List of the Top 9 Cloud Cost Management Software for Amazon EKS in 2025

Amazon CloudWatch acts as an all-encompassing platform for monitoring and observability, specifically designed for professionals like DevOps engineers, developers, site reliability engineers (SREs), and IT managers. This service provides users with essential data and actionable insights needed to manage applications, tackle performance discrepancies, improve resource utilization, and maintain a unified view of operational health. By collecting monitoring and operational data through logs, metrics, and events, CloudWatch delivers an integrated perspective on both AWS resources and applications, alongside services hosted on AWS and on-premises systems. It enables users to detect anomalies in their environments, set up alarms, visualize logs and metrics in tandem, automate responses, resolve issues, and gain insights that boost application performance. Furthermore, CloudWatch alarms consistently track metric values against set thresholds or those created by machine learning algorithms to effectively spot anomalies. With its extensive capabilities, CloudWatch is a crucial resource for ensuring optimal application performance and operational efficiency in ever-evolving environments, ultimately helping teams work more effectively and respond swiftly to issues as they arise.

StormForge delivers immediate advantages to organizations by optimizing Kubernetes workloads, resulting in cost reductions of 40-60% and enhancements in overall performance and reliability throughout the infrastructure. The Optimize Live solution, designed specifically for vertical rightsizing, operates autonomously and can be finely adjusted while integrating smoothly with the Horizontal Pod Autoscaler (HPA) at a large scale. Optimize Live effectively manages both over-provisioned and under-provisioned workloads by leveraging advanced machine learning algorithms to analyze usage data and recommend the most suitable resource requests and limits. These recommendations can be implemented automatically on a customizable schedule, which takes into account fluctuations in traffic and shifts in application resource needs, guaranteeing that workloads are consistently optimized and alleviating developers from the burdensome task of infrastructure sizing. Consequently, this allows teams to focus more on innovation rather than maintenance, ultimately enhancing productivity and operational efficiency.

For businesses leveraging a contemporary, multi-cloud environment to enhance their SaaS customer experience, Yotascale offers dynamic cloud cost management characterized by exceptional insights, precision, and rapid implementation, enabling reductions in cloud expenses by as much as 50%. In contrast to earlier solutions that often prove difficult to navigate and configure, failing to provide timely and proactive insights, Yotascale consistently delivers tangible benefits from the outset and continues to provide value daily by empowering the right stakeholders to make informed decisions promptly, thus managing cloud expenses effectively. Yotascale simplifies the process for teams to take control of their cloud financials through highly accurate, 95% precise cost allocation that aligns with existing business practices; comprehensive support for various multi-cloud platforms and container technologies (spanning Kubernetes, ECS, AKS, and more); along with actionable, scenario-driven recommendations tailored to applications, services, and workloads, making the task of optimizing cloud expenditures straightforward, efficient, and predictable. This approach not only enhances cost efficiency but also fosters a culture of accountability within teams, ensuring that cloud spending aligns with strategic objectives and financial goals.

CAST AI dramatically lowers your computing expenses through automated management and optimization strategies. In just a matter of minutes, you can enhance your GKE clusters with features like real-time autoscaling, rightsizing, automated spot instance management, and the selection of the most cost-effective instances, among others. With the savings forecast provided in the complimentary plan, you can visualize your potential savings through K8s cost monitoring. By enabling automation, you'll receive reported savings almost immediately while ensuring your cluster remains finely tuned. The platform is designed to comprehend your application's requirements at any moment, applying real-time adjustments to maximize both cost-efficiency and performance, going beyond simple recommendations. By leveraging automation, CAST AI minimizes the operational expenses associated with cloud services, allowing you to concentrate on developing exceptional products rather than managing cloud infrastructure concerns. Organizations that implement CAST AI experience improved profit margins without increasing their workload due to more efficient engineering resource utilization and enhanced oversight of cloud environments. Consequently, CAST AI clients typically enjoy an impressive average savings of 63% on their Kubernetes cloud expenses, illustrating the tangible benefits of optimization. This results in a more streamlined operational process, underscoring the value of adopting such an innovative solution.

Sedai adeptly locates resources, assesses traffic trends, and understands metric performance, enabling continuous management of production environments without the need for manual thresholds or human involvement. Its Discovery engine adopts an agentless methodology to automatically recognize all components within your production settings while efficiently prioritizing monitoring data. Furthermore, all your cloud accounts are consolidated onto a single platform, allowing for a comprehensive view of your cloud resources in one centralized location. You can seamlessly integrate your APM tools, and Sedai will discern and highlight the most critical metrics for you. With the use of machine learning, it automatically establishes thresholds, providing insight into all modifications occurring within your environment. Users are empowered to monitor updates and alterations and dictate how the platform manages resources, while Sedai's Decision engine employs machine learning to analyze vast amounts of data, ultimately streamlining complexities and enhancing operational clarity. This innovative approach not only improves resource management but also fosters a more efficient response to changes in production environments.

Pepperdata's autonomous, application-level cost optimization achieves significant savings of 30-47% for data-heavy tasks like Apache Spark running on Amazon EMR and Amazon EKS, all without requiring any modifications to the application. By utilizing proprietary algorithms, the Pepperdata Capacity Optimizer effectively and autonomously fine-tunes CPU and memory resources in real time, again with no need for changes to application code. The system continuously analyzes resource utilization in real time, pinpointing areas for increased workload, which allows the scheduler to efficiently allocate tasks to nodes that have available resources and initiate new nodes only when current ones reach full capacity. This results in a seamless and ongoing optimization of CPU and memory usage, eliminating delays and the necessity for manual recommendations while also removing the constant need for manual tuning. Moreover, Pepperdata provides a rapid return on investment by immediately lowering wasted instance hours, enhancing Spark utilization, and allowing developers to shift their focus from manual tuning tasks to driving innovation. Overall, this solution not only improves operational efficiency but also streamlines the development process, leading to better resource management and productivity.

Zesty offers a cloud infrastructure optimization platform that effectively addresses the needs of databases, storage, and computing, while also assisting businesses in lowering their cloud expenditures. Utilizing advanced machine learning and automation, Zesty empowers FinOps and DevOps teams with valuable insights tailored for real-time applications, ensuring that cloud resources are utilized in the most efficient manner possible. The Zesty Commitment Manager further enhances this by automating the optimization of EC2 discount plans and RDS, maximizing financial benefits while minimizing risks. Additionally, Zesty Disk intelligently adjusts EBS volumes based on the dynamic needs of applications, leading to improved storage efficiency, reduced downtime, and potential cost savings of up to 70%. Furthermore, Zesty Insights provides a comprehensive overview of possible savings, identifies unused resources, and delivers practical recommendations to help organizations prioritize their cost-saving efforts effectively. By leveraging these innovative tools, companies can significantly enhance their cloud management strategies and drive greater operational efficiency.

Each module can function on its own or in combination to form a robust integrated pipeline that encompasses Continuous Integration (CI), Continuous Deployment (CD), and Feature Flags. All Harness modules leverage the capabilities of AI and machine learning to enhance their performance. Our algorithms are designed to verify deployments, pinpoint opportunities for test optimization, suggest recommendations for cloud cost savings, and restore the system to its previous state in the event of a rollback. They also play a crucial role in facilitating complex deployment patterns, identifying anomalies in cloud costs, and initiating a variety of other tasks. Staring at dashboards and logs post-deployment can be tedious; let us handle the monotonous tasks for you. Harness systematically evaluates the logs, metrics, traces, and other relevant data from your observability systems to assess the health and status of each deployment. If a problematic deployment is identified, Harness is capable of automatically reverting to the most recent stable version, ensuring a seamless experience for users. This automation not only saves time but also minimizes the risk of human error during critical deployment processes.

CloudNatix offers a robust solution that effortlessly integrates with any infrastructure, whether located in the cloud, a physical data center, or at the network's edge, accommodating a wide range of platforms such as virtual machines and both self-managed and managed Kubernetes clusters. By merging your dispersed resource pools into a single, scalable cluster, this service is accessible through an intuitive SaaS model. Users are provided with a global dashboard that delivers a comprehensive overview of expenses and operational metrics spanning multiple cloud and Kubernetes platforms, including AWS, EKS, Azure, AKS, Google Cloud, GKE, and additional services. This all-encompassing perspective allows for an in-depth examination of each resource, encompassing individual instances and namespaces across different regions, availability zones, and hypervisors. In addition, CloudNatix promotes a streamlined cost-attribution system that transcends public, private, and hybrid cloud environments, along with various Kubernetes clusters and namespaces. The platform also automates the allocation of costs to specific business units according to your preferences, enhancing the financial management process within your organization. This level of integration not only simplifies oversight but also equips businesses with the tools needed to maximize resource efficiency and strategically refine their cloud initiatives. Ultimately, such capabilities provide organizations with a significant advantage in navigating the complexities of modern cloud management.