Results for “capacity-discovery”

Discovers available Azure OpenAI model capacity across regions and projects, analyzes quota limits, and recommends optimal deployment locations.

Automates Azure OpenAI model deployment by checking capacity across regions and deploying to the best available option.

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

Deploy cloud-native deception across AWS, Azure, and GCP using decoy resources that generate high-fidelity alerts when attackers interact with them.

Assess cloud infrastructure for security misconfigurations, IAM privilege escalation paths, S3 public exposure, open security group rules, and IaC security gaps across AWS, Azure, and GCP with MITRE ATT&CK mapping.

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