Cloud Cost Optimization

While hybrid and multi-cloud operations can in theory allow organizations to improve resource allocation and efficiency, many times they lead to cost overruns. Resources aren’t set up properly (sizing issues) and are left to run indefinitely as there aren’t any decommissioning dates. Due to a lack of visibility into virtual sprawl, costs can easily spiral out of control. Further, organizations lack early warnings or budget consumption alerts. It is also seen that DevOps teams often subscribe to cloud services for monitoring and backend connectivity, which aren’t accounted for in the cloud cost calculations. Such oversights prevent organizations from assessing the true cost and ROI of their cloud.

Most organizations that adopted cloud with a lift-and-shit approach have realized that it’s not the best way to optimize cloud costs. That’s why organizations need a cloud-first mindset, which means they need to stop provisioning for the peak loads and leverage the benefits of the cloud with right-sized, just-in-time resources. As not all workloads are equal, organizations need to match their demand with on-demand auto-scaling instances, reserved instances, spot instances, and discounted instances. They also need to adopt cloud cost management tools that automate consumption forecasting and simplify capacity management (e.g., power scheduling, removing unused instances, etc.).

Organizations realize the importance of continuous cost optimization at every stage of cloud consumption and why it needs to be a part of their operating model. To this end, they need to embrace automation and self-service analytics tools that offer better visibility and control over cloud spends and their baselines. To optimize cloud costs, organizations need to implement tools that simplify cost allocation, resource tagging, and showback/chargeback models. With automated multi cloud cost dashboards, organizations can easily understand what they are paying for and quickly determine if they have overprovisioned or heading towards some cost spike.

While most vendors claim to offer interactive dashboards and granular visibility, organizations should evaluate their ease of usage and customization. You may want to spin up a custom dashboard for better visibility or define some metric to benchmark your cloud efficiency. A multi-cloud cost-management solution should also offer seamless data collection as leading cloud services providers now charge by the second, more data is generated than ever before. The solution should be capable enough to not only ingest all this cost data from different cloud vendors in near real-time but should also simplify its analysis. Waiting for someone to report until the end of the month can be too late to take remedial actions. Further, organizations should prioritize solutions that offer AI or machine learning capabilities for anomaly detection and cost predictions. Such cloud cost insights can help organizations adopt a more proactive approach to managing their cloud spending.

While FinOps is an evolving field, most FinOps solutions are only an extension of cloud cost management. However, there’s a significant difference in the approach; cloud cost management tools are aimed at IT or operations teams, while FinOps tools are built to engage executives (project managers, product owners, etc.) and DevOps engineers, providing them improved visibility into their infrastructure costs. Earlier, only a few people in the operations team used to be responsible for controlling cloud costs. However, a majority of cost optimizations weren’t directly in their control as it required sensitizing and educating everyone about cloud cost management. This is where FinOps solutions make the difference by including every resource consumer into the cost-saving process.