tag: Gke · 5 items
- Platform/SRE — Learn: GKE Standard CPU node pools can now upgrade nodes in-place (existing VM updated rather than replaced), reducing the risk of upgrades stalling due to resource unavailability. No action required — this is a beneficial default behavior change worth understanding before your next GKE node-pool upgrade cycle.
- CI/CD — Skip
- Leader — Skip
- Signals: GA announcement
- Platform/SRE — Learn: Extreme-scale GKE engineering case study surfaces real control-plane and networking constraints worth tracking as clusters grow; no operational change needed now.
- CI/CD — Skip
- Leader — Learn: Illustrates how Google scales managed Kubernetes for massive AI workloads — useful context when evaluating GKE capacity or large-cluster architecture decisions.
- Platform/SRE — Plan: GKE Standard’s GA increase to 512 pods per node (up from 256) doubles workload density but requires a /22 Pod CIDR block for nodes in the 257–512 range — evaluate whether your cluster IP address plan supports this before enabling denser node configurations.
- CI/CD — Skip
- Leader — Learn: GKE’s doubled pod-density ceiling may shift cluster sizing and cost economics for teams running dense workloads; the new X5 48TB memory tier is worth noting only if the org operates SAP HANA at scale and previously hit the 32TB single-node ceiling.
- Signals: GA announcement
- Platform/SRE — Plan: GDC for VMware 1.35.300-gke.87 (Kubernetes 1.35.3) and 1.34.700-gke.93 (Kubernetes 1.34.7) are available for download; if running 1.34, note its EOL is 2026-10-27, so schedule an upgrade to 1.35 this quarter before that deadline.
- CI/CD — Skip
- Leader — Skip
- Signals: Kubernetes 1.35 EOL 2027-02-28 · Kubernetes 1.34 EOL 2026-10-27
- Platform/SRE — Learn: Valuable engineering case study on extreme-scale Kubernetes control plane constraints, scheduler behavior, and etcd limits — useful for informing architecture decisions on large clusters even if most won’t operate at this scale.
- CI/CD — Skip
- Leader — Learn: Illustrates the ceiling of managed Kubernetes scalability on GKE, which informs build-vs-buy decisions for large-scale platform strategies.