Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Containerization vs virtualization is a decision that impacts your infrastructure’s performance, scalability, and costs. Both technologies isolate applications and optimize resources, but they work differently. Virtualization creates full virtual machines with separate operating systems; containerization packages applications with only the dependencies they need.

What is Kubernetes Security Posture Management (KSPM)? KSPM is the continuous process of checking Kubernetes configurations, permissions, and policies against security benchmarks. It finds misconfigurations, policy violations, and compliance gaps by understanding Kubernetes-native resources like the control plane, workloads, RBAC bindings, and network policies—elements traditional security tools can’t see.

What is a Kubernetes dependency scanner? A Kubernetes dependency scanner finds known vulnerabilities in software packages your containers depend on—operating system packages, open-source libraries, and anything pulled in by package managers like npm, pip, or apt. It compares dependencies against vulnerability databases of known CVEs.

What is a Cloud Workload Protection Platform (CWPP)? A CWPP is a security tool that protects running workloads—containers, virtual machines, and serverless functions—across their entire lifecycle. For Kubernetes environments, this means protecting pods and containers from build time through deployment and into production runtime, covering threats like cryptomining, reverse shells, and lateral movement.

If you operate containers on AWS you’re likely familiar with how vulnerabilities can accumulate. The majority of container images currently include least one critical security flaw. Frequently hidden within a base image or an overlooked dependency. This makes enhancing your AWS container security essential. It’s the method to prevent problems such, as data leaks, privilege abuse and supply-chain threats.

Kubernetes applications often rely on Persistent Volume Claims (PVCs) to store critical data, from databases to user uploads. Losing this data due to cluster failures or accidents can be catastrophic for DevOps teams. In this post, we’ll walk through how to safeguard your Kubernetes PVCs using CloudCasa, a backup-as-a-service platform.

What is the best eBPF security tool for Kubernetes? For detection-only, Falco. For detection plus enforcement, Tetragon or KubeArmor. For full-stack correlation across cloud, Kubernetes, container, and application layers, ARMO CADR. The right choice depends on whether you need basic visibility, policy enforcement, or complete attack story generation that reduces investigation time by 90%+. Why do most eBPF security tools fail teams? They create more alerts, not better understanding.

Kubernetes networking offers incredible power, but scaling that power often transforms a clean architecture into a tangled web of complexity. Managing traffic flow between hundreds of microservices across dozens of namespaces presents a challenge that touches every layer of the organization, from engineers debugging connections to the architects designing for compliance. The solution to these diverging challenges lies in bringing structure and validation to standard Kubernetes networking.

For years, AI and machine learning workloads lived in the lab. They ran as internal experiments, batch jobs in isolated clusters, or offline data pipelines. Security focused on internal access controls and protecting the data perimeter. That model no longer holds. Today, AI models are increasingly part of production traffic, which is driving new challenges around securing AI workloads in Kubernetes.

Your CNAPP dashboard shows 10,000 critical findings from last night’s scan. Your CSPM flags misconfigurations every hour. Yet when the SOC asks what actually happened during last week’s incident, you’re still stitching together logs from five different tools to build a timeline that makes sense. Sound familiar? We recently spoke with a platform security lead at a fintech company running 400+ microservices on Kubernetes. Their CNAPP generated 47,000 findings in Q3.