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Cloud Cost Optimization: Strategies for Efficient Resource Management

Optimizing cloud costs involves more than just cost reduction, it also entails cost alignment with company goals. If costs are going up and revenues are going up, that's not necessarily an adverse outcome. Ensuring that costs correlate with profitable and productive activities is one of the most essential objectives in cloud cost optimization . 

Methods 

Review Pricing- Paying for unnecessary resources can be avoided by understanding the cost of the cloud and by informed spending decisions. Knowing the costs involved with the services help to avoid picking an arbitrary amount. 

Identifying idle & underutilized resources- Cloud costs can be easily optimized by looking for temporary and idle resources. Developers and administrators sometimes provision a temporary server for a certain task which should be de-provisioned when not in use any longer. Unused resources result in inflated AWS or Azure expenses that charge for resources the organization purchased but no longer uses. 

Right-sizing the resources- Methods to right-size resources involves evaluating CPU, memory, and storage usage to identify overprovisioned or underutilized instances. Overpowered or underpowered configurations can be avoided by selecting instance types according to workload needs. 

Review Instances- Amazon Web Services (AWS), a cloud service, offers Reserved Instances (RI), a cost-saving option. They allow to reserve a certain amount of capacity for a particular cloud service (such as virtual machines, storage, or databases) for a period, usually 1 or 3 years.

Leverage spot instances- A spot Instance is an unused Amazon EC2 instance that is available for less than the On-Demand price. However, because they aren't always accessible and can sell out rapidly, these situations are unreliable. Spot Instances are helpful for batch processes or processes that can be terminated right away, but not for crucial, time-consuming processes. 

Implementing Automation- Automation tools and scripts can help manage and optimize cloud resources dynamically. Auto-scaling, for instance, adjusts the number of instances based on demand, preventing overprovisioning during low usage periods and reducing costs. Autoscaling can be the solution to allowing for both cost- reduction and efficient resource optimization. Auto scaling allows to dynamically adjust the quantity of computing resources, based on actual usage. Autoscaling is particularly useful for unpredictable and mission-critical workloads. Instead of keeping resources idle during low usage periods, or hitting capacity during high usage, autoscaling ensures that the right services are used at the right time.

Opting for the right storage type- Most cloud vendors offer various storage classes within block and object storage, ranging from high-performance to low-cost tiers. Choose the one that fits your data’s performance requirements and access frequency.