
Discover how to architect fault-tolerant multi-region cloud applications using Kubernetes, GCP, and CockroachDB, with insights from Global Payments' migration of mission-critical systems for high availability.

Discover how Grafana Labs tackles production incidents, scales observability tools, and maintains reliability through real-world examples of monitoring challenges, failures, and successful solutions.

Discover how to build robust data streaming platforms using Strimzi, Kafka, and other open-source tools on Kubernetes, while learning architectural best practices and solutions to common challenges.

Discover how to build an open-source cloud-native database platform using Kubernetes, from basic container deployment to complex orchestration, while avoiding vendor lock-in and optimizing costs.

Discover how to optimize Kubernetes service performance through effective metrics collection, analysis, and bottleneck identification using tools like Prometheus, Grafana, and kube-burner for enhanced user experience.

Discover practical techniques for optimizing LLM inference deployments on Kubernetes, focusing on load balancing, autoscaling, and efficient GPU resource utilization using KServe and Knative.

Discover how Cloudera built a secure, scalable AI inference platform using Kubernetes and open-source projects, exploring architecture, performance optimization, and security implementation for production environments.

Discover practical techniques for optimizing AI platform performance through systematic resource management, from instrumentation and data gathering to visualization and throughput optimization.

Master OpenTelemetry implementation for LLM deployments in Kubernetes, covering performance optimization, observability standards, troubleshooting techniques, and advanced autoscaling strategies.

Discover how Buildpacks transform source applications into cloud-ready images, enabling efficient container workflows, enhanced security through SBOM, and scalable deployment for web apps, batch processing, and FaaS platforms.

Discover how The Update Framework (TUF) enables secure distribution of metadata, signing keys, and attestations while ensuring data integrity and tamper resistance in cloud native ecosystems.

Discover how NVIDIA's GeForceNow optimizes GPU resource management using Dynamic Resource Allocation, enabling seamless driver switching and maximum GPU utilization in cloud gaming infrastructure.

Discover how to implement workload identity federation in Kubernetes, enhancing security through credential management while improving developer experience and reducing system outages.

Dive into cloud-native AI architecture, exploring Kubernetes orchestration, Ray distributed computing, and vLLM for efficient large language model deployment and management.

Discover how cloud-native frameworks revolutionize farm data analytics, exploring a real-world implementation managing 1500 cows through KubeStellar and Software-Defined Farm paradigms for optimized agricultural operations.

Discover techniques for building portable cloud-native applications with modular pipelines, consistent interfaces, and efficient feedback loops using tools like Crossplane, Dagger, CloudEvents, and Argo CD.

Dive into advanced Kubernetes control plane architecture, exploring single-tenant, multi-tenant, and multi-shard implementations for scalable cloud-native infrastructure management and SaaS services.

Master progressive delivery techniques for Kubernetes deployments, focusing on controlled canary releases and targeted traffic management using Argo Rollouts for zero-downtime application updates.

Dive into advanced strategies for managing large-scale GPU clusters in Kubernetes, focusing on monitoring, health detection, and solving complex failure scenarios in LLM training environments.

Discover practical strategies for securing CI/CD pipelines through real-world insights from Adobe and Autodesk, featuring reference architectures, security controls, and implementation of CNOE stacks for cloud-native excellence.

Discover how to leverage AI-powered Chaos Engineering to stress test and strengthen Kubernetes networking components, focusing on Gateways, NetworkPolicies, and Services for enhanced resilience.