See whether the process is alive
Use /ping and runtime statistics for basic
monitoring and operational inspection.
Deployment and operations
Run the backend without assembling an ops toolkit first.
Deploy one application server with database pooling, caching, traffic controls, health and statistics endpoints, logs, and record history already present.
- Native or container
- Three databases
- Runtime visibility
Operational from the start
Useful controls before the first incident.
Run the latest binary or container with SQLite, MySQL, or PostgreSQL. Configure the infrastructure to fit the stage of the product instead of rewriting the application layer as it grows.
Bound database pressure
Connection-pool settings control open and idle connections rather than allowing unbounded database use.
Control abusive traffic
IP-and-path rate limits and concurrent-request bounds protect shared resources before application handlers do work.
Share state when you scale out
Olric can provide distributed cache, PubSub, and shared rate counters across Daptin instances.
Inspect what happened
Logs, runtime counters, pool information, and record-level change history give operators evidence to work from.
Cache
Response caching, validators, and invalidation paths reduce repeated work while keeping changed data visible.
Deployment choices
Start small without hiding the path to scale.
Single-node products
Use the latest native artifact or container with SQLite when simple operation matters more than horizontal scale.
Managed databases
Move durable relational state to MySQL or PostgreSQL while keeping the same application model.
Several instances
Configure shared durable storage and distributed coordination before placing instances behind a load balancer.
Existing platforms
Adapt the maintained Compose and Kubernetes examples to your network, secret, persistence, and observability standards.
Operational truth
Know what each signal proves.
/ping is the lightweight process-liveness signal. The
/health path serves an administrative application and
should not be described as a readiness probe. Runtime statistics
help inspection, but deployment-level readiness must reflect the
dependencies your product actually requires.
Daptin does not set every HTTP header, body, read, write, or idle limits in the latest release. Enforce those at a trusted reverse proxy, then size Daptin concurrency, rate, pool, and cache settings for real traffic. Repository examples are not production guarantees for every environment.