Built by the co-creators of OpenLineage and Marquez
Observability re-invented for Spark & Iceberg.
Skip the dashboards. We build a reusable telemetry context layer where the Data Reliability Engineer and agents can solve data incidents together on day one
Quick, smart alerting with incidence triage.
Reduce on-call burden. Every alert is paired with a detailed knowledge graph of your data infrastructure so you understand how everything fits together. A shared context with your team to solve incidents faster.
- Anomaly investigation starts the moment alerts are fired. Pulls deep context from your telemetry lake to pinpoint and assist with the root cause before downstream impacts.Incidents/ spark job rows written dropped 15xInvestigations/ #3812:45AM
- Scanning run-level lineage
- Scanning run-level lineage
Works where you already deploy Spark
With OpenTelemetry (OTel) capture execution traces for your Spark jobs, using OpenLineage (OLin) to map your high-level data flow context. Works with any Spark deployment and is fully open source. No context switching, no new interfaces to learn.
PLATFORM | STATUS |
|---|---|
Databricks | Supported |
Amazon EMR | Supported |
Amazon SageMaker AI | Supported |
AWS Glue | Supported |
Google Cloud Dataproc | Supported |
Jupyter Notebook | Supported |
MLflow | Coming soon |
Work with any platform
Databricks and Amazon EMR are supported today. Built on open standards, so integration keeps pace with your continuously evolving data stack.
The context graph for your data infrastructure.
Every run, commit, deployment and dataset is connected. Search it. Trace it. Understand it. Share it.
Run Spark with context
Build. Deploy. Debug. Let us deploy your Spark jobs and handle production monitoring, running investigations as soon as things go wrong. So you don't have to.
Setup the CLI
One command to set up oleander CLI in your repository. No servers to manage. We deploy your Spark jobs and handle scaling for you.
Integrations
Production intelligence, built on open standards. No vendor lock-in.
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