gcp-cud-advisor

What This Skill Does

The gcp-cud-advisor is an expert-level technical agent designed to optimize your Google Cloud Platform compute expenditure. By analyzing historical billing exports and resource utilization data, this agent identifies the optimal balance between Spend-based and Resource-based Committed Use Discounts (CUDs). It distinguishes between volatile workloads that should rely on Sustained Use Discounts (SUDs) and predictable steady-state workloads that are prime candidates for deep-discount commitments. The agent calculates specific coverage gaps, evaluates risk scenarios, and generates the exact gcloud CLI commands required to implement your new cost-saving strategy, ensuring you stop overpaying for on-demand compute resources.

Installation

To install this skill, run the following command in your terminal: clawhub install openclaw/skills/skills/anmolnagpal/cud-advisor

Use Cases

• Cloud Cost Optimization: Reducing monthly GCP invoices for GKE and Compute Engine clusters by transitioning from on-demand pricing to committed plans.
• Portfolio Planning: Assessing whether to commit to vCPU/RAM (Resource-based) for specific regions or opting for the flexibility of Spend-based commitments.
• Risk Mitigation: Analyzing the breakeven point and financial exposure of long-term commitments versus variable scaling needs.
• Audit Readiness: Reviewing existing CUD coverage to prevent over-commitment in environments that have downsized.

Example Prompts

1. "I have attached my BigQuery billing export for the last 90 days. Can you tell me which GKE clusters are steady enough for resource-based CUDs and which should stay on-demand?"
2. "Review my current CUD portfolio: [paste json from gcloud compute commitments list]. I'm currently at 40% coverage; suggest a plan to reach 70% without increasing risk."
3. "My monthly spend is roughly $5,000 across Compute Engine. If I commit to a 3-year term, what is the conservative vs aggressive savings projection for spend-based discounts?"

Tips & Limitations

• Data Privacy: This skill is instruction-only. It does not access your GCP account. You must provide the data via exports. Ensure you scrub sensitive project IDs or PII from exported JSON if your organization requires it.
• Accuracy: The quality of the recommendation is directly proportional to the detail of the data you provide. Always include at least 90 days of usage history to account for seasonal or periodic variations in compute load.
• SUD Interaction: Remember that Sustained Use Discounts (SUDs) are automatic. The agent will help you identify when a commitment is actually cheaper than the baseline SUD savings, preventing you from 'double-paying' for the same capacity.