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Datadog Announces New Cloud Cost Management Capabilities

Datadog announced new capabilities for its Cloud Cost Management product, including container cost allocation, cost monitors and support for Microsoft Azure.

Cloud Cost Management shows an organization's granular cost data, scoped to specific services, so that engineers can optimize cloud spend and performance.

"As organizations increase their usage of containers and multiple clouds, the ability to centralize cost data and allocate spend across different dimensions becomes even more important," said Kayla Taylor, Senior Product Manager, Cloud Cost Management at Datadog. "Datadog Cloud Cost Management gives engineers visibility into spend and helps create a cost-conscious culture so they can take action on cost insights. With granular alerting and visibility into containers and Azure environments, Datadog Cloud Cost Management provides the relevant observability and cost data that engineers need, in the platform they already use everyday, to empower them to reduce waste and avoid unexpected cost overages."

Datadog's new capabilities for Cloud Cost Management help organizations:

- Understand Container Costs: With a quick and easy setup process, container cost allocation gives FinOps and engineering teams full visibility into spend, so organizations understand why and when container costs change and can detect idle costs.

- Respond to Cost Changes: Customizable and granular cost monitors help service owners rapidly respond to unexpected cost changes alongside application performance data. Alerts are tailored to specific services so engineers can quickly pivot from detecting a cost overrun to identifying ways to take action in a single pane of glass.

- Allocate Spend Across Azure and AWS: With support for Azure in addition to AWS, organizations can now seamlessly understand the teams, services and environments responsible for their highest cloud costs. Teams using Microsoft Azure can optimize for performance and cost, with full visibility into infrastructure and application telemetry.

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Datadog Announces New Cloud Cost Management Capabilities

Datadog announced new capabilities for its Cloud Cost Management product, including container cost allocation, cost monitors and support for Microsoft Azure.

Cloud Cost Management shows an organization's granular cost data, scoped to specific services, so that engineers can optimize cloud spend and performance.

"As organizations increase their usage of containers and multiple clouds, the ability to centralize cost data and allocate spend across different dimensions becomes even more important," said Kayla Taylor, Senior Product Manager, Cloud Cost Management at Datadog. "Datadog Cloud Cost Management gives engineers visibility into spend and helps create a cost-conscious culture so they can take action on cost insights. With granular alerting and visibility into containers and Azure environments, Datadog Cloud Cost Management provides the relevant observability and cost data that engineers need, in the platform they already use everyday, to empower them to reduce waste and avoid unexpected cost overages."

Datadog's new capabilities for Cloud Cost Management help organizations:

- Understand Container Costs: With a quick and easy setup process, container cost allocation gives FinOps and engineering teams full visibility into spend, so organizations understand why and when container costs change and can detect idle costs.

- Respond to Cost Changes: Customizable and granular cost monitors help service owners rapidly respond to unexpected cost changes alongside application performance data. Alerts are tailored to specific services so engineers can quickly pivot from detecting a cost overrun to identifying ways to take action in a single pane of glass.

- Allocate Spend Across Azure and AWS: With support for Azure in addition to AWS, organizations can now seamlessly understand the teams, services and environments responsible for their highest cloud costs. Teams using Microsoft Azure can optimize for performance and cost, with full visibility into infrastructure and application telemetry.

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For many B2B and B2C enterprise brands, technology isn't a core strength. Relying on overly complex architectures (like those that follow a pure MACH doctrine) has been flagged by industry leaders as a source of operational slowdown, creating bottlenecks that limit agility in volatile market conditions ...

FinOps champions crucial cross-departmental collaboration, uniting business, finance, technology and engineering leaders to demystify cloud expenses. Yet, too often, critical cost issues are softened into mere "recommendations" or "insights" — easy to ignore. But what if we adopted security's battle-tested strategy and reframed these as the urgent risks they truly are, demanding immediate action? ...

Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...

While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...

A perfect storm is brewing in cybersecurity — certificate lifespans shrinking to just 47 days while quantum computing threatens today's encryption. Organizations must embrace ephemeral trust and crypto-agility to survive this dual challenge ...

In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability... 

While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...