Deploy previews for data pipelines, so reviewers see the diff in the data
If your reliability problem is in the data pipeline rather than the service.
Observability a two-person team can afford to run and actually understand
Overcast is metrics, logs and traces for small teams, priced and designed for engineers who are also the on-call rotation. One binary, one Postgres database, and alert rules you can read out loud. No sampling surprises, no per-host pricing, no bill that outgrows your infrastructure.
Metrics, logs and traces from a single process backed by Postgres and S3-compatible storage.
Rules are written the way you would say them, and they diff cleanly in code review.
Overcast never quietly drops data. Budget overruns are loud and configurable.
Standard OTLP ingest. Your instrumentation is portable on day one and on the day you leave.
Jump from an alert to the trace to the exact log line without changing tools.
The open-source build is the production build. No feature-gated community edition.
Observability vendors design for a buyer who has a platform team. If that is not you, you get one of two outcomes: a free tier that expires exactly when it becomes useful, or a bill that dwarfs the infrastructure it is watching.
Overcast is built for the middle.
error rate above 2% for 5 minutes is the actual rule syntax.Overcast runs as a single binary against Postgres and object storage. That is a deliberate ceiling: it will not scale to a hundred terabytes a day, and it is not trying to. In exchange, one person can operate it, upgrade it, and reason about it during an incident.
If you outgrow it, the data is in open formats and the exporters are OpenTelemetry-standard. Leaving is a migration, not a hostage negotiation.
Overcast does not silently sample. If you exceed your ingest budget it tells you and drops from the lowest-priority stream you configured. The failure mode of "your traces are incomplete and nobody told you" is worse than the failure mode of a loud warning.
Apache 2.0. Hosted plans start at $29/month.
Free
$29/month
$99/month
Metrics now carry trace exemplars, so a spike on a latency graph is one click from the slow trace that caused it.
Retention drops are now partition-level rather than row-level deletes. Retention enforcement went from minutes to milliseconds.
Yes, Apache 2.0, and the self-hosted build is the same artefact we run in our hosted product. There is no separate enterprise binary with the useful features in it.
Hosted plans are priced on ingested gigabytes per month, starting at $29. There is no per-host, per-container, per-seat or per-custom-metric charge, which is where observability bills usually detonate.
Comfortably into the low terabytes per day on a single node. Past that you should be looking at a purpose-built columnar backend, and we will tell you so rather than sell you an upgrade.
Ingest is standard OTLP and stored data exports to Parquet. Both directions are documented, because a tool you cannot leave is a tool you should not adopt.
It can, but most teams start by pointing a single service at it and running side by side for a few weeks. The OTLP endpoint makes that a config change rather than a rewrite.
Similar products worth comparing before you commit.
Deploy previews for data pipelines, so reviewers see the diff in the data
If your reliability problem is in the data pipeline rather than the service.
A local-first sync engine you can drop into an app you already shipped
Different layer, similar self-hostable philosophy.
Ranked by shared categories, tags and explicit alternative relationships.
A local-first sync engine you can drop into an app you already shipped
Deploy previews for data pipelines, so reviewers see the diff in the data
Revenue analytics that tells you what changed instead of showing forty charts