Predictable variations (cloud costs)

Predictable Cloud Cost Variations refer to the anticipated changes in cloud service expenses based on historical data, usage patterns, and planned activities. Unlike unpredictable variations, these changes can be forecasted and managed more effectively through strategic planning and resource optimization.

Factors for predictable variations

1. Seasonal Demand: Fluctuations in resource usage due to predictable events or seasons, such as holiday shopping periods, end-of-quarter financial reporting, or academic cycles. For example, an online retailer expects higher traffic and sales during the holiday season and plans for increased cloud resource usage accordingly.
2. Planned Campaigns and Events: Marketing campaigns, product launches, and other planned activities that are expected to drive increased usage of cloud services. For instance, a company launching a new product may anticipate a spike in website traffic and prepare by provisioning additional cloud resources.
3. Scaling for Growth: Anticipated growth in business operations that requires scaling up cloud resources over time. A growing startup, for example, forecasts increased user adoption and plans to gradually increase its compute and storage capacity.
4. Regular Maintenance and Upgrades: Scheduled maintenance or upgrades to infrastructure that temporarily increase resource usage. Migrating to a new database version may require additional resources during the transition period.
5. Application Development Cycles: Predictable resource needs based on development, testing, and deployment cycles of applications. A software development team, for instance, schedules regular testing phases that require temporary increases in cloud resources.

Strategies to manage predictable variations

Effectively managing predictable cloud cost variations involves strategic planning, budgeting, and leveraging cloud provider tools and features. Common strategies include:

• Capacity Planning: Forecast resource needs based on historical usage data and planned activities to ensure adequate capacity without overprovisioning.
• Budgeting and provisioning: Use cloud provider tools like AWS Budgets, Azure Cost Management, and Google Cloud’s Cost Management to set budgets and forecast costs based on expected variations.
• Reserved Instances and Savings Plans: Commit to long-term usage of specific resources to take advantage of discounts offered by Reserved Instances and Savings Plans.
• Scheduled Scaling: Implement scheduled scaling policies to automatically scale resource capacity based on predictable usage patterns.
• Resource allocation: Use tagging to categorize and track resources associated with specific projects, campaigns, or events for better cost management and accountability.
• Performance Optimization: Regularly review and optimize application performance to ensure efficient use of resources, aligning capacity with actual demand.

Further resources

• Easy cloud cost tagging for instant control – Blog article with strategies to easy to implement tagging strategy for predicted cloud costs.
• Framework to build a precise cost forecasting model– Article on building a framework to provision accurately based on predicted variations.