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Datadog and Google Cloud Extend Partnership

Datadog announced an extension of a strategic partnership with Google Cloud.

Under this partnership, Datadog and Google will grow a relationship that began in 2019 with Datadog’s first European Google Cloud data center to now include new regions, making it even easier for organizations to access and implement Datadog’s monitoring and security platform.

New benefits for Datadog and Google Cloud customers will include:

- Additional Datadog points of presence in Google Cloud regions

- Extended go-to-market collaboration and deeper sales alignment with Google Cloud and Datadog sales teams

- Access to Datadog’s 400+ integrations on Google Cloud’s scalable and secure infrastructure through a single-click deployment on the Google Cloud Marketplace, with consolidated billing that will allow customers to draw down on their Google Cloud committed spend

- Continued investment into product co-innovation with more native joint solutions around Anthos, Open Telemetry and the Google Cloud operations suite.

“Datadog’s monitoring and security platform is critical to organizations as they undergo digital transformation projects, manage cloud migrations, and build new customer-facing applications,” said Amit Agarwal, Chief Product Officer, Datadog. “Extending our partnership with Google Cloud will bring true observability to more customers as they take on these challenging initiatives and use Google Cloud’s cutting edge services to modernize their businesses.”

“Organizations need to be able to leverage monitoring data to optimize their applications in the cloud, and we’re pleased to partner with Datadog to help them do so,” said Kevin Ichhpurani, Corporate VP, Global Ecosystem at Google Cloud. “Datadog provides important capabilities in performance monitoring across on-premises, hybrid, and public cloud infrastructure. By expanding the availability of these capabilities on Google Cloud, we can jointly help customers optimize their most critical workloads for Google Cloud.”

Datadog’s platform brings together infrastructure monitoring, application performance monitoring and log management to provide unified, real-time observability of the business-critical applications that enterprises run in the cloud. Datadog’s existing support for Google Cloud includes easy-to-install integrations, the ability to deploy the Datadog Agent directly on hosts and compute instances to collect metrics with greater granularity, and out-of-the-box integration dashboards providing a high-level view into each and every Google Cloud service.

These capabilities complement Google Cloud’s expertise in artificial intelligence, machine learning, data analytics and more, providing Datadog and Google Cloud customers with observability into the performance of their most critical applications and services.

With this strategic partnership, Datadog and Google Cloud will work together on new go-to-market and co-innovation efforts to expand the reach of both Google Cloud and Datadog, including sales alignment, deeper product integrations and incentives for driving new business.

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Datadog and Google Cloud Extend Partnership

Datadog announced an extension of a strategic partnership with Google Cloud.

Under this partnership, Datadog and Google will grow a relationship that began in 2019 with Datadog’s first European Google Cloud data center to now include new regions, making it even easier for organizations to access and implement Datadog’s monitoring and security platform.

New benefits for Datadog and Google Cloud customers will include:

- Additional Datadog points of presence in Google Cloud regions

- Extended go-to-market collaboration and deeper sales alignment with Google Cloud and Datadog sales teams

- Access to Datadog’s 400+ integrations on Google Cloud’s scalable and secure infrastructure through a single-click deployment on the Google Cloud Marketplace, with consolidated billing that will allow customers to draw down on their Google Cloud committed spend

- Continued investment into product co-innovation with more native joint solutions around Anthos, Open Telemetry and the Google Cloud operations suite.

“Datadog’s monitoring and security platform is critical to organizations as they undergo digital transformation projects, manage cloud migrations, and build new customer-facing applications,” said Amit Agarwal, Chief Product Officer, Datadog. “Extending our partnership with Google Cloud will bring true observability to more customers as they take on these challenging initiatives and use Google Cloud’s cutting edge services to modernize their businesses.”

“Organizations need to be able to leverage monitoring data to optimize their applications in the cloud, and we’re pleased to partner with Datadog to help them do so,” said Kevin Ichhpurani, Corporate VP, Global Ecosystem at Google Cloud. “Datadog provides important capabilities in performance monitoring across on-premises, hybrid, and public cloud infrastructure. By expanding the availability of these capabilities on Google Cloud, we can jointly help customers optimize their most critical workloads for Google Cloud.”

Datadog’s platform brings together infrastructure monitoring, application performance monitoring and log management to provide unified, real-time observability of the business-critical applications that enterprises run in the cloud. Datadog’s existing support for Google Cloud includes easy-to-install integrations, the ability to deploy the Datadog Agent directly on hosts and compute instances to collect metrics with greater granularity, and out-of-the-box integration dashboards providing a high-level view into each and every Google Cloud service.

These capabilities complement Google Cloud’s expertise in artificial intelligence, machine learning, data analytics and more, providing Datadog and Google Cloud customers with observability into the performance of their most critical applications and services.

With this strategic partnership, Datadog and Google Cloud will work together on new go-to-market and co-innovation efforts to expand the reach of both Google Cloud and Datadog, including sales alignment, deeper product integrations and incentives for driving new business.

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In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...