mimir
Stand up Grafana Mimir for horizontally scalable, multi-tenant, long-term Prometheus + OTLP metrics storage. Covers monolithic / read-write / microservices deployment, S3 / GCS / Azure / filesystem block storage, Prometheus `remote_write` and OTLP ingestion, multi-tenancy with `X-Scope-OrgID`, ingester replication factor, compactor retention, and per-tenant limits. Use when running Mimir locally or on Kubernetes (Helm `mimir-distributed`), scaling Prometheus past a single node, picking ingest / query / backend split, configuring tenants and ingestion rate, debugging `/ready` 503s or `429 Too Many Requests`, or pointing Grafana at a Mimir datasource — even when the user says "I need long-term Prometheus storage", "scale Prometheus", "multi-tenant metrics backend", "Cortex replacement", "remote_write target", or "store 10M active series" without naming Mimir.
Works with
---
name: mimir
description: Stand up Grafana Mimir for horizontally scalable, multi-tenant, long-term Prometheus + OTLP metrics storage. Covers monolithic / read-write / microservices deployment, S3 / GCS / Azure / filesystem block storage, Prometheus `remote_write` and OTLP ingestion, multi-tenancy with `X-Scope-OrgID`, ingester replication factor, compactor retention, and per-tenant limits. Use when running Mimir locally or on Kubernetes (Helm `mimir-distributed`), scaling Prometheus past a single node, picking ingest / query / backend split, configuring tenants and ingestion rate, debugging `/ready` 503s or `429 Too Many Requests`, or pointing Grafana at a Mimir datasource — even when the user says "I need long-term Prometheus storage", "scale Prometheus", "multi-tenant metrics backend", "Cortex replacement", "remote_write target", or "store 10M active series" without naming Mimir.
license: Apache-2.0
---
# Grafana Mimir
> **Docs**: https://grafana.com/docs/mimir/latest/
Horizontally scalable, multi-tenant, long-term storage for Prometheus + OpenTelemetry metrics.
## Prerequisites
- Docker (for quick start) or a Kubernetes cluster (for Helm)
- An object-storage bucket for production (S3/GCS/Azure) — filesystem only for dev
- Prometheus or Alloy able to remote_write to the Mimir push endpoint
## Common Workflows
### 1. Stand up monolithic Mimir locally
```yaml
# demo.yaml
target: all
multitenancy_enabled: false
blocks_storage:
backend: filesystem
bucket_store:
sync_dir: /tmp/mimir/tsdb-sync
filesystem:
dir: /tmp/mimir/data/tsdb
tsdb:
dir: /tmp/mimir/tsdb
compactor:
data_dir: /tmp/mimir/compactor
sharding_ring:
kvstore: { store: memberlist }
distributor:
ring:
instance_addr: 127.0.0.1
kvstore: { store: memberlist }
ingester:
ring:
instance_addr: 127.0.0.1
kvstore: { store: memberlist }
replication_factor: 1
server:
http_listen_port: 9009
grpc_listen_port: 9095
log_level: error
```
```bash
# 1. Run it
docker run --rm -p 9009:9009 -v $(pwd)/demo.yaml:/etc/mimir/demo.yaml \
grafana/mimir:latest --config.file=/etc/mimir/demo.yaml
# 2. Verify readiness (expect HTTP 200, body: "ready")
curl -sf http://localhost:9009/ready
# 3. Verify it's serving the API
curl -s http://localhost:9009/api/v1/labels | jq '.status' # → "success"
# 4. Verify self-metrics scrape
curl -s http://localhost:9009/metrics | grep -E '^mimir_(distributor|ingester)_' | head
```
### 2. Send metrics — Prometheus remote_write
```yaml
remote_write:
- url: http://localhost:9009/api/v1/push
headers:
X-Scope-OrgID: tenant1 # required when multitenancy_enabled: true
```
```bash
# Verify samples are landing
curl -s -H 'X-Scope-OrgID: tenant1' \
'http://localhost:9009/api/v1/query?query=up' | jq '.data.result | length'
# Expect > 0 within ~30s of Prometheus scraping
```
### 3. Send metrics — Grafana Alloy
```alloy
prometheus.remote_write "mimir" {
endpoint {
url = "http://mimir:9009/api/v1/push"
headers = { "X-Scope-OrgID" = "tenant1" }
}
}
```
### 4. Deploy on Kubernetes (Helm, microservices)
```bash
# 1. Install
helm repo add grafana https://grafana.github.io/helm-charts
helm install mimir grafana/mimir-distributed --version 6.0.6 -f values.yaml
# 2. Verify every pod is Running / Ready
kubectl get pods -n mimir
# distributor, ingester, querier, query-frontend, store-gateway, compactor, ruler
# 3. Verify the gateway is ready
kubectl port-forward -n mimir svc/mimir-nginx 9009:80 &
curl -sf http://localhost:9009/ready
```
## Multi-tenancy
```yaml
multitenancy_enabled: true
# Every request must include header: X-Scope-OrgID: <tenant-id>
```
For storage backends (S3 / GCS / Azure / filesystem) see [`references/storage.md`](references/storage.md). For component roles, ring options, limits, and API endpoint dumps see [`references/architecture.md`](references/architecture.md).
## Troubleshooting
- `/ready` returns 503 → ingester still joining ring; check `mimir_ring_members` and ingester logs
- `429 Too Many Requests` on push → bump `limits.ingestion_rate` / `ingestion_burst_size`
- Samples written but query returns empty → confirm `X-Scope-OrgID` matches between write and read
- Query for old data returns nothing → check compactor logs and that store-gateway has synced blocks
## Resources
- [Mimir docs](https://grafana.com/docs/mimir/latest/)
- [Helm chart `mimir-distributed`](https://github.com/grafana/mimir/tree/main/operations/helm/charts/mimir-distributed)
- [Architecture reference](https://grafana.com/docs/mimir/latest/references/architecture/)More Debugging skills
diagnosing-bugs
mattpocock/skills
Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.
explore-code
lllllllama/rigorpilot-skills
Rigor Improve implementation leaf skill for auditable candidate implementation in deep learning research repositories. Use when the researcher explicitly authorizes exploratory work on an isolated branch or worktree to transplant modules, adapt a backbone, add LoRA or adapter layers, replace a head, or stitch together meaningful low-risk migration ideas with rollback-aware records in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline reproduction, conservative debugging, environment setup, verified contribution claims, or default repository analysis.
safe-debug
lllllllama/rigorpilot-skills
Rigor Debug / Rigor Audit skill for deep learning research work. Use when the user pastes a traceback, terminal error, CUDA OOM, checkpoint load failure, shape mismatch, NaN loss symptom, or training failure and wants conservative diagnosis before any patching, with debug fixes clearly separated from research contributions. Do not use for broad refactoring, speculative adaptation, automatic exploratory patching, or general repository familiarization.

