the implementation, repair mistakes and work through every recall exercise.

Verify

Use the final check without hints; revisit weak concepts in short practice sessions.