Operations

SLA

The Service Level Agreement (SLA) depends on how the Platform Operator manages node pools.

The availability of the online Datalayer services can be viewed on this Status page.

The availability depends on how the Platform Operator manages node pools.

The Platform Operator is responsible to provision the hardware resources (CPU/GPU and memory) to serve new Runtimes.

The response time of Datalayer services needs to be monitored to ensure they respond fast enough.

Any significant slowdown or unexpected behavior can be reported to Datalayer.

We offer professional support agreements with different SLA options for issue handling. Contact us to learn more.

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Datalayer observability operations are centered on the OTEL service.

The platform operator provisions the Kubernetes cluster with the Jupyter Contents, Environments and Pools.

To create new Runtimes, the Datalayer services must be up-and-running.

Disaster Recovery

Plan upgrades as controlled, staged rollouts.

The technical components we use, and the way we configure them, are secure by default.