Kubernetes adoption continues to grow as enterprises increasingly rely on containerized environments to deploy and scale their application. However, the complexity of the Kubernetes environment has evolved dramatically. It ranges from single-cluster setups of workloads to multi-cluster environments spanning hybrid and multi-cloud infrastructure. Kubernetes deployments are now characterized by their scale and diversity.

The eBPF dataplane differs from traditional Linux dataplane in many ways, with its structure largely dictated by the location of the so-called eBPF hooks inside the kernel – locations where developers can inject their eBPF programs to change default kernel behavior.

As Kubernetes becomes the backbone of modern cloud native applications, organizations increasingly seek to consolidate workloads and resources by running multiple tenants within the same Kubernetes infrastructure. These tenants could be: While multitenancy offers cost efficiency and centralized management, it also introduces security and operational challenges: To address these concerns, practitioners have three primary options for deploying multiple tenants securely on Kubernetes.

In today’s cloud-native environments, network security is more complex than ever, with Kubernetes and containerized workloads introducing unique challenges. Traditional tools struggle to monitor and secure these dynamic, interconnected systems, leaving organizations vulnerable to advanced threats, such as lateral movement, zero-day exploits, ransomware, data exfiltration, and more.

Over the past year, there has been a culmination of hype and excitement around Generative AI (GenAI). Most organizations initiated proof-of-concept projects for GenAI, eager to reap the technology’s benefits, which range from improved operational efficiency to cost reductions. According to recent research, 88% of organizations are in the midst of actively investigating GenAI, transcending other AI applications.

In Kubernetes, pods often need to securely communicate with external resources, such as internet services or APIs. Traditional Kubernetes network policies use IP addresses to identify these external resources. However, managing policies with IP addresses can be challenging because IPs often change, especially when dealing with dynamic websites or APIs.

This is the second blog post in a series exploring how Kubernetes, despite its inherent complexity, provides features that simplify security efforts. Kubernetes presents an interesting paradox: while it is complex, it simplifies many aspects of deploying and managing containerized applications, including configuration security. Once you navigate its learning curve, Kubernetes unlocks powerful capabilities and tool support that make managing configuration security significantly easier.

In today’s cloud-native ecosystems, effective configuration security is essential. Containers and Kubernetes clusters operate in dynamic environments with multiple interconnected risk vectors, making security more complex than in traditional IT environments. Misconfigurations can lead to vulnerabilities, breaches, and compliance issues, putting applications and data at risk.

In the ever-evolving Kubernetes landscape, security remains a paramount concern. Ensuring that your containers are free from vulnerabilities is crucial for maintaining the integrity and performance of your applications. This is where Calico Vulnerability Management steps in, offering a comprehensive solution designed to keep your Kubernetes environment secure from potential threats.

Calico Open Source 3.29 is here, bringing powerful new features and enhancements to simplify networking and security in Kubernetes. In this post, we’ll explore the key highlights of this release and celebrate the contributions of the talented individuals who made it happen.