Cohesity, a leader in AI-driven data security, has announced a strategic integration with Datadog, the AI-powered observability and security platform for cloud applications. Through this collaboration, the two companies aim to deliver enterprise-grade AI Agent Resilience, combining real-time observability with rapid, automated data recovery capabilities designed specifically for production AI environments.
As AI agents transition from experimental deployments to mission-critical enterprise workflows, they increasingly interact directly with core infrastructure components such as data stores, APIs, and enterprise applications. However, this operational shift introduces new risks. Because AI systems operate at machine speed, even a small logic error, schema mismatch, or data anomaly can escalate rapidly and disrupt business operations within seconds. Consequently, organizations require not only real-time monitoring but also the ability to act instantly when anomalies occur.
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Through the integration, Datadog provides continuous monitoring and observability across cloud infrastructure, AI workloads, object storage systems, and application services. This enables enterprises to establish behavioral baselines for AI systems and quickly identify irregular patterns, such as unexpected data deletions, abnormal data mutations, or suspicious AI agent activity. Once an anomaly is detected, Cohesity extends those insights into automated, API-driven recovery workflows, enabling organizations to restore affected datasets to verified point-in-time states with speed and precision.
Together, the two platforms aim to deliver a closed-loop resilience model for AI-driven systems. This model includes continuous telemetry and anomaly detection across infrastructure and enterprise data environments, automated orchestration from alert detection to remediation, and granular recovery capabilities for multiple enterprise workloads. These workloads include virtual machines, databases, files, objects, SaaS applications, and AI data stores. Additionally, the system maintains a complete audit trail documenting detection, response actions, and restoration processes to support governance and compliance requirements.
A practical example highlights the importance of this integrated approach. In a representative scenario, an AI agent operating within its authorized access boundaries mistakenly deleted critical records from a cloud object storage environment after misinterpreting a newly introduced data schema. Datadog’s monitoring system quickly detected an unusual drop in object counts within the storage environment. Immediately afterward, the platform triggered an automated recovery workflow through Cohesity. Within minutes, the affected records were restored from immutable snapshots without affecting other data and without requiring manual intervention.
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As enterprises deploy increasingly autonomous AI systems, this type of automated resilience is becoming essential. Organizations must ensure that AI innovation does not compromise operational stability or data integrity.
“The only way to embed AI in core enterprise workflows confidently and at scale is to strengthen your cyber resilience simultaneously,” said Vasu Murthy, Chief Product Officer, Cohesity. “Datadog provides the real-time signals that something has gone wrong. Cohesity enables surgical recovery to a trusted state. Together, we’re empowering enterprises to build and operate AI systems they can truly trust secure, compliant, and always available.”
“Observability is foundational to operating AI agents in production,” said Yrieix Garnier, VP of Product at Datadog. “Enterprises need real-time visibility into how agents interact with their data and systems. By integrating Datadog’s AI Observability and workflow automation with Cohesity’s immutable recovery capabilities, customers can move from insight to action in minutes strengthening reliability and trust in AI-driven operations.”
Cohesity’s broader cyber resilience platform already supports a wide range of enterprise data environments, including virtual machines, databases, file and object storage, SaaS applications, vector databases, model configurations, and AI agent memory systems. As AI workloads increasingly span hybrid and multicloud infrastructures, the integration ensures that recovery capabilities align with the full operational scope of modern AI systems.
Overall, the joint solution enables organizations to innovate with AI while maintaining strict governance, data integrity, and business continuity standards. By combining continuous observability with automated recovery, Cohesity and Datadog are helping enterprises scale AI adoption while ensuring operational resilience across complex digital ecosystems.
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