
Discover how Yelp manages container security at scale, from implementing vulnerability tracking to developing maturity models that guide thousands of engineers in maintaining robust Docker and Kubernetes deployments.

Dive into CEL validation cost budgeting in Kubernetes, learn to analyze runtime costs, and implement efficient CRD validations while avoiding budget violations and API server rejections.

Discover how to optimize AI/ML workloads on Kubernetes using distributed cache systems, achieving high-performance data access with 50+ GB/s throughput and sub-2ms latency for large-scale GPU clusters.

Explore a detailed comparison of three leading eBPF-based Kubernetes security solutions, examining performance impacts, required privileges, and key features to make an informed choice for cluster protection.

Discover how Google engineered a private cloud platform using Kubernetes, exploring their innovative approach to cloud tenancy, isolation, networking, and integration of CNCF technologies for scalable infrastructure.

Discover how LinkedIn manages stateful systems in Kubernetes through LiStatefulSet API, enabling customized safety checks and deployment policies while maintaining system availability and data durability.

Discover the evolution of Kubernetes Operator development through 5 versions of a Postgres implementation, exploring architectural decisions, design patterns, and practical strategies for building robust operators.

Discover how Reddit transformed its infrastructure management through platform abstractions, Kubernetes integration, and self-service interfaces to achieve scalable, efficient systems deployment.

Explore Kubernetes pod disruption management techniques, from PodDisruptionBudgets to graceful termination, with practical insights on implementing effective workload availability solutions.

Discover how Kubernetes ensures quality through cloud provider testing, exploring infrastructure-specific behaviors, testing frameworks, and the future of multi-cloud validation processes.

Discover cutting-edge CRI-O and Kubernetes features, from sigstore signature support to Podman pod integration and OCI artifacts, designed for cluster admins seeking advanced container runtime capabilities.

Dive into CoreDNS's plugin architecture, exploring cloud vendor integrations, hybrid-cloud implementations, and hands-on plugin development with Golang for enhanced DNS service discovery.

Discover how SIG ContribEx drives Kubernetes' growth through contributor empowerment, workflow optimization, and community initiatives while maintaining project quality and sustainability.

Discover how Bloomberg leverages Karmada to manage multi-cluster GPU workloads, optimize resource utilization, and streamline AI model training across data centers with intelligent scheduling and high availability.

Dive into safe Custom Resource Definition (CRD) management in Kubernetes, covering version control strategies, schema modifications, and practical insights from real-world implementations.

Explore platform engineering principles and their impact on software architecture, focusing on effective platform design, SDLC integration, and key metrics for measuring developer experience.

Discover how using dedicated etcd instances can enhance Cilium's scalability in large Kubernetes clusters, exploring direct etcd API interaction and performance optimization techniques.

Discover how Uber implements robust multi-tenancy in Kubernetes, exploring isolation strategies, node pools, and namespace integration for managing multiple users while ensuring security and performance.

Discover how to achieve zero-downtime Kubernetes cluster upgrades at scale, focusing on deployment methods, canary rollouts, and quick rollbacks while managing hundreds of clusters with 130+ services each.

Master best practices for deploying and managing LLM inference pipelines on Kubernetes, covering optimization techniques, security measures, and efficient pipeline management using tools like KServe.

Discover how Bloomberg optimizes GPU resource management across multiple clusters using Karmada, focusing on intelligent scheduling, high availability, and streamlined job submission for AI training.