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Back to News List

Datadog enhances AI agent reliability and security with new observability tools

June 12, 2025•Beth Pariseau•Original Link•2 minutes
AI Observability
Datadog
Security

Datadog introduces AI agent observability and security features to improve trust and reliability in enterprise automation workflows.

By Beth Pariseau, Senior News Writer
Published: 12 Jun 2025

Beth Pariseau

NEW YORK -- As enterprises rapidly adopt generative AI, the need for reliable and secure agentic workflows has grown. Datadog has responded with a suite of new AI agent observability and security tools unveiled at its DASH 2025 conference. These include:

  • Bits AI Security Analyst Agent: A preview release aimed at streamlining SecOps tasks.
  • SRE Agent: Enhances incident investigation with multi-step reasoning and learning capabilities.
  • LLM Observability: Features like Experiments for comparing AI models and AI Agent Monitoring for tracking automation workflows.
  • AI Agent Console: Provides a unified view of internal and external agents, including governance data.

Customer Reactions and Concerns

Allen Cox, Senior Director of Security and IT at MyFitnessPal, shared mixed feelings during a breakout session. While Datadog's tools have simplified their security operations, Cox highlighted lingering trust issues:

"AI may give us an opportunity to expand the total range of things that we're choosing to alert on, but we have to rethink detection and response in that context."

Bert Stewart, Head of the Global Command Center for Thomson Reuters, praised the SRE Agent's speed but expressed concerns about pricing:

"It's very interesting stuff, but when things roll out from Datadog, you don't know how much it's going to cost."

Security Enhancements

Datadog also introduced:

  • Sensitive Data Scanner: Prevents data leakage and poisoning attacks.
  • Security Detections: For malicious models, prompt injections, and more (coming later in 2025).

Competitive Edge

Katie Norton, IDC analyst, noted Datadog's focus on runtime data sets it apart:

"AI apps aren't deterministic, so you need to have visibility into the runtime to secure them."

For more details, check out related articles:

  • Alation boosts agentic AI with Numbers Station acquisition
  • Datadog acquisition gives it feature flagging for AI

Have a tip? Email Beth Pariseau or reach out @PariseauTT.

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August 1, 2025•AuthorsSiddharth DwivediAnubhav Mishra

Snowflake Cortex AI Enhances Trust with Observability Tools

Snowflake Cortex AI offers built-in observability, evaluations, and monitoring to ensure trustworthy and production-ready AI applications.

AI Observability
Snowflake Cortex
Generative AI
July 9, 2025•Unknown

Debate Over AI-Generated Code and MCP Servers for Secure Access

Discussion on using MCP servers to control AI agent access versus allowing LLMs to generate and execute code freely, highlighting security and liability concerns.

AI
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MCP

About the Author

Michael Rodriguez

Michael Rodriguez

AI Technology Journalist

Veteran technology journalist with 12 years of focus on AI industry reporting. Former AI section editor at TechCrunch, now freelance writer contributing in-depth AI industry analysis to renowned media outlets like Wired and The Verge. Has keen insights into AI startups and emerging technology trends.

Expertise

AI Industry Analysis
Startup Ecosystem
Technology Trends
Product Reviews
Experience
12 years
Publications
800+
Credentials
2
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