Packs

5 packs

Optimize GKE Costs

Analyzes current usage, recommends cost-saving measures, and applies optimizations to GKE workloads.

3 skills · pack

GKE Batch & Inference

For teams running batch/HPC and AI/ML inference workloads on GKE with specialized hardware.

2 skills · pack

Secure Google Cloud Workload

Assesses security requirements, identifies risks, and provides actionable recommendations for IAM, network, and data protection.

4 skills · pack

Deploy AI Inference on GKE

Deploy and optimize AI/ML inference workloads on GKE using GPUs, TPUs, and model servers.

3 skills · pack

Google Cloud Well-Architected

For architects evaluating Google Cloud workloads against the Well-Architected Framework pillars: reliability, cost optimization, and operational excellence.

6 skills · pack

Results for “workload”

15 skills

Hardens Google Kubernetes Engine (GKE) clusters with Workload Identity, Secret Manager, RBAC, Binary Authorization, Network Policies, and Pod Security Standards.

14.4k · bundle

Runs batch processing and high-performance computing (HPC) workloads on Google Kubernetes Engine (GKE), including job queues, parallel processing, and MPI workloads.

securing-kubernetes-on-cloud

Hardens managed Kubernetes clusters on EKS, AKS, and GKE by implementing Pod Security Standards, network policies, workload identity, RBAC scoping, image admission controls, and runtime security monitoring.

24.6k · bundle

Deploys and optimizes AI/ML inference workloads on GKE, using GPUs, TPUs, and model servers.

Configures GKE storage including PVCs, PersistentVolumes, Filestore, and GCS FUSE with best practices for production workloads.

Protects stateful GKE workloads by configuring backup plans, restore workflows, and disaster recovery using Backup for GKE.

More results

kubernetes-patterns

Provides production-grade Kubernetes YAML patterns and kubectl debugging commands for deploying, managing, and debugging workloads reliably.

Manage AWS EKS clusters, node groups, IRSA, add-ons, and workloads using AWS CLI and eksctl commands.

gke-reliability

Configures GKE workload reliability with PodDisruptionBudgets, health probes, topology spread constraints, and graceful shutdown patterns.

kubernetes-specialist

Create and manage Kubernetes workloads with declarative YAML manifests, covering deployments, networking, security, storage, Helm charts, and troubleshooting.

10.4k · bundle

Set up and manage Google Kubernetes Engine clusters, node pools, workloads, networking, and storage with Autopilot defaults.

Provides expertise in containerization technology, covering container creation, orchestration integration, security hardening, and operational best practices for production workloads.

Evaluates a containerized framework for deploying distributed big data workloads, measuring execution time and cloud cost scaling from four to eight nodes.

cloudthinker-ai

Manages Google Kubernetes Engine clusters via gcloud CLI, covering cluster discovery, node pool management, workload analysis, autopilot configuration, and upgrade planning.

gke-cluster-creation

Creates GKE clusters with golden path Autopilot defaults, supporting Standard and GPU workloads. Guides through project, region, and networking inputs, then provisions and verifies cluster settings.