Datadog Announces 2023 Report on Real-World Container Use, Reveals Rise in Serverless Containers

Rhea-AI Summary

Datadog's fifth annual report, 10 Insights on Real-World Container Use, reveals that 46% of container organizations now run serverless containers, up from 31% two years ago. The report also highlights the doubling adoption of Arm processor-based compute for containerized workloads, the challenge of sizing workloads with over 65% of Kubernetes workloads utilizing less than half of their requested CPU and memory, and the 58% year-over-year increase in usage of GPU-based compute on containerized workloads. The shift to serverless containers is driven by the desire to improve developer productivity and agility while reducing operational overhead and cloud costs.

Positive

• The adoption of Arm processor-based compute for containerized workloads has more than doubled over the past year.
• Usage of GPU-based compute on containerized workloads has increased 58% year-over-year.

Negative

• Sizing workloads remains a challenge for organizations as more than 65% of Kubernetes workloads are utilizing less than half of their requested CPU and memory.

46% of container organizations now run serverless containers, up from 31% two years ago

NEW YORK, Nov. 2, 2023 /PRNewswire/ -- Datadog, Inc. (NASDAQ: DDOG), the monitoring and security platform for cloud applications, today unveiled the findings of its fifth annual report, 10 Insights on Real-World Container Use. To understand the state of the container ecosystem, Datadog examined data from more than 2.4 billion containers run by tens of thousands of customers.

Datadog's report found that serverless containers continue to rise in popularity—46% of container organizations now run serverless containers, up from 31% two years ago—as teams look to improve developer productivity.

Other key findings from the report include:

• The adoption of Arm processor-based compute for containerized workloads has more than doubled over the past year.
• Sizing workloads remains a challenge for organizations as more than 65% of Kubernetes workloads are utilizing less than half of their requested CPU and memory.
• Usage of GPU-based compute on containerized workloads—which is used to efficiently train machine learnings and large language models (LLMs), perform inferences and process large datasets— has increased 58% year-over-year.

"We are continuing to see organizations move to serverless containers for the benefits of improving productivity and agility while reducing operational overhead and cloud costs," said Yrieix Garnier, VP of Product at Datadog. "With the serverless approach, organizations don't have to provision or manage the infrastructure needed to run, maintain and scale the containers. This strategy also comes with cost benefits as cloud providers manage the serverless containers and therefore can optimize resource utilization and cloud spend."

10 Insights on Real-World Container Use is available now. For the full results, please visit: https://www.datadoghq.com/container-report/. To learn how Datadog helps companies monitor and secure their containerized environments, visit: https://www.datadoghq.com/product/container-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, real-user monitoring, 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 May 5, 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
Janine Kromhout
press@datadoghq.com

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SOURCE Datadog, Inc.

FAQ

What is the key finding of Datadog's report on container use?

The key finding is that 46% of container organizations now run serverless containers, up from 31% two years ago.

What is the adoption rate of Arm processor-based compute for containerized workloads?

The adoption of Arm processor-based compute for containerized workloads has more than doubled over the past year.

What is the increase in usage of GPU-based compute on containerized workloads?

The usage of GPU-based compute on containerized workloads has increased 58% year-over-year.

What is the challenge faced by organizations in sizing workloads?

The challenge is that more than 65% of Kubernetes workloads are utilizing less than half of their requested CPU and memory.

Why are organizations shifting to serverless containers?

Organizations are shifting to serverless containers to improve developer productivity and agility while reducing operational overhead and cloud costs.