GKE
Kubernetes Release Cycles and Vendor Support Harbor Freedoms–and Sacrifices
Analysis of the "lag gap" between upstream Kubernetes releases and vendor GA availability, comparing release cadence, support windows, and lifecycle cost tradeoffs across hyperscalers, VMware VCF, and Red Hat OpenShift to guide ...
Jack Wallen | | AWS EKS, Azure AKS, cluster costs, cncf, compliance, DISA STIG, enterprise devops, enterprise Kubernetes, EOL, extended support fees, FedRAMP, FIPS, GA delay, GKE, hyperscalers, innovation velocity, kubernetes, lag gap, lifecycle support, platform choice, Red Hat OpenShift, release cadence, rollback, stability, support window, TCO, upgrade strategy, vendor support, virtualization, VMware VCF
Hybrid Cloud at Enterprise Scale: Private Kubernetes for Portability and Control
Private Kubernetes is the missing abstraction layer for enterprise hybrid cloud. Learn how a private Kubernetes platform enables portability, security, governance, and freedom from vendor lock-in across on-prem, private cloud, and public ...
Shravani Gunturu | | AKS, cloud abstraction layer, cloud portability, EKS, enterprise cloud strategy, enterprise Kubernetes, GitOps, GKE, hybrid cloud, hybrid cloud architecture, Kubernetes governance, Kubernetes platform, Kubernetes security, multicloud strategy, Openshift, openstack, platform engineering, private cloud Kubernetes, private Kubernetes, vendor lock-in
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
The AppDev Tech Field Day Report: GCP Cloud Run Demo and a GKE Comparison
Cloud Run and Google Kubernetes Engine are powerful tools for deploying containerized applications. But why exactly does GCP need two products? ...
Google Unfurls Managed Kubernetes Service for the Enterprise
Google this week launched an enterprise edition of its managed Google Kubernetes Engine (GKE) service through which it will manage fleets of clusters in addition to applying customer configurations and policy guardrails ...
Google Adds Additional Storage Service for GKE
As part of a broader expansion of its cloud storage services, Google is extending its Filestore Enterprise for accessing NFS-based storage to be accessible by Google Kubernetes Engine (GKE) clusters running on ...
Despite Google’s ‘Autopilot,’ Kubernetes is Still Hard
We are, obviously, a very long way from being able to put Kubernetes cluster management on “autopilot,” but Google’s new platform ostensibly moves us closer to achieving that goal. Google Kubernetes Engine ...

