Data Jobs Monitoring detects and helps resolve
job failures and latency spikes across data pipelines
NEW
YORK, June 20, 2024 /PRNewswire/ -- Datadog,
Inc. (NASDAQ: DDOG), the monitoring and security platform for
cloud applications, today announced the general availability of
Data Jobs Monitoring, a new product that 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 optimize overprovisioned compute
resources to reduce costs.
Data Jobs Monitoring immediately surfaces specific jobs that
need optimization and reliability improvements while enabling teams
to drill down into job execution traces so that they can correlate
their job telemetry to their cloud infrastructure for fast
debugging.
"Data Jobs Monitoring enables my organization to centralize our
data workloads in a single place—with the rest of our applications
and infrastructure—which has dramatically improved our confidence
in the platform we are scaling," said Matt
Camilli, Head of Engineering at Rhythm Energy. "As a result,
my team is able to resolve our Databricks job failures 20% faster
because of how easy it is to set up real-time alerting and find the
root cause of the failing job."
"When data pipelines fail, data quality is impacted, which can
hurt stakeholder trust and slow down decision making. Long-running
jobs can lead to spikes in cost, making it critical for teams to
understand how to provision the optimal resources," said
Michael Whetten, VP of Product at
Datadog. "Data Jobs Monitoring helps teams do just that by giving
data platform engineers full visibility into their largest, most
expensive jobs to help them improve data quality, optimize their
pipelines and prioritize cost savings."
Data Jobs Monitoring helps teams to:
- Detect job failures and latency spikes: Out-of-the-box
alerts immediately notify teams when jobs have failed or are
running beyond automatically detected baselines so that they can be
addressed before there are negative impacts to the end user
experience. Recommended filters surface the most important issues
that are impacting job and cluster health, so that they can be
prioritized.
- Pinpoint and resolve erroneous jobs faster: Detailed
trace views show teams exactly where a job failed in its execution
flow so they have the full context for faster troubleshooting.
Multiple job runs can be compared to one another to expedite root
cause analysis and identify trends and changes in run duration,
Spark performance metrics, cluster utilization and
configuration.
- Identify opportunities for cost savings: Resource
utilization and Spark application metrics help teams identify ways
to lower compute costs for overprovisioned clusters and optimize
inefficient job runs.
Data Jobs Monitoring is now generally available. To learn more,
please visit:
https://datadoghq.com/product/data-jobs-monitoring/.
About Datadog
Datadog is the observability and security platform for
cloud applications. Our SaaS platform integrates and automates
infrastructure monitoring, application performance monitoring, log
management, user experience monitoring, cloud security and many
other capabilities to provide unified, real-time observability and
security for our customers' entire technology stack. Datadog is
used by organizations of all sizes and across a wide range of
industries to enable digital transformation and cloud migration,
drive collaboration among development, operations, security and
business teams, accelerate time to market for applications, reduce
time to problem resolution, secure applications and infrastructure,
understand user behavior and track key business metrics.
Forward-Looking Statements
This press release may include certain "forward-looking
statements" within the meaning of Section 27A of the Securities Act
of 1933, as amended, or the Securities Act, and Section 21E of the
Securities Exchange Act of 1934, as amended including statements on
the benefits of new products and features. These forward-looking
statements reflect our current views about our plans, intentions,
expectations, strategies and prospects, which are based on the
information currently available to us and on assumptions we have
made. Actual results may differ materially from those described in
the forward-looking statements and are subject to a variety of
assumptions, uncertainties, risks and factors that are beyond our
control, including those risks detailed under the caption "Risk
Factors" and elsewhere in our Securities and Exchange Commission
filings and reports, including the Quarterly Report on Form 10-Q
filed with the Securities and Exchange Commission on November 7, 2023, as well as future filings and
reports by us. Except as required by law, we undertake no duty or
obligation to update any forward-looking statements contained in
this release as a result of new information, future events, changes
in expectations or otherwise.
Contact
Dan
Haggerty
press@datadoghq.com
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SOURCE Datadog, Inc.