Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Implementing AI Agent Security on Azure AKS: A Practical Guide

Your platform team deployed eBPF-based runtime sensors on AKS last week. Defender for Containers is enabled. Azure Policy is enforcing pod security standards across your AI workload namespaces. And your Observe pillar is still blind — because nobody enabled the Diagnostic Setting that routes kube-audit logs to the Log Analytics workspace where your tooling can actually consume them.

How to investigate cloud credential compromise with Bits AI Security Analyst

Cloud environments create a flood of security signals, often reaching tens of thousands per day depending on the organization’s size. Security engineers and analysts spend a disproportionate share of their time triaging these signals instead of acting on legitimate threats. But the time-intensive parts of that work, such as identifying related signals and building a timeline, can be handled systematically, leaving teams free to focus on what actually requires human judgment.

Evaluate, optimize, and secure your Google Cloud AI stack with Datadog

As AI adoption accelerates on Google Cloud, the challenge for most teams today is no longer just building AI-powered applications. It’s also managing the full AI stack from end to end, including data pipelines, infrastructure, release process, and security operations. Many teams are monitoring these layers with different tools, creating complexity, fragmenting visibility, and slowing decisions on what to do next.

Securing air-gapped environments with Elastic on Google Distributed Cloud

If you are not using AI to defend against AI, you will lose. But for organizations operating in air-gapped environments, the path to AI-driven defense can be blocked by the very isolation that protects them. Today, we're announcing that Elastic Security is now the embedded security layer for Google Distributed Cloud (GDC) air-gapped environments, expanding our collaboration with Google Cloud.

CrowdStrike Expands Real-Time Cloud Detection and Response to Google Cloud

Complexity has become a defining security challenge as organizations expand across hybrid and multi-cloud environments. In fact, 52% of surveyed organizations ranked multi/hybrid cloud complexity among their top three infrastructure concerns.1 This complexity creates fragmented visibility across cloud providers, workloads, and Kubernetes environments — gaps that adversaries increasingly exploit to move undetected.

The 7 Rs of AWS Application Migration: Choosing the Right Path for Each Workload

Most application migration projects fail the same way: someone picks a single strategy for the entire portfolio, then tries to force every workload into it. Lift-and-shift everything to meet a data centre exit deadline. Refactor everything because someone read a cloud-native manifesto. Retire nothing because no one wants to make the decision. AWS’s 7 Rs framework exists to prevent that.

Cloudflare Just Shipped 20+ Features for AI Agents in One Week

The conversation explores why the Internet and the cloud were not designed for an AI-agent world, and what infrastructure needs to change as software agents begin generating code, running workflows, and interacting directly with online services. Ming and Anni walk through several announcements from Cloudflare’s Agents Week, including new tools for agent infrastructure, memory, developer workflows, AI Gateway, email, artifacts, browser automation, security, and agent-ready websites.

AI Workload Security on GKE: Evaluating Google Cloud Native vs Third-Party Solutions

A CISO running AI agents on GKE has watched three Google product launches in eighteen months — Model Armor, expanded Security Command Center coverage for AI workloads, additions to Chronicle’s curated detection content — and is being asked whether the GCP-native stack is now sufficient. The vendor demos and the Google Cloud blog say yes. The 2 AM analyst experience says something different.