Top Cloud Cost Optimization Best Practices

Managing and optimizing cloud costs has become a critical aspect of business operations today. As the reliance on cloud services continues to grow, with public cloud spending predicted to reach $805 billion by 2025, effectively managing these expenditures becomes critical. Cloud cost optimization revolves around understanding and controlling the capital spent on cloud services to ensure maximum efficiency and effectiveness of the investments.

According to the Flexera 2024 State of the Cloud Report, 75% of organizations have reported a rise in cloud waste, with an average of 32% of cloud budgets underutilized. This trend underscores the challenges many companies face regarding visibility and resource management, which complicates effective control over cloud expenditures. Implementing best practices for cloud cost optimization is essential for these companies to manage and streamline their cloud spending efficiently.

What is Cloud Cost Optimization?

The goal of cloud cost optimization is to minimize the expenses associated with cloud computing services while preserving or improving performance. This involves adjusting spending to reflect genuine requirements without sacrificing service quality or performance. Reducing costs sometimes involves addressing overprovisioned cloud resources and eliminating unused instances.

Cloud cost optimization begins with a thorough assessment of your existing cloud infrastructure. This initial evaluation involves analyzing current resource usage, identifying underutilized or idle resources, and understanding your business operations' demand patterns. This step sets the foundation for identifying optimization opportunities and developing a strategy to align costs with actual needs while maintaining performance and service quality.

Cloud cost optimization is centered around several fundamental principles designed to help organizations manage and reduce their cloud expenses while maintaining or enhancing system performance. Key principles include right-sizing cloud resources to match demand, eliminating waste by removing unused or seldom-used cloud resources, ensuring cost visibility and accountability through proper resource tagging and monitoring, and auto-scaling to adjust resources based on demand.

As an example, let's examine Gartner's guidance framework for managing and optimizing the costs of public IaaS and PaaS:

"The logical flow between these five areas should not be interpreted as a mandate to implement them sequentially. Instead, organizations should apply an iterative approach and develop each area as independently as possible. Although there are obvious dependencies between areas, these shouldn’t block the development of subsequent capabilities. For example, you can start reducing your costs even if you don’t possess full visibility of your spending.

This framework is provider-neutral and can be applied to all major cloud providers, including AWS, GCP and Microsoft Azure. The described approach helps organizations develop a consistent multicloud governance model to achieve operational excellence in managing public cloud spending." — as outlined by Gartner

Cloud Cost Optimization Best Practices

As reliance on cloud solutions increases, implementing a cloud cost optimization strategy ensures operational performance while aligning expenses with actual usage patterns.

Let's have a look at the top best practices to help organizations manage and reduce costs efficiently:

1. Resource Management

Effective resource management is critical in optimizing cloud costs. A strategic approach involves regularly auditing the cloud environment to identify and decommission underused or idle resources and eliminate unnecessary cloud costs.

Regularly adjusting cloud services and resources to match usage helps prevent overprovisioning of cloud services.

The review of used resources includes analyzing their actual capacity and workload to find possible optimization possibilities. Thus, some resources can be scaled up or down to better fit the tasks they are aimed at. They can also be migrated to other resource types or alternative services, and loads can be split or combined—all to bring maximum performance for the most reasonable cost.

Analyzing infrastructure and detecting optimization possibilities is a complex task that needs to be performed regularly. Using cloud resource optimization tools like EPAM Syndicate RightSizer allows you to establish the process effectively and get the necessary result quickly with minimum risk of human error.

Key Priorities for Practitioners by Cloud Spend

"When the data are split by cloud spend, we see that reducing waste or unused resources remains at the top across spending tiers, but for lower spenders, the second priority is accurate forecasting of spend. This reflects the need to understand the trajectory of spending before it gets out of hand. For the highest spenders, accurate forecasting fell to the fifth position, likely reflecting their more mature forecasting capabilities. With forecasting established, full allocation of cloud spending rose to third spot for those spending $100M or more per year." — as outlined by FinOps.org

2. Workload Auto-Scaling and Scheduling

Implementing auto-scaling automatically adjusts the number and capacity of active servers based on real-time demand. This capability allows the cloud environment to scale up during peak usage times and scale down in lower traffic periods, thus optimizing cloud costs efficiently by aligning resource allocation with demand.

Implementing auto-scaling automatically adjusts the number and capacity of active servers based on real-time demand. Adding scheduling allows this system to adapt and anticipate changes proactively based on predictable usage patterns. By setting up schedules, the cloud environment can automatically scale up in anticipation of known high-load events like scheduled sales or product launches and scale down during predictably lower traffic periods, such as overnight hours.

This combination enhances the cloud environment's capability to optimize cloud costs efficiently by aligning resource allocation with real-time and forecasted demand, leading to smoother operations and potential performance improvements.

This flexibility allows for the dynamic provisioning and de-provisioning of cloud resources, enabling organizations to launch or terminate services as needed without maintaining unnecessary, costly infrastructure.

3. Cost Monitoring and Management

Effective budgeting and forecasting necessitate vigilant cost monitoring and management. Automated systems are configured to issue alerts when budget thresholds are reached, facilitating prompt and strategic responses. This automation is calibrated according to predefined budgets, business expectations, or the specific expectations of infrastructure owners for new initiatives.

Regular audits and reviews should be conducted to continuously monitor cloud usage and examine cost data, providing a clear view of cloud costs and revealing any discrepancies or wasteful spending.

Additionally, utilizing cloud cost optimization tools can significantly assist in tracking spending trends and identifying cost anomalies. These tools can also be configured to send alerts when expenses cross predefined thresholds, ensuring cloud budget compliance and preventing runaway costs.

Furthermore, it's crucial to regularly review cloud bill statements for anomalies, focusing on high-cost areas such as cloud computing, storage costs, databases, and end-user computing. This routine check helps catch unexpected charges early and rectify billing issues, thus maintaining control over cloud costs.

Anomalies are a priority: determining the root cause is speedy for most

"Time to detect has largely improved, primarily because of maturing native cloud tools and vendor solutions. (>10% are still trying to figure out how to detect and analyze anomalous spend.) Now the focus is on how much time it takes to determine the cause of the anomaly and implement a response. While the majority reported this takes less than a few days, for some this can take many weeks." — as outlined by FinOps.org

Effective cost monitoring and management are crucial in controlling spending and optimizing available environments in any cloud infrastructure. Handling these elements can become significantly more complex in multi-cloud environments, where different services and pricing structures across platforms require more nuanced management strategies.

Operating in a multi-cloud environment introduces challenges such as varying cost structures, diverse service agreements, and fluctuating pricing models across cloud providers. Managing compliance and security uniformly across these platforms further complicates the scenario, as each cloud infrastructure has unique configurations and inherent risks. Maintaining operational efficiency and optimizing costs across multiple clouds can also be daunting without centralized visibility.

Use Maestro to streamline cost monitoring and management in multi-cloud environments. This tool offers centralized management, providing a unified view of all cloud expenses and simplifying operational complexities. Maestro's compatibility with major cloud providers allows seamless management across different environments, and its user-centric design enables effective resource monitoring and analysis.

By employing Maestro, businesses can enhance visibility, ensure compliance, and optimize spending in multi-cloud setups, transforming complex cloud strategies into cost-effective operations.

4. Strategic Purchasing and Usage Practices

To maximize cost-saving potential, cloud providers should choose the appropriate cloud pricing model—on-demand, reserved, or spot instances—based on specific usage patterns. Understanding these models and selecting the right one ensures that resources are purchased at the best price and matched to consumption needs.

Discounts and savings plans can reduce cloud costs for predictable usage patterns.

Organizations operate continuously, unaffected by traditional peak and off-peak pricing strategies due to stable pricing policies. Therefore, utilizing heat maps to track usage patterns may not yield benefits in terms of cost optimization through off-peak scheduling. Instead, businesses should optimize their cloud resource usage based on current performance needs and constant cost assessments to maintain operational efficiency, irrespective of time-based pricing changes.

5. Design and Deployment

When it comes to modernizing applications for the cloud, opting for cloud-native designs is far more advantageous than merely lifting and shifting on-premises applications. Cloud-native applications are designed to harness the full range of cloud efficiencies, including autoscaling, managed services, and dynamic resource allocation.

This approach allows organizations to build scalable and resilient applications, adapting seamlessly to changing demands and reducing costs by utilizing resources more efficiently. By embracing cloud-native design principles, businesses can create future-proof systems that use cloud technology's best capabilities for sustainable, long-term success.

6. Data and Transfer Management

By strategically overseeing data movements, organizations can significantly reduce the expenses associated with data transfer and ensure efficient data lifecycle management. This involves careful planning and execution of when and how data is moved between different environments or across availability regions, taking advantage of less costly data transfer options and avoiding unnecessary or redundant data transfers. Implementing such strategies helps reduce overhead costs and enhances the overall data handling efficiency within the cloud environment.

7. Promoting a Cost-Aware Culture

By building a dedicated FinOps team, companies can ensure focused education on the importance of cloud cost awareness, including training on tools and resources offered by cloud providers, fostering a cost-efficient management environment. This team plays a crucial role in developing and implementing cost-effective practices, making strategic decisions that align with organizational financial goals, and improving an environment where cost-efficiency is a shared responsibility. This collaborative approach helps minimize unnecessary costs and maximizes the overall ROI in cloud services.

Role of FinOps in Cloud Cost Optimization

FinOps is an evolving cloud financial management discipline that combines systems, best practices, and culture to increase an organization's ability to understand cloud costs and make informed business decisions. FinOps is indispensable in balancing and optimizing cloud services' cost, quality, and value in cloud computing, where expenses are variable and can scale quickly.

Key Aspects of FinOps in Cloud Cost Optimization:

1. Cost Visibility and Accountability: FinOps promotes a deep understanding of cloud spending across all departments and ensures that every dollar spent is tracked and attributed correctly. This visibility allows organizations to see who spends what, thus encouraging responsible spending and preventing budget overruns.

2. Real-Time Decision Making: One of FinOps's core principles is enabling real-time business decision-making based on cloud usage and financial data. This agility is crucial for businesses that adapt quickly to market changes or adjust their strategies based on performance and operational metrics.

3. Cross-Functional Collaboration: FinOps brings professionals from IT, finance, and business units to collaborate on cloud spending decisions. This ensures that financial and operational objectives are aligned, thus improving efficiency and effectiveness in cloud investments. For instance, while IT might focus on performance and resilience, finance can provide insights into expenditure and budget alignment, ensuring optimal decision-making.

4. Optimization and Improved ROI: Through continuous monitoring and analysis, FinOps helps organizations use their cloud resources better, scaling up or down based on need rather than static predictions. This dynamic management allows for significant cost savings and improved ROI by aligning spending with actual use and business value created.

5. Benchmarking and Performance Metrics: FinOps utilizes benchmarks and KPIs to measure and manage the efficiency of cloud spending. By comparing performance against industry standards or past internal data, companies can identify areas for improvement and recognize opportunities for cost optimization.

A complex review of infrastructure against benchmarks and KPIs can be performed automatically. EPAM Syndicate Rule Engine offers a comprehensive, detailed infrastructure assessment against different standards, requirements, and rulesets. It covers hundreds of security, compliance, utilization, and cost-effectiveness rules, covering world-known standards like GDPR, PCI DSS, CIS benchmark, and many others. It also allows rule customization and creating your own rule sets—all that makes the assessment perfectly fit the needs of your specific business.

How to Monitor Cloud Expenses

Organizations must develop strategies that provide depth and breadth in their analysis to monitor cloud expenditures effectively. This involves using various cloud cost management tools and methodologies to offer real-time insights and historical data analysis. Here’s a short description of how comprehensive monitoring approaches can be implemented:

1. Usage Monitoring:

• Purpose: Usage monitoring helps track real-time resource usage in the cloud, ensuring efficient utilization and identifying cost-saving opportunities.

• Tools: For detailed insights and comprehensive infrastructure management, use native tools like AWS CloudWatch, Google Cloud Operations, and Azure Monitor or third-party options like Datadog and Prometheus.

• Implementation: Set up monitoring tools to track critical metrics, configure alerts for unusual activities, and create dashboards to visualize usage trends easily. Regularly revisit and adjust monitoring configurations to align with changing business needs.

2. Historical Data Analysis:

• Purpose: Helps understand trends, seasonal impacts, and long-term usage patterns to optimize future cloud spending and budgeting.

• Tools: Cloud cost management tools like AWS Cost Explorer and Microsoft Power BI can effectively analyze historical data. These cost management tools help create detailed reports that illustrate spending trends and identify potential areas for cost reduction.

• Implementation: Regularly review historical spending data, compare it with operational milestones, and adjust future forecasts and budgets based on these insights.

3. Cost Allocation Tags and Cost Categories:

• Purpose: Facilitate detailed tracking and categorizing cloud expenditures by department, project, or specific identifier. This enhances accountability and aids in precise budget tracking. Tags label resources for expense attribution, while cost categories group these resources into logical, manageable clusters.

• Tools: Most cloud providers, such as AWS, Azure, and Google Cloud, support tagging resources. This can be coupled with cost management tools that help report and analyze tagged data.

• Implementation: Implement a consistent tagging strategy across all resources. Use the tagged data to allocate costs accurately and generate precise billing reports for stakeholders.

4. Budgeting and Forecasting:

• Purpose: Enhance financial control by alerting stakeholders about budget thresholds and forecasting future cloud needs to align operations and spending.

• Tools: Use cloud-specific tools like AWS Budgets and Google Cloud Budgets and forecasting tools like AWS Forecast and Google Cloud's BigQuery. Third-party tools like CloudCheckr add granularity in alerts and deeper analytics.

• Implementation: Set budgets for projects or departments with automated alerts for critical thresholds. Develop and regularly update budget forecasts based on historical data and anticipated needs. Involve C-level executives in planning and resource allocation to ensure alignment with strategic goals.

5. Custom Dashboards:

• Purpose: Provides a centralized view of all cloud spending data tailored to the organization's needs.

• Tools: Visualization tools like Grafana and Tableau and cloud provider-specific services like AWS QuickSight can help you create custom dashboards.

• Implementation: Design dashboards that reflect the metrics most relevant to the organization’s cost optimization goals. Update dashboards regularly to reflect new data sources or changing business priorities.

6. Cost Anomaly Detection:

• Purpose: Identifies irregular spending patterns that could indicate misconfigurations, unused resources, or security issues leading to unexpected costs.

• Tools: Advanced machine learning models provided by platforms like AWS Cost Anomaly Detection focus on spotting outliers in spending patterns.

• Implementation: Set up cost anomaly detection on all significant resources. Customize the sensitivity based on the organization's typical cloud usage variations.

Common Mistakes in Cloud Cost Management

Addressing common pitfalls in cloud cost management helps organizations optimize their resources effectively and avoid waste and inefficiencies that can unnecessarily inflate expenses.

Here’s a list of commonly observed mistakes that companies should try to avoid and solutions to overcome these pitfalls:

1. Lack of a Structured Review Process and Cost Monitoring

Without a structured process for reviewing cloud costs and usage, expenditures can grow unchecked. This oversight often occurs because companies do not have a dedicated team focusing on FinOps or fail to audit their cloud infrastructure regularly.

Solution: Implement regular audits and reviews, possibly monthly or quarterly, to identify wasteful spending and areas.

2. Poor Planning

Insufficient planning in cloud infrastructure utilization can encompass inadequate budgeting and a lack of precise evaluation regarding virtual infrastructure deployment and technical services. This often results in inefficiencies and unoptimized uses of resources that could otherwise be better allocated or adjusted.

Solution: Invest in thorough planning phases before deploying cloud resources. Use forecasting tools and detailed needs assessments to ensure adequate and targeted budget allocations. Regularly review and adjust plans based on actual usage and changing business needs to avoid over-provisioning or underutilizing resources.

3. Lack of Resource Ownership

Deploying various workloads without adequate tagging or adherence to established schemes or policies can lead to resource ownership confusion. This is particularly common three months after deployment, when numerous services may be active. Yet, who is responsible for them remains unclear, and why costs are incurred is unclear. If resources are carelessly removed, this could disrupt operational functionalities. Hence, establishing clear resource ownership is crucial to effectively managing and optimizing service usage.

Solution: Implement a comprehensive tagging strategy for all cloud assets from the outset of deployment. Tags should include the owner (department or individual), purpose, and associated project or cost center. Enforce policies that no resources can be deployed without appropriate tagging and regular reviews to ensure compliance.

4. Poor Data Transfer Management

Data transfer fees can be unexpectedly high, especially when moving data frequently between regions or in and out of cloud environments. Companies often do not consider these costs thoroughly in their planning phases, leading to significant overages.

Solution: To manage and reduce data transfer costs effectively, it's advisable to implement a comprehensive data transfer optimization strategy. This includes thoroughly reviewing and optimizing the infrastructure topology to minimize unnecessary data movements and strategically using data transfer reservations to secure lower rates wherever possible.

5. Underutilization of Instances

Many companies purchase reserved instances to save money, as these often come at a discounted rate compared to on-demand pricing. However, a common pitfall is not fully utilizing these reserved capacities due to overestimation of needs or changes in the project scope. This results in paying for unneeded resources, thus contrary to the initial intention of cost savings. Companies need adept forecasting and regular review of usage versus reservation to mitigate this issue.

Solution: Сonduct a correct analysis of infrastructure consumption, considering many factors. Compare budgets and plans for each workload for at least one year. Analyze run rate and purchase granularly with time shifts.