Generates cost optimization guidance for Google Cloud workloads based on the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify cost requirements and constraints, and provide actionable recommendations for build, deploy, and manage the workload cost-efficiently in Google Cloud.
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Generates cost optimization guidance for Google Cloud workloads based on the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify cost requirements and constraints, and provide actionable recommendations for build, deploy, and manage the workload cost-efficiently in Google Cloud.
Google Cloud Well-Architected Framework skill for the Cost Optimization pillar
Overview
The Cost Optimization pillar of the Google Cloud Well-Architected Framework
provides a structured approach to optimize the costs of your cloud workloads
while maximizing business value. Cloud costs differ significantly from
on-premises capital expenditure (CapEx) models, requiring a shift to operational
expenditure (OpEx) management and a culture of accountability (FinOps).
The FinOps lifecycle consists of three iterative phases:
Inform: Visibility and allocation. Always start with Cloud Billing
reports for built-in console visibility (filtered by department labels).
Complement with Looker Studio for custom, shareable cross-departmental
dashboards.
Optimize: Rates and usage. Eliminate waste, right-size resources, and leverage commitments (CUDs, SUDs).
Operate: Continuous improvement. Integrate cost management into delivery pipelines and establish governance.
Operational instructions
Comprehensive First: Always provide a complete list of standard recommendations/strategies relevant to the service or scenario mentioned. Do not limit the scope or omit standard elements just because you are proposing follow-up questions.
Full Conjunction: When an instruction bundles multiple actions (e.g., "A AND B"), you must mention and explain BOTH actions in your response explicitly.
Conditional Assessment: Only use the 'Workload assessment questions' to refine advice after providing standard framework recommendations, unless the user explicitly asks for an interview or assessment first.
Core principles
The recommendations in the cost optimization pillar of the Well-Architected
Framework are aligned with the following core principles:
The following are examples of Google Cloud products and features that are
relevant to cost optimization:
Visibility and monitoring:
Cloud Billing reports: Built-in dashboards for visualizing spending and
trends. Essential for visibility within the console.
BigQuery billing export: Enables granular, custom analysis of billing
data using SQL and BI tools.
Looker Studio: Used for creating detailed, shared cost dashboards and
reports. Use alongside Cloud Billing reports for custom visual insights.
Billing alerts and budgets: Automated notifications when spending
reaches predefined thresholds.
Storage Insights: Used to analyze Cloud Storage access patterns and identify
cost-saving opportunities.
Automation and optimization tools:
Recommender / Active Assist: Automatically identifies idle resources,
rightsizing opportunities, and unused commitments.
Cloud Hub Optimization: Integrates billing and resource utilization data
to help developers and application owners quickly identify their most
expensive, fluctuating, or underutilized cloud resources.
FinOps hub: Presents active savings and optimization opportunities in
one dashboard.
Billing quotas: Limits on resource consumption to prevent unexpected
cost spikes.
Efficient infrastructure:
Managed services and serverless services: Services like Cloud Run, Cloud
Run functions, and GKE Autopilot reduce operational overhead and pay-per-use
scaling.
Compute Engine:
Committed Use Discounts (CUDs): Best for predictable, steady-state workloads.
Spot VMs: Best for fault-tolerant, interruptible, or unpredictable batch tasks.
Sustained Use Discounts (SUDs): Passive, automatic discounts for instances running a significant portion of the month without commitments. Always mention this as a passive alternative or complement to CUDs.
Cloud Storage Lifecycle Policies: Automated moves data to lower-cost
storage classes (Nearline, Coldline, Archive) based on age or access.
Note: Always recommend Storage Insights first to understand current
access patterns before defining lifecycle rules.
:
Workload assessment questions
Ask appropriate questions to understand the cost-related requirements and
constraints of the workload and the user's organization. Choose questions from
the following list:
How do you incorporate cost considerations into your cloud architecture design
process?
How do you foster a culture of cost awareness among your development teams?
How do you monitor and manage cloud costs across different projects or
departments?
What strategies do you use to optimize the cost of your compute resources?
How do you balance cost optimization with the need for agility and innovation?
How do you ensure that you are not over-provisioning cloud resources?
How do you use data and analytics to drive cost optimization decisions?
How do you optimize costs in different environments (e.g., development,
testing, production)?
How do you ensure that your cost optimization efforts are sustainable and
ongoing?
How do you measure the success of your cloud cost optimization initiatives?
Validation checklist
Use the following checklist to evaluate the architecture's alignment with
cost-optimization recommendations:
Cost Attribution: 100% of resources are labeled with key metadata
(e.g., env, team, app).
Granular Visibility: BigQuery billing export is enabled and used for
regular cost reviews.
Budgets and Alerts: Every project or business unit has defined budgets
and active alerts.
Rightsizing: Resources are regularly adjusted based on rightsizing
suggestions provided by Active Assist Recommender.
Commitment Strategy: Spend is reviewed monthly to optimize Committed Use Discount (CUD) coverage. For non-committed workloads, verify if Sustained Use Discounts (SUDs) are being captured automatically.
Idle Resource Management: Unused disks, IP addresses, and idle VMs are
identified and removed monthly.
Managed Services: Serverless options are preferred for new workloads
unless specific technical constraints exist.
Storage Tiers: Lifecycle policies are active for all major storage
buckets to minimize archival costs. Be aware of retrieval fees
associated with Nearline, Coldline and Archive storage classes.
Network Egress: Data transfer is minimized by keeping traffic regional,
using Cloud CDN, and leveraging Standard Network Tier where
appropriate. High-volume on-premises traffic uses Direct Peering or
Cloud Interconnect (always verify if hybrid connectivity is involved).
Native Reporting: Cloud Billing reports must be used for standard
views of spending trends in the console.
Custom Dashboards: Looker Studio is used for advanced, shareable, and
customized reporting.
Networking and Content Delivery
Location awareness: Keep traffic within a single region where possible to avoid inter-region data transfer costs.
Cloud CDN: Caches content to reduce data egress from the origin.
Network Service Tiers: Offers Standard Tier as a lower-cost option compared to Premium Tier for latency-tolerant traffic.
Cloud Interconnect / Direct Peering: Optimizes costs for high-volume data transfer to on-premises environments. Note: Always clarify hybrid connectivity options when discussing egress control, as on-premises sync is often a factor in multi-regional designs.
Managed Databases:
Instance sizing: Right-size CPU and memory based on Cloud Monitoring metrics.
High Availability (HA): Implement HA only for production environments to avoid doubling node costs for all environments.
Storage Optimization: Optimize storage costs by managing backup retention policies AND explicitly identifying and deleting unused or idle resources (like unused and orphaned disks, expired snapshots, or idle instances).
Organization and governance:
Resource Manager: Logical structure (Organizations, Folders, Projects)
for cost attribution.
Labels: Metadata tags for categorizing and filtering costs by
environment, team, or application.
Organization Policy Service: Enforces constraints (e.g., restricted
regions or machine types) to control costs.
