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”

9 skills

implementing-security-monitoring-with-datadog

Deploys Datadog Cloud SIEM, CSM, and Workload Protection to detect threats, enforce compliance, and respond to security events across cloud and hybrid infrastructure.

24.6k · bundle

oke-troubleshooter

Diagnose and root-cause issues with OCI Kubernetes Engine clusters and workloads through evidence-driven investigation.

enterprise-agent-ops

Operate long-lived agent workloads with observability, security boundaries, and lifecycle management.

More results

workflow-debugging

Debug AEM Workflow issues on AEM 6.5 LTS and AMS including stuck workflows, failed steps, missing Inbox tasks, launcher failures, stale instances, thread pool exhaustion, queue backlogs, purge failures, and permissions errors.

cloudthinker-ai

Designs and executes load tests, covering scenario design, baseline capture, execution configuration, results analysis, and reporting for k6, Locust, Gatling, and JMeter.

graphsignal-profiler

Set up GPU profiling, tracing, and monitoring for inference workloads using vLLM, SGLang, PyTorch, and dstack services via the Graphsignal Profiler sidecar.

sakamoto-family-smile

Turn model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.

google-cloud-waf-reliability

Evaluates Google Cloud workloads against the Reliability pillar of the Well-Architected Framework, providing actionable recommendations for building, deploying, and managing reliable systems.

google-cloud-waf-operational-excellence

Generates operations-focused guidance for Google Cloud workloads based on the Operational Excellence pillar of the Well-Architected Framework, including assessment questions and validation checklists.