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- Outdated Technologies Are Widely Used: AWS's current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
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SOURCE Datadog, Inc.