NEW YORK, June 09, 2026 (GLOBE NEWSWIRE) -- Datadog, Inc. , (NASDAQ: DDOG), the leading AI-powered observability and security platform, today unveiled its latest capabilities and technologies at DASH , the company’s annual event where it launches new features and rolls out key integrations focused on driving autonomy and reducing complexity in an industry facing rapid AI-driven transformation.

“AI has created new operational challenges where code development has outpaced human-scale management and malicious actors now use AI to attack critical systems. But AI didn't create this complexity — it accelerated what was already there. The companies that win on AI won't just build better models, they'll build operational control around them,” said Olivier Pomel, co-founder and CEO at Datadog.

“We consistently invest about 30% of revenue into R&D, which is why we are able to deeply understand and solve the problems our customers face every day in managing operational complexity,” said Alexis Lê-Quôc, co-founder and CTO at Datadog. “At DASH, we launched 100+ capabilities unified around one goal: giving customers the visibility they need to find and fix the issues that matter most, the moment they matter.”

Key new products include:

Bits AI Becomes Truly Autonomous for Both Incident and Development Actions
Bits AI is Datadog’s suite of agents built to automate development, security and operational workflows.

“To date, Datadog’s Bits AI has focused on investigating the root cause of issues. Now — with Bits Detection , Agent Evals , Infrastructure , Code , Release , Data Analysis , Testing and Chat — Bits AI is capable of truly autonomous operations, becoming a reliable teammate that operates across every stage of the production lifecycle and development loop,” said Lê-Quôc.

With these critical updates, Bits AI automatically detects, investigates and remediates issues by scanning infrastructure around the clock to surface issues, recommend fixes and resolve them. The whole process can happen autonomously using strong, pre-defined guardrails. And these capabilities aren’t limited to traditional systems and applications; with its new Agent Eval capabilities, Bits AI can debug and generate fixes for AI agents.

Bits AI also operates across the development loop by following each release and pull request from code change, staging and rollout through to production, and validates that it’s working the way it should be at every step of the way.

Bits AI is available on the tools teams use every day, like Slack and Claude, to keep workflows simple.

Protect AI Agents With AI Guard
“With AI agents operating with elevated privileges, accessing sensitive data, and communicating externally, a single malicious prompt hidden in an innocuous-appearing prompt can turn a well-intended agent into a malicious actor leaking sensitive information — costing millions in reputational damage and data loss. But attackers have learned to hide agent poisoning using subtle instructions only detectable with a deep understanding across multiple steps of the agent’s behavior. Datadog’s new AI Guard uses a unique combination of deep agent telemetry tracing and AI-native stateful behavioral anomaly analysis to detect and block AI agent attacks otherwise missed by stateless prompt-and-response evaluation,” said Tim Knudsen, Vice President of Security Products at Datadog.

Bring Your Own Cloud Makes Datadog the One Platform for Wherever Data Lives
As AI volumes increase, the number of logs generated is growing exponentially. This often forces companies to make an uncomfortable decision: keep the data and absorb the cost, or delete it and risk losing visibility. Datadog is addressing this concern directly with Bring Your Own Cloud , which deploys the Datadog platform into a customer’s own environment so that data is processed and indexed in their cloud object storage.

Create and Monitor Agents Within Datadog
With Bits Agent Builder , teams can create custom AI agents inside Datadog that automate remediation and operational workflows — resolving incidents, generating tailored reports and enforcing standards across environments — all within the controls defined by the customer. To help teams understand the business value of their agents, Datadog also announced Agent Console . This product provides centralized monitoring for AI agents and agentic developer tools like Claude Code, Cursor and GitHub Copilot.

“While there is no doubt coding agents are speeding software development, a lack of visibility makes it difficult to know the full impact these agents have on the business. Agent Console provides the needed visibility to answer the key questions for users about the heaviest adopters of agents, the tasks that agents perform best and where they struggle, and how the work produced by agents correlates with spend,” said Lê-Quôc.

To learn more about Datadog’s latest product capabilities and approach to AI-powered observability and security, please read the round-up blog for all the keynote announcements made at DASH: https://www.datadoghq.com/blog/dash-2026-new-feature-roundup-keynote .

About Datadog
Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence.

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 May 7, 2026, 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.

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