Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Datadog Introduces Cloud Cost Management

Datadog, Inc., the monitoring and security platform for cloud applications, announced the general availability of Cloud Cost Management, which shows an organization’s cloud spend in the context of their observability data. This allows engineering and FinOps teams to automatically attribute spend to applications, services and teams, track any changes in spend, understand why those changes occurred and include costs as a key performance indicator of application health.

As organizations continue to migrate their workloads to the cloud, controlling cloud spend has become increasingly important. However, reconciling what resources an application is using with the cost of those resources has required substantial manual work to correlate data across multiple point solutions. As a result, Gartner planning assumptions estimate that by 2024 60% of infrastructure and operations leaders will encounter public cloud cost overruns.

Recommended AI: Eric Tippetts Announces Version 3.0 of Innovative Network Marketing App

Cloud Cost Management addresses this challenge by unifying observability and cloud data to provide finance, FinOps and operations teams with detailed cloud spend reports. Teams now have the ability to drill down and investigate changes in cloud spend by cost center, application, service and resource. And as Cloud Cost Management is part of the Datadog platform, engineers can do this as part of their existing workflows, bringing an additional level of cost awareness to their work.

“Best practices are important, but there is no substitution for real measurement and cost optimization. Datadog Cloud Cost Management helped us attribute spend at a granular level over dozens of accounts to achieve significant savings. It also enabled us to bring cost data adjacent to operational metrics in a familiar environment for our engineering teams to monitor cost as part of overall service health,” said Martin Amps, Principal Engineer at Stitch Fix.

Related Posts
1 of 40,842

Recommended AI: Instagram Subscriptions: How Exclusivity on Instagram Could Reshape Influencer Marketing

“As the shift to the cloud accelerates so does the need for organizations to rightsize their cloud spend,” said Yrieix Garnier, VP of Product at Datadog. “Datadog Cloud Cost Management helps organizations do this by improving cost visibility across organizations so engineering, FinOps and finance teams can work together to make better business decisions about their cloud usage.”

Cloud Cost Management helps teams:

  • See cloud costs directly in engineers’ existing workflows: Engineers can view cloud costs in their existing workflows to understand how they are driving cloud costs across their organization.
  • Understand cost changes: Use observability data—CPU and memory utilization alongside instance costs or the number of reads and writes to S3 buckets along with their associated sizes and costs, for example—to automatically surface cost changes and help teams understand why changes have occurred.
  • Take ownership of costs: Use flexible, out-of-the-box dashboards and powerful data visualization to make cost data an easy-to-understand metric for engineering teams as they monitor the health and performance of their services.

Recommended AI: “Bitcoin Has No Intrinsic Value”. Then What Gives Bitcoin Value?

[To share your insights with us, please write to sghosh@martechseries.com]

Comments are closed.