Machine learning cybersecurity firm Darktrace PLC today announced the expansion of its artificial intelligence-driven cloud detection and response system Darktrace / CLOUD to support Microsoft Azure environments, enabling faster and more efficient deployment through an agentless approach.

Also available for AWS deployments, Darktrace / CLOUD leverages Darktrace’s “Self-Learning AI” to monitor cloud assets, containers and users and then correlate that activity with identity and network data from across an organization’s digital ecosystem. What’s delivered — contextualized understanding — allows Darktrace / CLOUD to provide proactive detection, investigation and response to malicious activity across cloud environments within seconds.

Darktrace’s Self-Learning AI also allows Darktrace / CLOUD to deliver automated cloud security posture management that continuously assesses cloud configurations against industry standards, allowing security teams to identify and prioritize misconfigurations, vulnerabilities and policy violations in real time. The capabilities give security teams a complete, live understanding of their cloud environments and help them focus their limited time and resources where they are needed most.

The new support for Azure announced today includes integration with Microsoft Azure’s virtual network flow logs for agentless deployment into the cloud. DackTrace / CLOUD leverages virtual network flow logs to automatically capture network data while integrating into Azure cloud environments with minimal manual effort beyond initial configuration. Through the integration, deployment times are reduced to as little as 15 minutes versus several weeks for common agent-based systems and several days for most agentless systems.

Darktrace / CLOUD’s agentless approach is said by the company to additionally lower the cost of operations by eliminating the central processing unit and memory consumption associated with cloud security agents. Through Darktrace / CLOUD’s agentless approach, the need for dedicated resources per cloud instance is reduced and performance impact is minimized, allowing teams to scale their security across their cloud architecture without the cost of additional agents.

“As organizations rapidly transition to the cloud, cloud detection and response are becoming critical to ensuring safety and security, but personnel and cost are proving notable barriers to their effective deployment,” said Darktrace Chief Product Officer Max Heinemeyer. “Using our Self-Learning AI, integrated with Microsoft Azure, Darktrace / CLOUD deploys quickly and easily, then provides teams with constant visibility, autonomous investigation and real-time response without ballooning operating costs.”

The launch of Azure support comes after it was announced on Oct. 1 that Thoma Bravo had completed its $5.3 billion takeover of Darktrace. The deal to acquire Darktrace had previously been announced in April.

Nicole Carignan, vice president of strategic cyber AI at Darktrace, spoke with theCUBE, SiliconANGLE Media’s livestreaming studio, in August to discuss how Darktrace is using AI to spot abnormalities through boosting incident detection, cyber resilience and threat vulnerability prioritization:

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