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AWS Cost Optimization - 11 Tools and 11 Critical Best Practices
What Is AWS Cost Optimization? #
AWS cost optimization is the process of reducing AWS expenses without impacting performance, achieved through strategies like rightsizing instances, using optimal pricing models, and decommissioning unused resources. The aim is to ensure that every dollar spent on AWS aligns with your business objectives and delivers measurable efficiency.
AWS native tools for cost optimization include:
- AWS Cost Optimization Hub: A centralized dashboard that identifies, filters, and consolidates over 18 types of cost optimization recommendations, such as rightsizing, Graviton migration, and commitment-based saving recommendations. It helps quantify potential savings to prioritize actions across your AWS accounts.
- AWS Compute Optimizer: Analyzes your AWS resources (like EC2 instances, EBS volumes, and Lambda functions) using actual usage data and recommends how to right-size them for a better balance of performance and cost.
- AWS Trusted Advisor: Provides cost optimization checks, such as those for reserved capacity and idle resources.
- AWS Cost Explorer: Provides interactive charts and reports that help analyze historical AWS spending, identify cost drivers, and track usage patterns.
- AWS Budgets: Allows you to set custom cost and usage thresholds and receive alerts when actual or forecasted spend exceeds defined limits.
- AWS Pricing Calculator: Estimates the cost of planned AWS architectures by modeling service configurations and comparing pricing options.
This is part of a series of articles about cloud costs
In this article:
Why Should You Optimize Your AWS Costs? #
Optimizing AWS costs is crucial for aligning cloud usage with business goals while avoiding overspending. Without cost optimization, organizations risk inefficient resource allocation, runaway expenses, and a lack of visibility into how cloud services support their operations.
Here’s why cost optimization should be a priority:
- Avoid unnecessary spend: Identify and eliminate unused or underutilized resources such as idle EC2 instances, unattached EBS volumes, or low-utilization RDS databases.
- Maximize return on investment (ROI): Ensure every AWS service contributes directly to business value, improving the efficiency of cloud investments.
- Improve budget predictability: Implement budgeting and forecasting mechanisms to prevent cost surprises and enable better financial planning.
- Enhance operational efficiency: Use automation and monitoring to reduce manual interventions and improve resource utilization.
- Support scalability without waste: Align cost with usage by adopting auto-scaling and right-sizing strategies, enabling your infrastructure to scale dynamically without excess capacity.
- Enable accountability across teams: Implement tagging and cost allocation to give teams visibility and responsibility over their usage and spending.
- Leverage flexible pricing options: Take advantage of reserved instances, savings plans, and spot instances to reduce costs while maintaining required performance levels.
Related content: Read our guide to cloud cost optimization (coming soon)
AWS Native Cost Optimization Tools #
AWS Cost Optimization Hub #
AWS Cost Optimization Hub helps centralize and automate the discovery of optimization opportunities across your AWS environment. This tool consolidates findings from various AWS cost management services into a single dashboard, providing prioritized recommendations for actions such as rightsizing, removing idle resources, or purchasing savings plans. By providing a unified view, it simplifies cost reviews and accelerates execution of optimization strategies.
The Cost Optimization Hub is especially useful for organizations operating at scale, where managing hundreds of resources manually becomes cumbersome. It reduces the risk of missing cost-saving opportunities by automatically surfacing insights and actionable recommendations. Using this hub ensures that optimization initiatives are tracked, executed, and measured efficiently.
AWS Compute Optimizer #
AWS Compute Optimizer automatically analyzes your EC2 instances, auto scaling groups, EBS volumes, and Lambda functions to recommend optimal resource types and sizes based on actual utilization. It uses machine learning to identify over-provisioned or under-provisioned resources, suggesting changes that can reduce costs without impacting performance.
This tool enables teams to act on concrete data rather than guesswork. By aligning compute resources with real-world demand, organizations can avoid both wasted spend and performance bottlenecks. Compute Optimizer integrates directly into the AWS Management Console, making it accessible during day-to-day AWS resource management activities.
AWS Trusted Advisor #
AWS Trusted Advisor is a diagnostic tool that analyzes your AWS configuration and usage against best practices, including cost optimization, security, performance, and fault tolerance. For cost optimization, Trusted Advisor automatically identifies underutilized resources, unattached volumes, idle load balancers, and other inefficiencies, and provides clear recommendations to address them.
Beyond just cost savings, Trusted Advisor also helps reduce operational risks by highlighting potential security and availability issues. Its dashboard provides a quick status summary and detailed reports, expediting the remediation of expensive misconfigurations. Integrating Trusted Advisor checks into your regular review process helps maintain continual improvement in your AWS environment.
AWS Cost Explorer #
AWS Cost Explorer is a visualization tool that enables users to analyze and manage their AWS spending through interactive graphs and reports. It offers both high-level and detailed breakdowns of usage and costs, allowing teams to identify spending patterns, track historical trends, and visualize cost drivers across accounts or services. With customizable filters and grouping options, organizations can drill into cost data by service, region, tags, or other dimensions.
Cost Explorer also provides forward-looking features, including forecasting and recommendations. It integrates with other AWS billing tools and supports exporting cost and usage reports for deeper analysis. Regular use of Cost Explorer is essential for detecting anomalies, validating the impact of optimization efforts, and informing resource planning decisions.
AWS Budgets #
AWS Budgets gives users control over their cloud expenses by allowing them to create custom cost and usage budgets. You can set up alerts based on actual or forecasted spend, enabling quick intervention if your costs approach thresholds. This tool supports both cost and usage budgets, making it possible to monitor not only overall spending but also specific services, accounts, or projects.
Detailed variance analysis within AWS Budgets helps teams identify trends that might lead to budget overruns. It also integrates with AWS Cost Explorer, allowing users to investigate the reasons behind deviations from budget directly within the AWS ecosystem. Using AWS Budgets is a best practice for maintaining ongoing cost governance and accountability throughout the organization.
AWS Pricing Calculator #
AWS Pricing Calculator is an online estimation tool that allows you to model future AWS usage and project associated costs. You can input hypothetical scenarios for various AWS services, adjust configurations, and instantly see the price impact. This helps teams perform cost modeling before deploying workloads, supporting decisions on service selection, architecture, and scaling strategies.
The calculator also allows comparisons between on-demand, reserved, and spot pricing, making it easier to choose the most economical option for each workload. Its sharing functionality lets you generate detailed cost breakdowns for internal financial planning or external client proposals.
Beyond Native Tools: Third-Party AWS Cost Optimization Solutions #
1. CloudQuery #
CloudQuery is a third party solution that allows you to move data from your AWS account into the third party database of your choice. This makes it easy to combine information from AWS with company context that explains why your AWS spend patterns are the way they are. The CloudQuery Platform also offers a range of built-in reports that can quickly identify AWS spending anomolies and help you to keep your spending under control.
Key features Include:
- Runs entirely on your own infrastructure: If you choose the self-hosted version of CloudQuery, all syncs can be run on your own infrastructure, meaning no company data leaves the environment that you control.
- Flexible data movement: Combine data from AWS with data from any other system to ensure that your team has complete context on your AWS spending.
- Lightning fast syncs: Sync large amounts of information from AWS to the database of your choice in seconds.
- Integrates with your existing tech stack: CloudQuery's integration-based architecture and wide range of plugins means that it can slot easily into the tech stack you already use.
- Identification of cloud waste: CloudQuery makes it straightforward to use SQL or natural language to find unattached EBS volumes, superfluous RDS logging or other examples of cloud waste
2. Finout #
Finout offers a third-party solution for AWS cost optimization that requires no tagging changes or code modifications. It provides visibility into AWS spending across services, teams, and regions, making it easier to track, analyze, and control costs. Finout ingests cost data and turns it into actionable insights, helping teams manage their budgets and make decisions about cloud usage.
Key features include:
- Cost allocation without tagging changes: Allocate costs accurately across teams, regions, or environments using Finout’s Virtual Tags without modifying existing AWS resource tags.
- Custom dashboards and anomaly detection: Build tailored dashboards to monitor budgets and spending trends, with built-in tools for forecasting and detecting cost anomalies.
- Optimization insights via CostGuard: Identify and act on savings opportunities through recommendations for rightsizing, idle resource cleanup, and commitment management.
- Commitment management with My Commitments: Centralize and audit all AWS savings plans and reserved instances, with detailed analytics on utilization and coverage.
- Support for Amazon Bedrock cost management: Monitor and optimize costs associated with Amazon Bedrock using analytics and automated allocation tools.
3. Ternary #
Ternary is a dedicated AWS FinOps platform that gives organizations control over their cloud spending by combining cost transparency, team accountability, and intelligent optimization. Intended to handle the complexity of large cloud environments, it helps teams uncover cost-saving opportunities, manage commitments, and align financial and engineering goals.
Key features include:
- Visibility across AWS and beyond: Monitor AWS usage alongside services like Kubernetes, Snowflake, and Datadog for cost transparency.
- Cost allocation and labeling: Use custom labels to track spending by team, service, or environment without altering existing AWS tagging.
- Optimization recommendations: Detect and act on savings opportunities with intelligent suggestions for idle resources, oversized instances, and underutilized databases.
- Commitment lifecycle management: Oversee the lifecycle of reserved instances and savings plans to ensure cost efficiency over time.
- Team-level accountability and collaboration: Break down data silos by curating views and dashboards specific to each team’s needs, improving decision-making and planning.
4. CloudZero #
CloudZero is an AWS cost optimization platform focused on connecting cloud spend to business outcomes. Unlike traditional tools that rely heavily on tagging, CloudZero allocates AWS costs automatically, giving visibility into usage across teams, services, and business units.
Key features include:
- Cost allocation without tags: CloudZero’s CostFormation® technology maps AWS spend to products, teams, and features, even in environments with poor or inconsistent tagging.
- Business-aligned cost visibility: Break down cloud expenses by dimensions that matter to the business, like microservices, teams, or initiatives, for team-specific insights.
- Automated alerts and anomaly detection: Engineers receive notifications when spending spikes occur, allowing remediation before costs spiral out of control.
- Unit cost metrics: Identify inefficiencies and track the cost of delivering specific features or services using real unit costs rather than estimates or averages.
- Customizable spend analytics: Use standard and custom dashboards to explore AWS data in the context of business goals, making it easier to report on performance and track trends.
5. Holori #
Holori is a multi-cloud cost management and optimization platform intended to give organizations visibility and control over their AWS cloud expenses. It brings together cost data, infrastructure views, and optimization insights into a single interface, unifying FinOps and DevOps needs.
Key features include:
- Unified multi-cloud cost management: Visualize AWS, GCP, and Azure spending in one dashboard with centralized views for FinOps analysis and optimization.
- Dual interface for DevOps and FinOps: Switch between Grafana-style dashboards for metrics and a Drawio-like graphical interface for infrastructure visualization.
- Cost optimization recommendations: Identify unused resources, downsize over-provisioned instances, and activate savings plans to reduce AWS expenses effectively.
- Custom views and smart filters: Group and save segments of infrastructure for targeted cost tracking, reuse, and team-wide collaboration.
- Cost anomaly alerts: Detect and respond to unexpected spend increases with alerts delivered via Slack or email, using custom rules and thresholds.
10 AWS Cost Optimization Best Practices #
Here are some of the ways that organizations can improve their cost management strategy in AWS.
1. Implement Continuous Rightsizing #
Continuous rightsizing is the ongoing process of adjusting AWS resources, such as EC2 instances, databases, and storage, to match current workload requirements. Rather than set resources once and leave them, organizations should routinely analyze usage and resize resources as demands change. Tools like AWS Compute Optimizer and Trusted Advisor can automate recommendations, but regular reviews should also be a part of standard operations.
Ignoring rightsizing results in overprovisioned (and expensive) resources or underpowered systems that affect performance. Implementing continuous rightsizing makes cloud environments more agile and cost-effective, reducing waste caused by "set-and-forget" deployments.
2. Adopt a FinOps Culture Across Teams #
FinOps, or cloud financial operations, is a cultural practice that brings together engineering, finance, and business teams to collaborate on cloud spending. By fostering transparency and shared accountability, organizations can ensure that cost optimization becomes a collective responsibility rather than the sole concern of IT or finance. This involves regular communication, cross-functional cost reviews, and clear ownership of budgets.
Adopting a FinOps culture also includes establishing policies, processes, and education to help teams make informed decisions. Implementing a chargeback or showback model, providing self-service cost dashboards, and setting clear expectations for cloud usage all contribute to a sustainable FinOps practice.
3. Use Tagging and Cost Allocation Effectively #
Proper tagging of AWS resources is essential for effective cost allocation and granular visibility. By applying standardized cloud tagging for project, environment, department, or business owner, organizations can map every dollar spent to the right cost center. This supports chargeback, showback, and detailed reporting, helping leaders understand what drives cloud spending.
Effective tagging also enables automation and policy enforcement around cost optimization. For example, untagged or mis-tagged resources can be flagged for remediation, while reports can be generated to monitor spending by project or team. Regular auditing and refinement of tagging strategies keep cloud environments organized and cost-efficient, allowing organizations to react quickly to unexpected expenses.
4. Continuously Review Pricing Model Changes #
AWS regularly introduces new services, price reductions, and purchasing options, such as savings plans or instance families, that can impact the existing cloud spend. Organizations must stay informed about these changes and continually reevaluate their commitments and resource usage to ensure they are benefiting from the most favorable pricing.
This practice should involve periodic reviews—at least quarterly—where teams assess whether current pricing models align with actual usage and workloads. Automated alerting and cost analysis tools can assist by highlighting potential areas for savings when new pricing opportunities arise.
5. Automate Reporting and Governance #
Automated reporting is critical for maintaining visibility and control in fast-paced cloud environments. By scheduling regular, detailed cost and usage reports, organizations can proactively identify anomalies, enforce budgets, and ensure accountability without manual intervention.
Governance automation includes setting up rules and policies to enforce spending limits, tag compliance, and resource lifecycle management. Automated notifications and remediation actions further reduce the risk of costly oversights or non-compliance. Implementing rigorous reporting and governance routines builds the foundation for cost-aware cloud operations.
6. Leverage Reserved and Savings Plans #
Reserved instances and savings plans allow AWS users to commit to a certain level of usage over time in exchange for significant discounts compared to on-demand pricing. Identifying steady-state workloads and committing to appropriate reservation models can result in immediate, predictable cost savings. Both options offer flexibility in instance type, region, and payment schedule.
To maximize benefits, organizations should regularly review workload patterns, utilization rates, and expiration dates of reservations. Tools like AWS Cost Explorer and Trusted Advisor can recommend optimal coverage and purchasing opportunities. Being strategic with reservations and combining them with on-demand and spot capacity ensures flexibility and savings.
7. Optimize Data Transfer and Storage Costs #
Data transfer and storage are often overlooked cost drivers in AWS environments. Transferring data between regions, availability zones, or out to the internet can incur significant charges if not managed carefully. Reviewing architectural patterns and minimizing cross-zone or cross-region transfers can lead to substantial savings.
Storage optimization involves right-sizing volumes, selecting the appropriate storage class (such as S3 Standard vs. S3 Infrequent Access), and regularly removing unused or outdated data. Lifecycle policies and automation help ensure that backup and archival practices do not balloon costs over time. Consistent review of transfer and storage usage prevents silent accumulation of unnecessary expenses.
8. Turn Off Idle or Unused Resources #
Leaving resources running when they are not in use, such as development servers during non-working hours or abandoned test environments, is a common source of waste on AWS. Organizations should implement policies and automation to shut down, terminate, or deallocate resources outside business-critical windows.
Regular audits, tagging, and automated scheduling tools can help identify candidates for shutdown. Establishing clear guidelines, such as “no orphan resources”, reduces clutter, lowers the attack surface, and directly cuts unnecessary AWS spending. Conducting monthly clean-up exercises is a simple habit that can yield measurable returns.
9. Use Spot Instances for Non-Critical Workloads #
Spot instances offer access to spare AWS compute capacity at deep discounts, making them suitable for flexible, non-critical, or interruptible workloads. Implementing spot for suitable use cases, such as batch jobs, CI/CD pipelines, or data processing, can result in dramatic cost reductions. Automation tools can manage spot capacity allocation, instance replacement, and fallback strategies.
Teams should design workloads to be stateless or checkpointable, so that interruptions do not impact business operations. Monitoring spot market trends and integrating spot management features from AWS or third-party providers helps ensure reliability and maximizes the potential savings of this model.
10. Implement Cost-Aware Architecture Design #
Cloud-native architecture should always consider cost as a design constraint alongside performance, security, and scalability. This involves choosing services, regions, and availability models not only based on technical requirements but also based on cost efficiency. Serverless computing, containerization, and event-driven architectures can provide both agility and cost control.
Architectural reviews should include cost modeling and incorporate lessons learned from past billing data. By adopting modular, scalable, and cost-aware design principles, organizations avoid expensive architectural mistakes and maintain the flexibility to adapt to changing business needs while keeping spending in check.
11. Establish KPIs and Track Unit Economics #
Establishing key performance indicators (KPIs) tied to cloud usage helps quantify the value delivered per dollar spent. Rather than only monitoring total cloud spend, teams should track unit economics—metrics such as cost per user, cost per transaction, or cost per environment. These metrics connect AWS expenses to business outcomes, enabling data-driven decisions about scaling, investment, and optimization.
Using KPIs encourages performance accountability and helps identify inefficiencies. When a feature’s cost grows faster than its usage or revenue impact, teams can investigate architectural improvements or cost-saving opportunities. Integrating financial KPIs into engineering dashboards ensures that cost considerations remain visible during product development and scaling.