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Datadog Launches Bits AI SRE Agent

Datadog launched Bits AI SRE, an AI agent aware of telemetry, architecture, and organizational context that investigates alerts and surfaces actionable root cause in minutes, giving engineers the information they need to confidently resolve incidents faster, save engineering hours, and reduce end-user and business impact.

Bits AI SRE is part of Datadog’s Bits AI, a suite of AI capabilities that works autonomously across critical monitoring, development, and security workflows to help teams resolve application issues in real time.

Powered by the full breadth and depth of the Datadog platform’s data, Bits AI SRE provides an understanding of organizations’ systems to identify and resolve alerts fast. When an alert fires, Bits AI SRE rapidly analyzes runbooks, telemetry, and more, to separate signal from noise and uncover hypothetical root causes. It validates its own findings, identifies a final conclusion, and delivers that conclusion directly to third-party collaboration tools—all before on-call responders even log in.

What used to take hours to troubleshoot manually, can now be done in minutes autonomously by Bits AI SRE, representing a step toward a future where engineers can focus less on managing incidents and more on building resilient systems.

Designed for enterprise scale, Bits AI SRE supports HIPAA-regulated workloads, includes role-based access controls (RBAC), and features enterprise contracts with trusted AI partners—ensuring organizations adopt AI with confidence and control.

“This launch represents a pivotal expansion of Datadog’s AI strategy as our first generally available AI agent, and signals a new phase of intelligent, automated reliability,” said Yanbing Li, Chief Product Officer at Datadog. “Bits AI SRE allows companies to mitigate issues faster, reduce customer impact, and adopt AI safely. It has already been tested against more than 2,000 customer environments, including both global enterprises and fast-growing start-ups with a diverse range of production environments. Tens of thousands of investigations have run to date, from routine alerts to high-severity incidents, with organizations already reporting positive outcomes. This reflects the tangible and immediate value, tied directly to operational and business outcomes, that we are delivering.”

Bits AI SRE is the first of three AI agents that is Generally Available to all Datadog users. 

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Datadog Launches Bits AI SRE Agent

Datadog launched Bits AI SRE, an AI agent aware of telemetry, architecture, and organizational context that investigates alerts and surfaces actionable root cause in minutes, giving engineers the information they need to confidently resolve incidents faster, save engineering hours, and reduce end-user and business impact.

Bits AI SRE is part of Datadog’s Bits AI, a suite of AI capabilities that works autonomously across critical monitoring, development, and security workflows to help teams resolve application issues in real time.

Powered by the full breadth and depth of the Datadog platform’s data, Bits AI SRE provides an understanding of organizations’ systems to identify and resolve alerts fast. When an alert fires, Bits AI SRE rapidly analyzes runbooks, telemetry, and more, to separate signal from noise and uncover hypothetical root causes. It validates its own findings, identifies a final conclusion, and delivers that conclusion directly to third-party collaboration tools—all before on-call responders even log in.

What used to take hours to troubleshoot manually, can now be done in minutes autonomously by Bits AI SRE, representing a step toward a future where engineers can focus less on managing incidents and more on building resilient systems.

Designed for enterprise scale, Bits AI SRE supports HIPAA-regulated workloads, includes role-based access controls (RBAC), and features enterprise contracts with trusted AI partners—ensuring organizations adopt AI with confidence and control.

“This launch represents a pivotal expansion of Datadog’s AI strategy as our first generally available AI agent, and signals a new phase of intelligent, automated reliability,” said Yanbing Li, Chief Product Officer at Datadog. “Bits AI SRE allows companies to mitigate issues faster, reduce customer impact, and adopt AI safely. It has already been tested against more than 2,000 customer environments, including both global enterprises and fast-growing start-ups with a diverse range of production environments. Tens of thousands of investigations have run to date, from routine alerts to high-severity incidents, with organizations already reporting positive outcomes. This reflects the tangible and immediate value, tied directly to operational and business outcomes, that we are delivering.”

Bits AI SRE is the first of three AI agents that is Generally Available to all Datadog users. 

The Latest

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...