What is Axiom?
Axiom is a managed data platform for collecting, storing and querying timestamped events and telemetry. Its platform overview describes separate event and metrics stores behind a shared console. Logs, traces and metrics can feed investigations, dashboards and monitors.
Core concepts
- Datasets organize ingested data. Event datasets hold logs and traces; metrics use their own dataset type.
- Query languages include Axiom Processing Language (APL) for events and Metrics Processing Language (MPL) for metrics. The console also provides a query builder.
- OpenTelemetry ingestion accepts logs, traces and metrics over OTLP/HTTP. A dataset and an API token with ingestion permissions are required, with a dedicated dataset for each signal type.
- Dashboards and monitors turn queries into shared views and alerts.
The OpenTelemetry guide includes Collector configuration and explains the signal-specific endpoints and headers. Check those details against the edge deployment used by your organization.
Getting started
Follow the quickstart, create a dataset and send a small representative event stream. Explore the same data through the query builder and APL. For an existing instrumented application, test an OpenTelemetry Collector pipeline before expanding collection.
Common use cases
Axiom can support application log investigations, distributed tracing and metrics exploration. Its documentation also covers Kubernetes, Grafana, Cloudflare and cloud-service integrations.
Initial assessment
Explore, with gut confidence based on public documentation. The documented OTLP ingestion and shared query workflow make it worth evaluating for teams consolidating telemetry. A useful trial would check signal coverage, query ergonomics, retention and data location, access control, and cost against a representative workload.
