Results for “resource-allocation”

Optimize Kubernetes cluster costs by right-sizing resources, configuring autoscalers, using spot instances, and monitoring spend.

Detects available CPU, GPU, memory, and disk resources and generates strategic recommendations for scientific computing tasks.

Two numbers with two different audiences.

Almost every cloud estate is over-provisioned.

Optimize GKE costs by rightsizing workloads, configuring Spot VMs, selecting machine types, and using Committed Use Discounts.

Audits Claude Code context window consumption across agents, skills, MCP servers, and rules. Identifies bloat, redundant components, and produces prioritized token-savings recommendations.

The relevant axis is not "how do we deploy" but "how fast and how cheaply can we

Evaluates Google Cloud workloads against the Performance Optimization pillar of the Well-Architected Framework, providing actionable recommendations for resource allocation, modular design, elasticity, and monitoring.