Datadog's State of Cloud Costs 2024 Report Finds Spending on GPU Instances Growing 40% as Organizations Experiment with AI

Rhea-AI Summary

Datadog's State of Cloud Costs 2024 report reveals a 40% increase in spending on GPU instances as organizations explore AI and large language models (LLMs). GPUs, over 200% faster than CPUs, are critical for these AI workloads. Despite increased spending on cloud compute, 83% of container costs are wasted due to idle resources. Moreover, 83% of organizations still use outdated technologies, spending 17% of their EC2 budgets on them. Only 67% are utilizing cloud service discounts, down from 72% last year. Conversely, green technology adoption is up, with Arm-based instances now accounting for 18% of EC2 budgets, offering better performance and lower energy consumption.

Positive

• GPU spend increased by 40%, indicating strong investment in AI and LLMs.
• GPUs are over 200% faster than CPUs for parallel processing, benefiting AI workloads.
• Arm-based instances spend doubled to 18% of EC2 budgets, highlighting a shift towards green technology.
• Arm-based instances use up to 60% less energy, offering better performance at a lower cost.

Negative

• 83% of container costs are wasted due to idle resources.
• 17% of EC2 budgets are spent on outdated technologies, which are less cost-effective.
• Participation in cloud service discounts dropped to 67%, down from 72% last year.
• 54% of wasted container spend is due to overprovisioning cluster infrastructure.

GPUs can be more than 200% faster than CPUs when parallel processing

NEW YORK, June 13, 2024 /PRNewswire/ -- Datadog, Inc. (NASDAQ: DDOG), the monitoring and security platform for cloud applications, today announced its new report, the State of Cloud Costs 2024. The report found organizations that use graphics processing unit (GPU) instances have increased their average spending on those instances by 40% in the last year. This growth in spend on GPU instances comes as more companies are experimenting with AI and large language models (LLMs). GPUs' capacity for parallel processing makes them critical for training LLMs and executing other AI workloads, where they can be more than 200% faster than CPUs.

"Today, the most widely used type of GPU-based instance is also the least expensive. This suggests that many customers are still in the experimentation phase with AI and applying the GPU instance to their early efforts in adaptive AI, machine learning inference and small-scale training," said Yrieix Garnier, VP of Product at Datadog. "We expect that as organizations expand their AI activities and move them into production, they will be spending a larger proportion of their cloud compute budget as they use more expensive types of GPU-based instances."

In addition to more companies spending compute on AI projects, the report found that containers were a common theme of wasted spend among organizations. In fact, 83% of container costs were associated with idle resources. About 54% of this wasted spend was on cluster idle, which is the cost of overprovisioning cluster infrastructure, while 29% was associated with workload idle, which comes from resource requests that are larger than their workloads require. This wasted spend comes as organizations allocate more of their EC2 compute to running containers, up to 35% compared to 30% a year ago.

Other key findings from the report include:

• Outdated Technologies Are Widely Used: AWS's current infrastructure offerings commonly both outperform their previous-generation versions and cost less, but 83% of organizations still spend an average of 17% of their EC2 budgets on previous-generation technologies.
• Fewer Organizations Are Taking Advantage of Discounts: Cloud service providers offer commitment-based discounts on many of their services—for example, AWS has discount programs for Amazon EC2, Amazon RDS, Amazon SageMaker and others—but only 67% of organizations are participating in these discounts, down from 72% last year.
• Green Technology Is on the Rise for Better Performance and Cost: On average, organizations that use Arm-based instances spend 18% of their EC2 compute budget on them—twice as much as they did a year ago. Instance types based on the Arm processor use up to 60% less energy than similar EC2s and often provide better performance at a lower cost.

For the report, Datadog analyzed AWS cloud cost data from hundreds of organizations and explored how their use of emerging and previous-generation technologies, patterns of cloud resource usage, and participation in AWS discount programs all contributed to their cloud costs.

Datadog's State of Cloud Costs 2024 is available now. For the full results, please visit: https://www.datadoghq.com/state-of-cloud-costs/. To learn how Datadog helps companies optimize their cloud costs, visit: https://www.datadoghq.com/product/cloud-cost-management/.

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

View original content to download multimedia:https://www.prnewswire.com/news-releases/datadogs-state-of-cloud-costs-2024-report-finds-spending-on-gpu-instances-growing-40-as-organizations-experiment-with-ai-302172281.html

SOURCE Datadog, Inc.

FAQ

What did Datadog's State of Cloud Costs 2024 report find about GPU spending?

The report found that organizations increased their spending on GPU instances by 40% as they experiment with AI and large language models.

Why are GPUs important for AI and LLM workloads according to Datadog's report?

GPUs are critical for AI and LLM workloads because they can be over 200% faster than CPUs in parallel processing.

What percentage of container costs are wasted according to Datadog's report?

83% of container costs are wasted, mainly due to idle resources and overprovisioning.

How much of EC2 budgets are spent on outdated technologies?

On average, 17% of EC2 budgets are spent on outdated technologies.

What is the trend in cloud service discount participation?

Participation in cloud service discounts has decreased to 67%, down from 72% last year.

What does the report say about the use of Arm-based instances?

The use of Arm-based instances has doubled, now accounting for 18% of EC2 budgets, offering better performance and up to 60% energy savings.