Datadog has launched more than 100 new products and features focused on AI operations, security and software development. The rollout was announced at the company's DASH event in New York.
The updates focus on autonomous monitoring, protection for AI agents, log management in customer cloud storage, custom agent creation and centralised oversight of AI agent use. The additions are intended to help customers manage operational complexity as AI tools spread across software development and infrastructure.
A key change is the expansion of Bits AI, Datadog's set of AI agents for development, security and operations. The system now goes beyond root-cause investigation and can detect, investigate and remediate issues automatically across infrastructure and the software production cycle.
Bits AI can continuously scan infrastructure, surface problems, recommend fixes and, in some cases, resolve them within pre-defined controls. It can also track releases and pull requests from code changes and staging through to production, checking whether software behaves as expected at each stage.
Another addition is Agent Evals, a feature that can debug AI agents and generate fixes for them. Bits AI is also available through tools including Slack and Claude.
Olivier Pomel, Co-Founder and Chief Executive Officer at Datadog, set out the company's view of the market shift. “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 Pomel.
Datadog also introduced AI Guard, a security product aimed at AI agents. The tool is designed to detect and block attacks hidden in prompts or in multi-step agent behaviour, an area the company argues can be missed by traditional prompt-and-response testing.
Tim Knudsen, Vice President of Security Products at Datadog, described the risks associated with agents given broader access to systems and data. “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 behaviour. Datadog's new AI Guard uses a unique combination of deep agent telemetry tracing and AI-native stateful behavioural anomaly analysis to detect and block AI agent attacks otherwise missed by stateless prompt-and-response evaluation,” said Knudsen.
Data storage
Another part of the launch addresses the cost of storing and searching large volumes of logs. Datadog's Bring Your Own Cloud option allows customers to deploy the platform in their own environment so data can be processed and indexed in cloud object storage they already control.
The company positioned this as a response to the sharp rise in log data linked to AI workloads. For many organisations, the choice has been between retaining more data at higher cost or deleting some of it and losing visibility into systems.
Agent oversight
Datadog also launched Bits Agent Builder, which lets customers create their own AI agents inside the platform for remediation and operational workflows. Those agents can be configured to resolve incidents, generate reports and enforce standards within customer-defined controls.
Alongside that, the company introduced Agent Console, a monitoring product for AI agents and developer tools such as Claude Code, Cursor and GitHub Copilot. The aim is to give teams a central view of adoption, performance and spending linked to agent use.
Alexis Lê-Quôc, Co-Founder and Chief Technology Officer at Datadog, said the launch was organised around visibility and control. “We consistently invest about 30 per cent 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 Lê-Quôc.
He added: “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.”
Lê-Quôc also outlined how the company sees the next stage of Bits AI. “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.
On the new monitoring product for coding agents, he said: “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.