Kubernetes

Curved Kubernetes: Microsoft Workload Orchestration in Azure Arc
Microsoft has confirmed the release and general availability of “workload orchestration” as a new service in Azure Arc, the company’s extension mechanism that enables Azure cloud management capabilities to work outside Azure ...

Mastering Reloader: Automating Kubernetes Restarts with Confidence
Reloader is the missing piece in your DevOps toolkit — bridging the gap between configuration changes and application readiness in real time ...

Unleashing the Power of Argo CD by Streamlining Kubernetes Deployments
There are many CD tools for Kubernetes on the market, but the popular ones include Argo CD, Flux CD, Jenkins X and GitHub Actions ...

Is Open Source KubeVirt Ready for Your VMs at Scale?
KubeVirt is designed for teams focused on DevOps that have or want to adopt Kubernetes — and also have virtual machine workloads that otherwise cannot be easily containerized without KubeVirt ...

Setting Up Scalable Monitoring With Prometheus, Grafana and Mimir on Kubernetes
A comprehensive and adaptable guide to setting up scalable monitoring with Prometheus, Grafana, and Mimir on Kubernetes ...

Advanced DevOps for AI: Continuous Delivery of Models Using Jenkins and Docker
Learn how to automate the continuous integration/continuous delivery (CI/CD) pipeline for machine learning (ML) models using Jenkins, Docker and Kubernetes ...

Evolving Kubernetes and GKE for Gen AI Inference
The combination of foundational improvements in open-source Kubernetes and powerful, managed solutions on GKE represents a significant leap forward for any organization working with generative AI ...
Akshay Ram | | AI aware load balancing, AI aware routing, benchmark database, cloud-native applications, community driven effort, container orchestration, data driven decisions, developer velocity, Evolving Kubernetes, Gen AI inference, GKE, GKE features, GKE Inference Quickstart, GPUs, Inference Gateway, inference perf project, intelligent scheduling, Kubernetes primitives, KV cache utilization, large models, latency vs throughput curves, microservices, model replica routing, open source Kubernetes, request response patterns, scaling, seamless portability, specialized hardware, standardized benchmarking, tail latency reduction, throughput increase, total cost of ownership, TPU serving stack, TPUs, user experience, vLLM library

Navigating the Complexities of Rapidly Scaling Kubernetes Environments
Managing Kubernetes traffic with disparate technologies creates challenges, especially when scaling, emphasizing the need for tool consolidation ...

Why Kubernetes 1.33 Is a Turning Point for MLOps — and Platform Engineering
With Kubernetes v1.33, that point has arrived for artificial intelligence (AI) and machine learning (ML) infrastructure. ...

Security in Kubernetes: Your Stack is Lying to You
The organizations that succeed will not be the ones with the most tools. They will be the ones that treat security as code, embed it into every commit and align their practices ...