Operations | Monitoring | ITSM | DevOps | Cloud

Kubernetes is built on the foundation of APIs and abstraction, and Calico leverages its extensibility to deliver network security and observability in both its commercial and open source versions. APIs are the special sauce that help automate and operationalize your Kubernetes platforms as part of a CI/CD pipeline and other GitOps workflows. Calico OSS 3.30, introduces numerous battle-tested observability and security tools from our commercial editions. This includes the following key features.

With the upcoming release of Calico v3.30 on the horizon, we are excited to introduce Calico Whisker, a simple yet powerful User Interface (UI) designed to enhance network observability and policy debugging. If you’ve ever struggled to make sense of network flow logs or troubleshoot policies in a complex Kubernetes cluster, Whisker is your friend!

The Calico eBPF data plane is your choice if latency is your primary concern. It was very disturbing that some benchmarking brought to our attention that eBPF had higher tail latency than iptables. The 99+% percentiles were higher by as much as a few hundred milliseconds. We did a whole bunch of experiments and we could not crack the nut until we observed that there are some occasional and unexpected TCP reset (RST) packets, but no connections were reset.

Kubernetes has revolutionized cloud-native applications, but networking remains a crucial aspect of ensuring scalability, security, and performance. Default networking approaches, such as iptables-based packet filtering, often introduce performance bottlenecks due to inefficient packet processing and complex rule evaluations. This is where Calico eBPF comes into play, offering a powerful alternative that enhances networking efficiency and security at scale.

As we kick off the new year, we’re excited to introduce the latest updates to Calico, designed to create a single, unified platform for all your Kubernetes networking, security, and observability needs. These new features help organizations reduce tool sprawl, streamline operations, and lower costs, making it more convenient and efficient to manage Kubernetes environments.

Have you ever wondered how to navigate the complexities of managing Kubernetes clusters effectively? Observability is the key, and Elasticsearch plays a pivotal role in storing and analyzing the critical data that keeps your systems running smoothly.

Kubernetes is known for its modularity, and its integration with cloud environments. Throughout its history, Kubernetes provided in-tree cloud provider integrations with most providers, allowing us to create cloud-related resources via API calls without requiring us to jump through hoops to deploy a cluster that utilizes the power of underlying networking infrastructure. However, this behavior will change with the release of Kubernetes v1.31, and right now is the best time to plan for it.

The Generative Artificial Intelligence (GenAI) innovations and advancements over the past 1.5 years have been unmatched. Gartner predicts that by 2026, more than 80% of enterprises will have deployed GenAI-enabled applications in production environments and/or used GenAI application programming interfaces or models. This is up from less than 5% in 2023.

Service mesh is a tool for adding observability, security, and traffic management capabilities at the application layer. A service mesh is intended to help developers and site reliability engineers (SREs) with service-to-service communication within Kubernetes clusters. The challenges involved in deploying and managing microservices led to the creation of the service mesh, but service mesh solutions themselves introduce complexities and challenges.

When enterprises transition to a microservices model, they often need to migrate their legacy applications to the new infrastructure. One popular framework used for these traditional applications is.Net. Due to migration, enterprises require the ability to run Windows containers in their Kubernetes infrastructure.