Operations overview

The framework runs the same code in dev and prod, but production deployment has its own set of considerations that don’t matter on a laptop:

Topic	Concerns
Deployment	How does a node start, register with the cluster, accept traffic, and shut down cleanly?
Tuning	Gossip cadence, mailbox sizes, failure-detector thresholds — defaults are sensible, but workloads vary.
Security	TLS on the cluster transport, secret management, key rotation.
Upgrades	Schema migrations, rolling deployments without downtime.
Troubleshooting	What logs, metrics, and traces tell you about a misbehaving system.

This section maps each to a deeper page.

A production-ready setup checklist

For a non-trivial actor system going to production:

□ Persistence backend chosen + production-grade
   (e.g. SQLite for single-node, Cassandra for multi-node)
□ Cluster wired up (if multi-node) with concrete seed strategy
□ Downing strategy configured (split-brain protection)
□ Coordinated shutdown configured with SIGTERM hooks
□ Health checks exposed via HttpManagement
□ Metrics exposed via Prometheus or OTel
□ Log aggregation hooked up (structured logging via withFields/MDC)
□ TLS enabled on the cluster transport
□ Secrets via env vars, NOT in application.conf
□ Kubernetes manifests with PreStop hook + grace period
□ Tracing optional but configured if multi-actor flows exist
□ Runbook for "actor X keeps crashing" / "cluster won't form"

None of these are framework-specific tricks — they’re general production hygiene applied to an actor system. Each is covered in its own page.

Deployment

How	When
Kubernetes	Cloud + container orchestration. StatefulSets, headless services, RBAC for the K8s API seed provider.
Docker Compose	Local multi-node clusters for testing and small deployments.
Process manager	systemd / PM2 — for bare-metal or VM deployments.

K8s is the most common production path; the page covers Deployment vs StatefulSet, PreStop hooks, and the seed-provider configuration.

Tuning

Defaults work for most workloads — reach for these pages when you see specific symptoms:

Knob	When to tune
Gossip cadence	Large clusters (>20 nodes) where the default 1-second gossip is wasteful, or small clusters where you want faster convergence.
Failure detector	Tight networks (LAN) where 2-second unreachable detection is too slow, or noisy networks where it triggers false alarms.
Mailbox sizing	When you see memory growth from unbounded mailboxes, or when bounded mailboxes are dropping more than expected.
Dispatcher tuning	When you observe HTTP latency degradation under actor-heavy load, or low CPU utilization with high actor throughput.

If you can’t articulate the symptom, don’t tune. Defaults aren’t optimal but they’re rarely bad.

Security

Three layers:

Concern	Page
Cluster transport TLS + auth	Cluster security
Encryption at rest for persisted data	Master key rotation
TLS everywhere (HTTP, brokers, journals)	TLS everywhere

The cluster transport defaults to unauthenticated TCP — fine inside a private network, dangerous on the public internet. Always enable TLS + shared-secret auth for any cluster that crosses untrusted boundaries.

Upgrades

The framework supports rolling deployments without downtime when configured for it. Two distinct concerns:

• Code rollouts — replacing node binaries while the cluster stays up. Handled by K8s rolling updates + coordinated shutdown. See Rolling migration.
• Schema migrations — evolving event/state shapes over time. Handled by event adapters + envelope versioning. See Upgrade strategies and Persistence migration overview.

The rolling-migration page is the most practical — a step-by-step recipe for “I need to add a field to my event without taking the cluster down.”

Troubleshooting

Symptom                            → Likely cause
─────────────────────────────────────────────────────────
Actor isn't receiving messages     → Stopped ref, dead-letter, mailbox full
Cluster won't form                 → Seed nodes unreachable, port conflict
Sharded entities won't spawn       → Coordinator not on a leader, role mismatch
PersistentActor takes 30s to start → No snapshot, deep journal — set snapshotPolicy
Tests hang at the end              → Forgot await system.terminate()
Memory grows unboundedly           → Unbounded mailboxes; pick a mailbox cap

See Troubleshooting for the diagnostic-by-symptom catalog.

When things go wrong

The first place to look is logs

Every supervisor decision, every cluster event, every dead-letter is logged. With LogContext MDC (correlation IDs propagating across tell), a multi-actor request trail stitches together in one log query. Configure structured logging from day one — see Logging.

The second place is metrics

Stock metrics give you actor message-rate, mailbox depth, cluster member count, sharding region count — enough to identify “something is off” before users notice. Wire a Prometheus exporter in production. See Stock metrics.

The third place is traces

Spans propagate across tell and across cluster nodes. Single request, end-to-end view — much faster to diagnose than tailing logs. Enable selectively when you have multi-actor flows.

Where to next

Deployment

• Kubernetes
• Docker Compose
• Process manager

Tuning

• Gossip cadence
• Failure detector
• Mailbox sizing
• Dispatcher tuning

Security

• Cluster security
• Master key rotation
• TLS everywhere

Upgrades

• Rolling migration
• Upgrade strategies

Diagnostics

• Troubleshooting