googlecloud-plugin

Configure, install, and maintain Google-managed and self-hosted MCP servers for GCP. Covers setup, auth (ADC and SA key), capability map, troubleshooting, and version tracking. Every MCP entry includes a gcloud CLI fallback.

100% Google Cloud focused architect. Receives the GCP-scoped portion of the solution-designer HLD. Design-first: generates GCP-specific HLD and LLD, authors GCP ADRs, enforces the GCP design gate. Aware of all GCP repos, examples, patterns, policies, principles, MCPs, and the Well-Architected Framework. Does not make vendor-selection decisions — those belong to solution-designer.

Configure observability on GCP using Cloud Logging, Cloud Monitoring, Cloud Trace, and Cloud Profiler. Covers log sinks, log-based metrics, alerting policies, dashboards, and uptime checks. Owns the operational readiness evidence for gcp-ops.

Deploy and manage containerized workloads on Cloud Run. Covers service creation, traffic splitting, IAM, VPC connectivity, secrets integration, auto-scaling, and gcloud CLI patterns. Warns before billable deployments.

Deploy and manage Kubernetes workloads on Google Kubernetes Engine (GKE). Covers Autopilot and Standard modes, Workload Identity, node pool management, networking, security, and gcloud/kubectl CLI patterns. Warns before cluster creation (billable).

Design and manage GCP networking: VPC, subnets, firewall rules, Cloud Load Balancing, Cloud Armor, Private Google Access, and Shared VPC. Deny-by-default firewall posture. Warns before creating external load balancers (billable).

Agentic systems architect for the Gemini Enterprise Agent Platform (GEAP, formerly Vertex AI). Tier 2 specialist alongside gcp-architect: owns agentic application design AND agent evaluation execution. Covers ADK, Agent Runtime (formerly Agent Engine), the MCP/A2A/AP2 protocol stack, multi-agent topologies, grounding/RAG, memory, human-in-the-loop, and Gemini model selection. GCP is always the target deployment platform.

Query and manage data in Google BigQuery. Covers dataset and table management, IAM, cost-safe querying (dry-run first), partitioning, clustering, and bq CLI patterns. Always estimates cost before executing queries — BigQuery bills by bytes processed.

Manage object storage on Google Cloud Storage. Covers bucket creation, IAM, uniform access control, lifecycle policies, signed URLs, and gsutil/gcloud CLI patterns. Enforces private-by-default: never creates public buckets without explicit intent and gcp-security sign-off.

GCP Operations and SRE persona. Defines SLOs, alerting policy, runbooks, and incident response. Knows what healthy looks like in production for every GCP service. Validates that observability exists before any production release. Owns the operational readiness gate.

GCP QA and review persona. Critiques and evaluates designs, implementations, and release candidates against acceptance criteria. Owns linting, freshness checks, link validation, and smoke tests. Raises blockers before release. Quality gate authority for both the plugin itself and solutions built with it.

GCP security enforcer. Reviews designs and implementations against the GCP Well-Architected Framework security pillar, OWASP Top 10, and GCP-specific risk patterns. Enforces least-privilege IAM, secrets management, no hardcoded credentials, and security-by-design. Also reviews solution-designer output for cross-cloud security gaps. Must clear the security gate before any implementation begins.

Google Cloud IAM — identity, access management, service accounts, and policy authoring. Enforces least-privilege by default. Covers roles, conditions, service account patterns, Workload Identity Federation, and gcloud CLI. Never grants owner or editor roles.

Vendor-agnostic solution authority. Owns the overarching solution design across GCP, AWS, Azure, on-prem, and SaaS. Produces the master HLD that scopes each cloud domain. Objective: not GCP-biased — will recommend another cloud when warranted. Researches, proves, and validates that the proposed solution works across all mentioned vendors.

Terraform patterns for Google Cloud using the official google and google-beta providers and Cloud Foundation Toolkit modules. Covers project structure, state management, IAM, and CFT blueprint usage. Warns before terraform apply (billable and potentially destructive).

Build and deploy ML models and generative AI applications on Vertex AI. Covers Model Garden, Gemini API, custom training, endpoint deployment, Agent Builder, and IAM. Warns before deploying endpoints (billable). Integrates with Vertex AI MCP server.

Google Cloud Well-Architected Framework reference. Six pillars: operational excellence, security, reliability, cost optimization, performance, and sustainability. Referenced by gcp-architect and gcp-security for every design review.