This principle in the cost optimization pillar of the Google Cloud Well-Architected Framework provides recommendations to help you optimize the cost of your cloud deployments based on constantly changing and evolving business goals.
As your business grows and evolves, your cloud workloads need to adapt to changes in resource requirements and usage patterns. To derive maximum value from your cloud spending, you must maintain cost-efficiency while continuing to support business objectives. This requires a proactive and adaptive approach that focuses on continuous improvement and optimization.
Principle overview
To optimize cost continuously, you must proactively monitor and analyze your cloud environment and make suitable adjustments to meet current requirements. Focus your monitoring efforts on key performance indicators (KPIs) that directly affect your end users' experience, align with your business goals, and provide insights for continuous improvement. This approach lets you identify and address inefficiencies, adapt to changing needs, and continuously align cloud spending with strategic business goals. To balance comprehensive observability with cost effectiveness, understand the costs and benefits of monitoring resource usage and use appropriate process-improvement and optimization strategies.
Recommendations
To effectively monitor your Google Cloud environment and optimize cost continuously, consider the following recommendations.
Focus on business-relevant metrics
Effective monitoring starts with identifying the metrics that are most important for your business and customers. These metrics include the following:
- User experience metrics: Latency, error rates, throughput, and customer satisfaction metrics are useful for understanding your end users' experience when using your applications.
- Business outcome metrics: Revenue, customer growth, and engagement can be correlated with resource usage to identify opportunities for cost optimization.
- DevOps Research & Assessment (DORA) metrics: Metrics like deployment frequency, lead time for changes, change failure rate, and time to restore provide insights into the efficiency and reliability of your software delivery process. By improving these metrics, you can increase productivity, reduce downtime, and optimize cost.
- Site Reliability Engineering (SRE) metrics: Error budgets help teams to quantify and manage the acceptable level of service disruption. By establishing clear expectations for reliability, error budgets empower teams to innovate and deploy changes more confidently, knowing their safety margin. This proactive approach promotes a balance between innovation and stability, helping prevent excessive operational costs associated with major outages or prolonged downtime.
Use observability for resource optimization
The following are recommendations to use observability to identify resource bottlenecks and underutilized resources in your cloud deployments:
- Monitor resource utilization: Use resource utilization metrics to identify Google Cloud resources that are underutilized. For example, use metrics like CPU and memory utilization to identify idle VM resources. For Google Kubernetes Engine (GKE), you can view a detailed breakdown of costs and cost-related optimization metrics. For Google Cloud VMware Engine, review resource utilization to optimize CUDs, storage consumption, and ESXi right-sizing.
- Use cloud recommendations: Active Assist is a portfolio of intelligent tools that help you optimize your cloud operations. These tools provide actionable recommendations to reduce costs, increase performance, improve security and even make sustainability-focused decisions. For example, VM rightsizing insights can help to optimize resource allocation and avoid unnecessary spending.
- Correlate resource utilization with performance: Analyze the relationship between resource utilization and application performance to determine whether you can downgrade to less expensive resources without affecting the user experience.
Balance troubleshooting needs with cost
Detailed observability data can help with diagnosing and troubleshooting issues. However, storing excessive amounts of observability data or exporting unnecessary data to external monitoring tools can lead to unnecessary costs. For efficient troubleshooting, consider the following recommendations:
- Collect sufficient data for troubleshooting: Ensure that your monitoring solution captures enough data to efficiently diagnose and resolve issues when they arise. This data might include logs, traces, and metrics at various levels of granularity.
- Use sampling and aggregation: Balance the need for detailed data with cost considerations by using sampling and aggregation techniques. This approach lets you collect representative data without incurring excessive storage costs.
- Understand the pricing models of your monitoring tools and services: Evaluate different monitoring solutions and choose options that align with your project's specific needs, budget, and usage patterns. Consider factors like data volume, retention requirements, and the required features when making your selection.
- Regularly review your monitoring configuration: Avoid collecting excessive data by removing unnecessary metrics or logs.
Tailor data collection to roles and set role-specific retention policies
Consider the specific data needs of different roles. For example, developers might primarily need access to traces and application-level logs, whereas IT administrators might focus on system logs and infrastructure metrics. By tailoring data collection, you can reduce unnecessary storage costs and avoid overwhelming users with irrelevant information.
Additionally, you can define retention policies based on the needs of each role and any regulatory requirements. For example, developers might need access to detailed logs for a shorter period, while financial analysts might require longer-term data.
Consider regulatory and compliance requirements
In certain industries, regulatory requirements mandate data retention. To avoid legal and financial risks, you need to ensure that your monitoring and data retention practices help you adhere to relevant regulations. At the same time, you need to maintain cost efficiency. Consider the following recommendations:
- Determine the specific data retention requirements for your industry or region, and ensure that your monitoring strategy meets the requirements of those requirements.
- Implement appropriate data archival and retrieval mechanisms to meet audit and compliance needs while minimizing storage costs.
Implement smart alerting
Alerting helps to detect and resolve issues in a timely manner. However, a balance is necessary between an approach that keeps you informed, and one that overwhelms you with notifications. By designing intelligent alerting systems, you can prioritize critical issues that have higher business impact. Consider the following recommendations:
- Prioritize issues that affect customers: Design alerts that trigger rapidly for issues that directly affect the customer experience, like website outages, slow response times, or transaction failures.
- Tune for temporary problems: Use appropriate thresholds and delay mechanisms to avoid unnecessary alerts for temporary problems or self-healing system issues that don't affect customers.
- Customize alert severity: Ensure that the most urgent issues receive immediate attention by differentiating between critical and noncritical alerts.
- Use notification channels wisely: Choose appropriate channels for alert notifications (email, SMS, or paging) based on the severity and urgency of the alerts.