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tidalDB on Kubernetes
How to run tidalDB on Kubernetes. Two manifest sets ship in this repo, mutually exclusive per namespace:
k8s/— the hardened single-node standalone deployment (namespacetidaldb,replicas: 1). Apply withkubectl apply -k k8s/. This is the recommended default: aStatefulSetwith a durable volume, the three health probes, metrics, secret-backed auth, and graceful rolling updates.k8s/cluster/— the multi-region cluster reference (namespacetidaldb-cluster,replicas: 3, automatic election, quorum-ack writes, elastic membership). Apply withkubectl apply -k k8s/cluster/. Still--experimental-cluster-gated. See Cluster mode on Kubernetes below.
Deploy the STANDALONE server, one replica (recommended default)
tidalDB is single-node-first: the server wraps one embedded engine whose state (WAL + checkpoints + indexes) lives on a data dir. It scales vertically (a bigger pod), not by adding replicas — there is no shared-storage multi-writer mode, so
replicas: 1in the standalone StatefulSet is load-bearing. Run one standalone pod, back it with a durablePersistentVolume, and recover from the WAL on restart (see recovery).The standalone pod remains the recommended deployment. The multi-region
clustermode is now genuinely HA — quorum-acked writes (m11p3), automatic election/failover (m11p4), and elastic membership (m11p5) all exist — but it is still--experimental-cluster-gated, so choose it deliberately when you need multi-node availability, and keep a single standalone pod when you do not. The cluster reference isk8s/cluster/; see Cluster mode on Kubernetes.
What's in k8s/
| File | Purpose |
|---|---|
namespace.yaml |
The tidaldb namespace |
schema-configmap.yaml |
The schema YAML the server loads (--schema); edit for your signals |
statefulset.yaml |
The server: durable PVC, probes, security context, resources |
service.yaml |
Headless Service for stable DNS + in-cluster clients |
poddisruptionbudget.yaml |
maxUnavailable: 0 — a drain can't silently kill the single node |
secret.example.yaml |
Template for the API-key secret (create the real one out-of-band) |
servicemonitor.yaml |
Optional Prometheus-Operator scrape config (apply separately) |
kustomization.yaml |
Ties the core resources together for kubectl apply -k |
Prerequisites
- A Kubernetes cluster (1.25+) and
kubectlpointed at it. For local testing,kindis used in the walkthrough below. - A container registry the cluster can pull from (for real clusters), or a local
image loaded into the node (for
kind). The image is built fromdocker/deploy/Dockerfile. - A default
StorageClass(for dynamicPersistentVolumeClaimprovisioning).kind, GKE, EKS, and AKS all ship one.
Deploy
1. Build and publish the image
# From the repo root — the build context must be the workspace root.
docker build -f docker/deploy/Dockerfile -t <registry>/tidaldb:<tag> .
docker push <registry>/tidaldb:<tag>
Set that reference in k8s/statefulset.yaml (image:), pinned by digest in
production (@sha256:...).
2. Create the namespace and the API-key secret
The secret is deliberately not in the kustomization so no key lands in git. Create it directly:
kubectl create namespace tidaldb
kubectl -n tidaldb create secret generic tidaldb-api-key \
--from-literal=api-key="$(openssl rand -hex 32)"
In production, manage it with External Secrets Operator, Sealed Secrets, or
Vault Agent instead. The StatefulSet injects it as TIDAL_API_KEY — clients
then send Authorization: Bearer <key> on every data route. If the secret is
empty the server runs unauthenticated and logs a WARN — never do that on a
shared network.
3. Edit the schema (optional)
k8s/schema-configmap.yaml carries the schema the server loads. Edit it to model
your signals, text fields, embedding slots, and (optionally) ranking profiles —
the format is documented in server-deployment.md.
The schema is read once at boot; roll the StatefulSet to apply changes.
4. Apply
kubectl apply -k k8s/
kubectl -n tidaldb rollout status statefulset/tidaldb --timeout=180s
5. Verify
kubectl -n tidaldb port-forward statefulset/tidaldb 9400:9400 &
KEY=$(kubectl -n tidaldb get secret tidaldb-api-key -o jsonpath='{.data.api-key}' | base64 -d)
curl -s localhost:9400/health # {"ok":true,...}
curl -s localhost:9400/openapi.json | jq .info # served API contract
curl -s -X POST localhost:9400/items \
-H "Authorization: Bearer $KEY" -H 'Content-Type: application/json' \
-d '{"entity_id":1,"metadata":{"title":"hello","category":"demo","created_at":"1700000000"}}'
curl -s -H "Authorization: Bearer $KEY" "localhost:9400/feed?profile=trending&limit=5"
How the health probes map
The server exposes three unauthenticated endpoints, wired to the three probe
types in statefulset.yaml:
| Probe | Endpoint | Behavior |
|---|---|---|
startupProbe |
GET /health/startup |
200 once the HTTP listener is up; high failureThreshold covers slow WAL replay / index load on large data dirs (see capacity-planning) |
livenessProbe |
GET /health/live |
200 while the process is alive; restart if it stops answering |
readinessProbe |
GET /health |
200 ready / 503 while draining — on SIGTERM the pod leaves the Service endpoints before it stops accepting |
Rolling updates and graceful shutdown
On kubectl rollout restart (or any pod delete), the kubelet sends SIGTERM. The
server flips readiness to 503 (so it leaves the Service), drains in-flight
requests, then checkpoints and fsyncs the WAL before exit.
terminationGracePeriodSeconds: 60 gives that room — raise it if your data dir
is large. Because there is one replica, a restart is a brief planned outage
while the new pod replays the WAL; the PodDisruptionBudget (maxUnavailable: 0) prevents an involuntary drain from taking the node down without operator
intent.
Persistence and backup
The volumeClaimTemplate provisions a PersistentVolumeClaim (/data, 10Gi by
default — size it from capacity-planning). The WAL
- checkpoints there are the source of truth and survive pod restarts. For backup and disaster recovery (snapshotting the PVC, restoring a corrupt data dir), see recovery.
Metrics
The pod exposes Prometheus metrics on :9091/metrics (unauthenticated — it is
not exposed by the headless Service externally; keep it cluster-internal). Scrape
it one of two ways:
- Prometheus Operator:
kubectl apply -f k8s/servicemonitor.yaml(requires themonitoring.coreos.comCRDs). - Plain Prometheus: the pod carries
prometheus.io/scrape,prometheus.io/port, andprometheus.io/pathannotations.
Alert rules and a dashboard ship in docs/ops/prometheus-alerts.yaml
and docs/ops/grafana-dashboard.json; see
monitoring.
Local walkthrough with kind
This is the exact flow used to verify the manifests end-to-end:
# 1. Create a local cluster.
kind create cluster --name tidaldb
# 2. Build the image and load it into the kind node (no registry needed).
docker build -f docker/deploy/Dockerfile -t tidaldb:deploy .
kind load docker-image tidaldb:deploy --name tidaldb
# 3. Namespace + API-key secret.
kubectl create namespace tidaldb
kubectl -n tidaldb create secret generic tidaldb-api-key \
--from-literal=api-key="$(openssl rand -hex 32)"
# 4. Apply and wait for ready.
kubectl apply -k k8s/
kubectl -n tidaldb rollout status statefulset/tidaldb --timeout=240s
# 5. Verify, then tear down.
kubectl -n tidaldb port-forward statefulset/tidaldb 9400:9400 &
curl -s localhost:9400/health
kind delete cluster --name tidaldb
The manifests set image: tidaldb:deploy with imagePullPolicy: IfNotPresent,
which is exactly what kind load + a local tag need. For a real cluster, swap in
your registry image.
kind create clusterfails with "could not find a log line that matches … Multi-User System"? On Docker Desktop the node'ssystemdcan die at boot withFailed to create control group inotify object: Too many open files(docker logs <cluster>-control-planeshows it). The Docker VM's inotify limits are too low; raise them in the VM kernel, then recreate:docker run --rm --privileged alpine sysctl -w fs.inotify.max_user_instances=8192 kind delete cluster --name tidaldb && kind create cluster --name tidaldbThis is a kind-on-Docker-Desktop prerequisite, unrelated to tidalDB.
Troubleshooting
| Symptom | Likely cause |
|---|---|
Pod Pending |
No default StorageClass, or the PVC can't bind — kubectl -n tidaldb describe pvc data-tidaldb-0 |
Pod CrashLoopBackOff at boot |
Bad schema YAML in the ConfigMap, or a data dir from an incompatible schema — check logs; see recovery § schema mismatch |
Pod never Ready, but Running |
Readiness probe failing — kubectl -n tidaldb logs statefulset/tidaldb; a large data dir may need a longer startupProbe |
401 Unauthorized on data routes |
Wrong/empty tidaldb-api-key secret; clients must send Authorization: Bearer <key> |
| Writes lost after restart | Data dir not on the PVC — confirm --data-dir /data and the data volume mount |
Cluster mode on Kubernetes
The cluster reference is k8s/cluster/: ONE StatefulSet
named tidaldb, replicas: 3, in its own namespace tidaldb-cluster. Each
pod is a region; the three pods (tidaldb-0/1/2) form the initial voter set.
This is real HA — automatic election/failover, quorum-acked writes, and
membership changes that ride the replicated log — but the mode is still
--experimental-cluster-gated (set via TIDAL_ALLOW_EXPERIMENTAL_CLUSTER=1 in
the manifest). It is mutually exclusive with the standalone set per namespace:
they share the StatefulSet name tidaldb, and the standalone set's replicas: 1
is load-bearing. Deploy one or the other.
Why one StatefulSet (not one per region)
Before m11p5, a pod bound its own grpc_addr literally, and a pod cannot bind a
Service ClusterIP — so each region needed a per-pod topology variant, defeating
the "every process parses the same file" contract. The m11p5 bind/advertise
split removes that: grpc_addr is the address peers dial (a per-pod headless
DNS name, re-resolved by tonic on every reconnect, so a rescheduled pod on a new
IP is reachable with no peer restart), while grpc_bind is the local socket
(0.0.0.0:9601). One topology ConfigMap names all three regions by their stable
pod DNS, and every pod mounts it unmodified.
What's in k8s/cluster/
| File | Purpose |
|---|---|
namespace.yaml |
The tidaldb-cluster namespace (mutually exclusive with tidaldb) |
topology-configmap.yaml |
The ONE bootstrap topology shared by all pods: 3 regions by per-pod DNS (grpc_addr advertised, grpc_bind 0.0.0.0), replication.ack: quorum, replication.reseed_self_restart: true, the election block |
schema-configmap.yaml |
The schema YAML every region loads (--schema) |
statefulset.yaml |
replicas: 3, podManagementPolicy: Parallel, TIDAL_REGION from POD_NAME, durable PVC at /data with --data-dir /data/db, the three probes (readiness now cluster-aware), uid 10001, terminationGracePeriodSeconds: 60, topology spread, and the ordinal-branching scale-up wrapper |
service-peers.yaml |
Headless peer Service (publishNotReadyAddresses: true) — stable per-pod DNS, keeps not-ready joiners resolvable for peers |
service-client.yaml |
Client Service — readiness-gated, drops not-ready/joining/quarantined pods from load balancing |
poddisruptionbudget.yaml |
maxUnavailable: 1 — a 3-voter cluster keeps quorum across one disruption |
secret.example.yaml |
Template for the tidaldb-credentials / TIDAL_API_KEY secret (create the real one out-of-band) |
kustomization.yaml |
Ties it together for kubectl apply -k k8s/cluster/ (secret excluded) |
The two Services
tidaldb-peers(headless,clusterIP: None,publishNotReadyAddresses: true): gives each pod the stable DNS nametidaldb-N.tidaldb-peers.tidaldb-cluster.svc.cluster.local, which the topology advertises.publishNotReadyAddresses: trueis load-bearing — a joiner is not ready until it first converges, but peers must still resolve it to feed it a snapshot + catch-up stream; without this the joiner could never reach a seed to become ready (a deadlock).tidaldb(client-facing, VIP, readiness-gated): the address in-cluster clients hit. Default readiness gating drops not-ready/joining/quarantined/ draining pods, so a client is never routed to a node that is still catching up.
The readiness predicate (cluster-aware /health)
The readinessProbe stays GET /health, but in cluster mode it is now
predicate-driven (m11p5 §4). /health returns 503 when the node is:
- shutting down (SIGTERM drain — leaves both Services before it stops accepting);
- quarantined (an m11p4 divergent leader-acked suffix — serves status and votes, refuses the data plane until reseeded);
- removed / decommissioned (a
Removedmembership record reached it, or a voter's typedremovedsignal told it so); - a joiner (seed-join learner) or install boot (snapshot-reseeded) that
has not yet first-converged — convergence means the boot catch-up pull
completed at least once AND lag fell to
≤ learner_promote_lag(hysteresis; neverlag == 0, which an open-loop write load keeps perpetually false). Sticky-ready after the first convergence.
A restarted, PVC-retained voter is Ready on today's terms — no regression for
ordinary pod restarts. GET /cluster/status/local surfaces the inputs
(lag_events, quarantined, role, term, reseed_required) for diagnosis,
plus the tidaldb_cluster_reseed_required and tidaldb_cluster_divergence
gauges.
Deploy the cluster
# 1. Build/publish an image whose runtime user is uid 10001 (matches the
# securityContext so the PVC is writable). One image serves every subcommand.
docker build -f docker/deploy/Dockerfile -t <registry>/tidaldb:<tag> .
docker push <registry>/tidaldb:<tag>
# Set image: in k8s/cluster/statefulset.yaml (pin by @sha256 in production).
# 2. Namespace + the credentials secret (stress/Ref-A shape: name
# tidaldb-credentials, key TIDAL_API_KEY). Same key on EVERY pod and client.
kubectl create namespace tidaldb-cluster
kubectl -n tidaldb-cluster create secret generic tidaldb-credentials \
--from-literal=TIDAL_API_KEY="$(openssl rand -hex 32)"
# 3. Apply and wait for the 3-pod voter set.
kubectl apply -k k8s/cluster/
kubectl -n tidaldb-cluster rollout status statefulset/tidaldb --timeout=300s
# 4. Confirm three reachable regions with low lag, and check each node's role.
kubectl -n tidaldb-cluster exec tidaldb-0 -- \
curl -s localhost:9500/cluster/status | jq '.regions[] | {name, lag_events, reachable}'
for p in tidaldb-0 tidaldb-1 tidaldb-2; do
kubectl -n tidaldb-cluster exec "$p" -- \
curl -s localhost:9500/cluster/status/local | jq '{role, term, membership_role, lag_events}'
done
Scale up (3 → N): seed-join as a learner, auto-promote
kubectl scale is the whole story — no topology edits. Pods with ordinal
≥ 3 boot with --seed (the StatefulSet's ordinal-branching wrapper adds it
automatically) and learn their roster/id/term from a seed, joining as a
learner. The leader auto-promotes a learner to a voter once its durable mark
is within learner_promote_lag of the leader's frontier (or stops falling behind
for K rounds under sustained load).
# Grow to 5 voters. Pods tidaldb-3 and tidaldb-4 seed-join + auto-promote.
kubectl -n tidaldb-cluster scale statefulset/tidaldb --replicas=5
kubectl -n tidaldb-cluster rollout status statefulset/tidaldb --timeout=600s
# Watch the new members converge and promote (promotion_pending shows the lag):
kubectl -n tidaldb-cluster exec tidaldb-0 -- \
curl -s localhost:9500/cluster/members | jq '.members[] | {id, name, role}'
A scaled pod still mounts the shared topology ConfigMap — a --seed boot
requires the local config for the behavioral knob blocks (replication,
wal, election, timeouts, grpc_tls); its regions: list is ignored for
the seed joiner's roster (the join response is authoritative).
Scale down (N → fewer): remove verb FIRST, then scale
Decommission a member before removing its pod, so the cluster stops counting it toward quorum cleanly. Remove the highest-ordinal members (StatefulSet deletes lowest-ordinal-last on scale-down).
# Going 5 -> 3: decommission tidaldb-4, then tidaldb-3, then scale.
# Remove verb: POST /cluster/members/remove {"region": "<name>"} (any node
# forwards to the leader; one-at-a-time, quorum-commit-gated).
kubectl -n tidaldb-cluster exec tidaldb-0 -- curl -s -X POST \
-H "Authorization: Bearer $KEY" -H 'Content-Type: application/json' \
-d '{"region":"tidaldb-4"}' localhost:9500/cluster/members/remove
kubectl -n tidaldb-cluster exec tidaldb-0 -- curl -s -X POST \
-H "Authorization: Bearer $KEY" -H 'Content-Type: application/json' \
-d '{"region":"tidaldb-3"}' localhost:9500/cluster/members/remove
# Each Remove is delivered to the removed peer (which flips to 503 and stops
# campaigning) before its ship cell retires. Only then is it safe to scale.
kubectl -n tidaldb-cluster scale statefulset/tidaldb --replicas=3
Removing pods without the remove verb leaves zombie members the cluster still expects — never scale down before decommissioning.
Node / pod replacement
kubectl delete pod tidaldb-N(PVC retained): the StatefulSet recreates the pod onto its existing PVC. It boots a follower, replays its WAL, and catches up via theStreamSegmentsstream (boot-time + the 30 s catch-up timer). No operator verb. This is the routine replace — already proven by the p4 leader-kill regression (lag → 0 within ~10 s).- PVC + pod delete (fresh reseed): delete the PVC and the pod. The new pod
comes up with an empty data dir, latches an install boot, and reseeds via
snapshot (
FetchSnapshot+ stream) from the leader, then rejoins clean. Use this when the data dir is corrupt or the node fell behind a compacted leader. Readiness stays 503 until the snapshot install first converges.
Self-healing reseed (quarantine / behind-compaction)
replication.reseed_self_restart: true (set in the topology ConfigMap) makes a
node that durably latches reseed_required (an m11p4 divergence quarantine, or a
typed snapshot-required refusal) drain and exit(0); the StatefulSet restarts it
and the boot-time install reseeds it via snapshot, clearing the quarantine
and the divergence gauge with no operator verb and no PVC wipe. The self-restart
is refused (loudly, in /cluster/status/local + the gauge) when the
remaining voters cannot sustain quorum without this node — exiting during a
2-voter window would be a total write outage. POST /cluster/reseed latches the
marker on demand.
PodDisruptionBudget and graceful shutdown
maxUnavailable: 1 lets a voluntary disruption (node drain, autoscaler, rolling
upgrade) take at most one pod at a time, preserving quorum (2 of 3). On SIGTERM a
pod flips readiness to 503 (leaving both Services), drains, lets the leader
lease/heartbeat windows lapse so a successor is elected cleanly, then checkpoints
- fsyncs the WAL;
terminationGracePeriodSeconds: 60covers the sequence.
The exit-gate harness
The in-cluster load Jobs in tidal-stress/k8s/ target
the cluster by per-pod DNS (tidaldb-N.tidaldb-peers.tidaldb-cluster.svc.cluster.local:9500),
in namespace tidaldb-cluster, reading the tidaldb-credentials secret. They
run the capacity ramp, the quorum-throughput gate (stress-job-t2a.yaml,
--ack quorum), and the leader-kill chaos drill (stress-job-t2b.yaml).
See also
- Server deployment guide — config, auth, the served OpenAPI spec
- Build a feed app — what to run against this server
- Cluster runbook — the multi-region mode's operational API (launch, promote, heal, reseed)
- Monitoring · Capacity planning · Recovery