Deploys and optimizes AI/ML inference workloads on GKE, using GPUs, TPUs, and model servers. Use when deploying GKE inference servers, configuring GKE GPU resources for inference, or deploying LLMs on GKE. Don't use for generic batch jobs or HPC task queues (use gke-batch-hpc instead).
Plans and configures multi-tenancy on GKE. Covers namespace isolation, RBAC planning for teams, resource quotas, LimitRanges, network isolation, and cost allocation. Use when designing GKE multi-tenancy, configuring GKE namespaces, setting up resource quotas, or isolating GKE teams. Don't use for single-tenant cluster…
Orchestrates comprehensive production readiness reviews and assessments for GKE clusters and workloads across scalability, security, reliability, observability, backup/DR, and cost optimization. Use when asked to productionize, prepare, assess, audit, or review a GKE cluster or workload before going live to…
Configures GKE edge networking, traffic routing, load balancing, and private service endpoints. Use when configuring Gateway API manifests, standard Ingress, Cloud Armor WAF security policies, Container-Native Load Balancing (NEGs), Private Service Connect (PSC), or Google-managed SSL certificates on GKE. Don't use…
Monitors, troubleshoots, and manages GKE TPU Dynamic Slices custom resources. Use when checking TPU slice lifecycle states, troubleshooting slice provisioning failures, validating single-slice or multi-slice (JobSet) workload manifests, or diagnosing stuck finalizers and the slice controller for the platform operator…
Monitors and troubleshoots GKE TPU workloads, nodes, and node pools using GKE system metrics and PromQL. Use when monitoring TensorCore duty cycle, TPU memory, node readiness, multi-host TPU node pool availability, host maintenance or preemption interruptions, and calculating MTTR or MTBI metrics for GKE TPUs. Don't…
Plans, executes, and validates Google Kubernetes Engine (GKE) cluster upgrades and maintenance operations for both Standard and Autopilot clusters. Produces upgrade plans, pre/post-upgrade checklists, maintenance runbooks with gcloud commands, release channel strategy, and troubleshooting guides. Handles node pool…
Bring an existing GKE cluster under management on user request (e.g. "manage my cluster in ") by creating its Cluster Agent profile, or take one out of management by excluding it. Use whenever a user asks to manage/onboard/watch a specific existing cluster, or to stop managing, exclude or offboard one.
Propose declarative configuration updates securely by committing file changes and submitting pull requests (merge requests on GitLab) for SRE review, including a request to delete a resource, which its "Deleting a resource" section answers with a stated stop, never a pull request. Not for fleet-audit finding fixes …
Orchestrate cross-cluster workload rebalancing using the kanban board with the validation-then-declare pattern. Use when fleet utilization shows one cluster overutilized and another with headroom and a workload should move.
Audits standalone GCE virtual machines, Managed Instance Groups (MIGs), serial console boot failures, sole-tenant node group headroom, and orphaned disk snapshots.
Read and analyze the source of any repository on GitHub or on another forge this install serves (GitLab) — public or one this install has a token for — without a local checkout. Clones broker-side and pulls file content back; use it to answer questions about code, not to change it.
Read and write the agent blackboard - the durable, named topics on the A2A bus where agents publish what they currently know (upgrade readiness, the environment blueprint, dated annotations). Use when asked about fleet or environment state that another agent may already have assessed, before starting a fresh…
Reports every GKE cluster's control-plane and node-pool versions against a target version or each cluster's release-channel default, naming the members that lag and by how many minors, and answers whether one cluster is current for its channel (--cluster); run again during a rollout, it shows which members started…
Authors Config Connector (KCC) manifests for Google Cloud resource changes and hands them to submit-suggestion as a pull request under the GitOps repository's clusters/ /provisioning/ path. Use when a request creates or changes a GKE cluster or node pool (create, grow, autoscale, adopt), a Cloud SQL instance (add a…
Read-only detection of controllers that stopped making progress without erroring — observedGeneration lag, stuck progress conditions, repeating warning events, and references to objects that do not exist — in one namespace or one kind.
Check GKE quota and live hardware obtainability before recommending capacity, and plan future capacity windows for deadline-bound batch jobs. Use when a cluster design, capacity plan, scale-up decision, GPU/TPU batch schedule, or a free-standing availability question needs live evidence: regional quota verification…
Read and change a hosted repository through forge-neutral verbs. Version control here is abstracted — remote operations go through vcs.py, local operations use a credential-free VCS binary on a working copy that vcs.py puts on disk. Covers history, file modes, proposals and issues, so no forge CLI is needed.
Answer a question about a past autonomous fleet audit from the on-pod report store — what a stream last found, how many criticals are open, what changed between two runs, which clusters were skipped or only partly covered, and when each stream last ran. Never the answer to a request to run an audit: a run collects…
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: