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Datadog Unveils Latest AI Agents to Rapidly Resolve Application Issues
Newsfile· 2025-06-10 20:05
Core Insights - Datadog has launched three new AI agents designed to enhance incident resolution for development, security, and operations teams, marking a significant advancement in its Bits AI platform [1][2][3] Group 1: New AI Agents - The new AI agents include Bits AI SRE, Bits AI Dev Agent, and Bits AI Security Analyst, each tailored for specific functions in incident response, product development, and security [2][3] - Bits AI SRE operates 24/7 to triage alerts and provide initial investigation findings, while Bits AI Dev Agent generates code fixes and opens pull requests tailored to the organization's technology stack [3][4] - Bits AI Security Analyst autonomously triages security signals and conducts investigations, delivering resolution recommendations without human intervention [3] Group 2: Enhanced Capabilities - The new Proactive App Recommendations feature analyzes existing telemetry to suggest high-impact fixes and actions to improve application performance [8] - APM Investigator automates the troubleshooting of latency spikes by identifying bottlenecks and proposing fixes, streamlining the resolution process for engineers [8] Group 3: Strategic Positioning - Datadog's platform processes trillions of data points, providing a rich data environment that enhances the effectiveness of its AI capabilities [3] - The architecture of the new AI agents allows for rapid deployment and consistent user experience, leveraging high-quality observability data for precise insights [2][3]
Datadog Expands AI Security Capabilities to Enable Comprehensive Protection from Critical AI Risks
Newsfile· 2025-06-10 20:05
Core Insights - Datadog has expanded its AI security capabilities to address critical security risks in AI environments, enhancing protection from development to production [1][2][3] AI Security Landscape - The rise of AI has created new security challenges, necessitating a reevaluation of existing threat models due to the autonomous nature of AI workloads [2] - AI-native applications are more vulnerable to security risks, including prompt and code injection, due to their non-deterministic behavior [3] Securing AI Development - Datadog Code Security is now generally available, enabling teams to detect and prioritize vulnerabilities in custom code and open-source libraries, utilizing AI for remediation [5] - The integration with developer tools like IDEs and GitHub allows for seamless vulnerability remediation without disrupting development processes [5] Hardening AI Application Security - Organizations need stronger security controls for AI applications, including separation of privileges and data classification, to mitigate new types of attacks [6] - Datadog LLM Observability monitors AI model integrity and performs toxicity checks to identify harmful behaviors [7] Runtime Security Measures - The complexity of AI applications complicates the task of security analysts in identifying and responding to threats [9] - The Bits AI Security Analyst, integrated into Datadog Cloud SIEM, autonomously triages security signals and provides actionable recommendations [10] Continuous Monitoring and Protection - Datadog's Workload Protection continuously monitors interactions between LLMs and their host environments, with new isolation capabilities to block exploitation of vulnerabilities [11] - The Sensitive Data Scanner helps prevent sensitive data leaks during AI model training and inference [8] Recent Announcements - New security capabilities were announced during the DASH conference, including Code Security, Cloud Security tools, and enhancements in LLM Observability [12]