Observability
Exploring eBPF for High-Performance Networking and Security in Kubernetes
Introduction
In the dynamic world of Kubernetes, networking, security, and observability are critical pillars for building robust and scalable applications. A revolutionary technology that is transforming all three of these domains is eBPF (extended Berkeley Packet Filter). This post provides an introduction to eBPF and explores its powerful capabilities for high-performance networking and security in Kubernetes, with a focus on tools like Cilium.
What is eBPF?
eBPF is a technology that allows you to run sandboxed programs in the Linux kernel without changing the kernel source code or loading kernel modules. These eBPF programs can be attached to various hook points in the kernel, such as system calls, network events, and function calls.
Read More…Illuminating Kubernetes: Effective Monitoring & Observability Strategies
Illuminating Kubernetes: Effective Monitoring & Observability Strategies
Kubernetes provides powerful orchestration, but its dynamic and distributed nature makes understanding its health and performance challenging. Traditional monitoring approaches often fall short. To effectively operate Kubernetes clusters and the applications running on them, we need robust observability – the ability to infer the internal state of the system based on its external outputs.
This guide explores essential strategies and best practices for implementing comprehensive monitoring and observability for Kubernetes, focusing on the three pillars: Metrics, Logs, and Traces. We’ll cover key tools, configuration patterns, and how to leverage this data for alerting, troubleshooting, and performance optimization.
Read More…Navigating Microservices: Service Mesh Implementation Patterns & Best Practices
Navigating Microservices: Service Mesh Implementation Patterns & Best Practices
As organizations adopt microservice architectures on platforms like Kubernetes, managing the communication between these distributed services becomes increasingly complex. Challenges arise in areas like reliable request routing, securing inter-service traffic, gaining consistent observability, and enforcing network policies. A Service Mesh provides a dedicated infrastructure layer to address these challenges transparently, decoupling operational concerns from application code.
Service meshes work by injecting a lightweight network proxy (a “sidecar,” typically Envoy or a similar proxy) alongside each application container. These proxies intercept all network traffic entering and leaving the application, forming the data plane. A separate control plane manages and configures these proxies, enforcing policies and collecting telemetry.
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