[Engineering Log] The Phased Migration to Kubernetes
- #retrospective
- #platform
- #kubernetes
Context
Moving a full observability stack (Alloy, Loki, Grafana, Postgres) from Docker Compose to Kubernetes is a high-stakes operation. A "Big Bang" migration carries significant risk of data loss and complex, multi-component failures that are difficult to debug in a new environment.
The transition introduces three primary architectural risks:
- Stateful Persistence: Moving from host-path volumes to Kubernetes-native Persistent Volume Claims (PVCs) requires validating storage-class handshakes and data availability across nodes.
- Telemetry Loopback: The tight coupling between components (Grafana/Postgres, Alloy/Loki) creates a "nervous system" where a networking failure in a new CNI (Container Network Interface) can blind the entire diagnostic stack.
- Configuration Complexity: Shifting from flat environment variables to Secrets, ConfigMaps, and RBAC-scoped ServiceAccounts adds layers of potential failure during initial deployment.
Challenge
- The Pain Point: "Big Bang" migrations are fragile. A database failure results in log loss; if logs fail, visibility into the database failure is lost, creating a circular diagnostic trap.
- The Question: How can I migrate critical stateful services and telemetry agents without losing historical data or system visibility during the migrations?
Investigation
I chose a Risk-Based Phased Migration over a one-time cutover.
| Option | Pros | Cons | Decision |
|---|---|---|---|
| Big Bang | Theoretically faster execution. | High risk of cascading bugs; extremely difficult to root-cause failures. | ❌ |
| Phased | Isolates failures; validates the platform layer-by-layer. | Increases temporary architectural complexity (Hybrid mode). | ✅ |
- Strategy: Move from Lowest Risk (Stateless/Agents) to Highest Risk (Stateful/Core Data).
Solution
The migration was executed in four distinct "gates," with each phase acting as a prerequisite for the next:
- 🏗️ Phase 1: Alloy (Agent) - Established the telemetry pipeline.
- 🪵 Phase 2: Loki (Log Store) - Validated Persistent Volume Claims (PVCs) and storage.
- 📊 Phase 3: Grafana (UI) - Switched the "Pane of Glass" to native Kubernetes.
- 💾 Phase 4: Postgres (Core) - Migrated the "Heart" using the StatefulSet & Volume Sync pattern.
The critical insight was using Phase 1 and 2 to build the monitoring for Phase 4. By the time the database moved, the Kubernetes-native logs and metrics were already live and verified.
Evolution
- Result: 100% of services migrated with zero data loss and full audit trails in Loki.
- Lesson: "Go slow to go fast." The hybrid phase (Docker + K3s) felt complex, but it provided the safety net needed for the stateful leap.
Thank you
Big thanks for reading! You’re awesome, and I hope this post helped. Until next time!