Metric Storage & Long-Term Retention Architecture
Design and scale resilient metric storage engines. We configure Cortex and Grafana Mimir clusters, object storage tiering, compactor tuning, and ruler high-availability for multi-year telemetry retention.
Who This Engagement Serves
Platform engineering teams experiencing Prometheus OOM crashes, slow PromQL queries, or escalating cloud storage bills.
Measurable Technical Outcomes
High-availability metric ingestion capable of millions of active series with fast 90-day PromQL range evaluations.
Engagement Scope & Boundaries
Cortex/Mimir component topology (ingester, distributor, querier, store-gateway, compactor), compaction blocks, and object storage lifecycle.
What Is Included
- • Cluster sizing and resource limits for Ingester and Store-Gateway components
- • Object storage backend configuration with S3/GCS/MinIO bucket lifecycle policies
- • Compactor block configuration for efficient multi-resolution downsampling
- • Prometheus remote-write buffering and queue tuning
- • Disaster recovery and shard rebalancing runbooks
What Is Excluded
- • Managing physical data center hardware
Step-by-Step Architectural Process
01. Series Volume Modeling
We measure active series counts, churn rate, and query patterns across teams.
02. Topology & Retention Blueprint
We calculate storage bucket allocations, compactor schedules, and distributor replication factors.
03. Deployment & Load Validation
We deploy the storage cluster, simulate remote-write spikes, and verify query latency under load.
Ready to Structure Your Telemetry Pipeline?
Speak directly with our senior telemetry architects in New Taipei City to align on scope, deliverables, and implementation schedules.