Datadog Jobs Monitoring

by Datadog

Spark & Databricks job optimization

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Centralize data workloads in a single place

Datadog Jobs Monitoring (DJM) helps data platform teams and data engineers detect problematic Spark and Databricks jobs anywhere in their data pipelines, remediate failed and long-running jobs faster, and proactively optimize overprovisioned compute resources to reduce costs. Unlike traditional infrastructure monitoring tools, native interfaces, and log analysis, DJM is the only solution that enables teams to drill down into job execution traces at the Spark stage and task level to quickly resolve issues and seamlessly correlate their job telemetry to their cloud infrastructure—in context with the rest of their data stack.

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Top Features

  • Detect problematic jobs

    Detect job failures and latency spikes anywhere in your data pipelines.

  • Resolve failures & latency

    Pinpoint and resolve failed and long-running jobs faster.

  • Cost-optimize clusters & jobs

    Reduce costs by optimizing misallocated clusters and inefficient jobs.

  • Centralize data pipeline visibility

    Centralize data pipeline visibility with the rest of your cloud infrastructure.

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Datadog Jobs Monitoring - Datadog Overview

Datadog offers a single unified platform to monitor your infrastructure, applications, networks, security threats, UX, and more.

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