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6 Best Cloud Cost Management and Cloud Optimization Solutions for Azure, AWS, and Google Cloud – February 2024 Comparison

Dave Hanson

Dave Hanson

DevOps and Cloud Architect

Best platform

Too busy for the full read? Here’s the BEST cloud cost management and cloud optimization solution for Azure, AWS, and Google Cloud.

CAST AI – an autonomous cloud optimization solution embracing the full power of automation to guarantee massive savings.

Scaling cloud resources has never been that easy – so easy that many teams end up losing control over their expenses. A bug or unplanned issue can turn into a hefty bill at the end of the month.

That’s why engineering teams need a cloud cost management and optimization toolkit that provides detailed visibility, exhaustive reporting, and, ideally, automated optimization features. In this post, we explore and compare some of the top tools you can use to get on top of your cloud bill.

Cloud cost management embraces monitoring, reporting, visibility, allocation, budgeting, and forecasting costs related to public cloud resources. It’s about learning where these expenses come from, to which teams they can be allocated, and how much you’re likely to spend in the future. 

On the other hand, cloud cost optimization is about identifying mismanaged resources and performing activities to eliminate waste and reduce your overall cloud spend. It may involve strategies such as rightsizing resources, shutting down unused instances, taking advantage of spot instances, and more.

Finding the right cloud cost management and optimization solution can be tricky, as multiple vendors offer various features, pricing models, and use cases. To save you time and hassle, our team has researched and reviewed tools that help you get on top of your cloud spend.

TL;DR

All solutions discussed below offer much value to teams looking to optimize their cloud bills and streamline cloud cost monitoring, allocation, and reporting processes.

However, our ultimate choice is CAST AI, mainly because it goes beyond cost monitoring and reporting and brings automated optimization features.

No time to read?

Catch our summary of the best cloud cost management and optimization tools in 2023

Unless stated otherwise, all cloud cost management and optimization solutions covered below are compatible with top public cloud providers – AWS, Google Cloud, and Microsoft Azure.

Here’s what makes each of them stand out:

  1. CAST AI – an autonomous cloud optimization solution embracing the full power of automation to guarantee massive savings.
  2. Spot by NetApp – a cloud optimization solution achieving significant savings and improvements thanks to automating spot instances.
  3. Harness – a cloud management module and BI tools focused on cost transparency, optimization, and governance with some automation features.
  4. Apptio Cloudability – financial management tools for monitoring, allocating, and analyzing cloud costs supporting multi-cloud and automating specific tasks.
  5. Cloudcheckr – detailed cloud cost reporting, allocation, and optimization recommendations for manual implementation.
  6. Kubecost – a comprehensive Kubernetes cost management solution teams can use for improved visibility, allocation, and real-time alerts.

FeatureCAST AI Spot.ioHarnessCloudabilityCloudcheckrKubecost
Supported platforms
AWS
Google Cloud
Microsoft Azure
Cost allocation and visibility
Detailed cost allocation
Automated cost forecasting N/AN/AN/AN/A
Cost reporting N/A N/A
Cost view across multi-cloud
Real-time alerts N/AN/AN/A
Cost optimization and automation
Rightsizing
Recommendations for instance types and sizes N/AN/AN/AN/A
Automated rightsizing
Multi-shape cluster construction N/AN/AN/A
Autoscaling
Automated pod scaling parameters N/AN/AN/A
Horizontal pod autoscaling
Node autoscaling
Cluster scheduling and termination N/A
Automatic bin packing
Spot instance automation
Full multi cloud optimization

CAST.AI – Automated Kubernetes Cost Optimization and Management

CAST AI is a cloud-native autonomous platform for analyzing, monitoring, and optimizing Kubernetes environments. Its automation features include rightsizing, autoscaling, cluster scheduling, spot instances, and more.

Pros

CAST AI splits cloud costs into project, cluster, namespace, and deployment levels. Your team can track expenses down to individual microservices and then produce a full estimate of your cluster costs. Its cost allocation works on a per cluster and per node basis. CAST AI also makes it easier to view and allocate costs in multi-cloud setups.

Powered by automation, CAST AI chooses optimal resources for your application’s requirements while reducing costs. When a cluster needs extra nodes, the platform’s automation engine selects the best performing instances at the lowest cost. By automating multi-shape cluster formation and rightsizing, it helps to make the right choices and avoid overprovisioning.

Users also benefit from CAST’s multiple autoscaling features. For instance, Horizontal Pod Autoscaler generates an optimal number of required pod instances. It then scales the replica count of your pods up and down and removes all pods if there’s no work to be done. CAST AI can also automatically pause and resume clusters so that you avoid paying for resources you don’t use. It also employs automated bin packing to maximize savings.

CAST AI allows you to achieve significant cost reductions with spot instance automation. You don’t have to worry about running out of capacity, as the platform continuously looks for the best alternatives.

Finally, the platform offers a variety of multi-cloud features. For instance, its Active-Active Multi-Cloud automatically distributes apps and replicates data over several cloud services to ensure business continuity in case of any failures. It also distributes traffic across all clouds your team uses, always selecting up and healthy endpoints.

Cons

Sounds too good to be true?

While CAST AI focuses on automating important cloud optimization tasks, it might not be a good match for teams looking for in-depth cost reporting and recommendations for manual implementation.

One feature that is certainly missing is real-time alerts informing you when your spending exceeds the budget and reducing the odds of an out-of-control bill. However, the vendor announced plans to add such functionality.

Final verdict

CAST AI is an interesting option for teams interested in automating cloud cost management and optimization to generate savings without any additional work for engineers.


Spot by NetApp – Optimizing the Cloud with Spot Instances

Spot.io is a cloud cost management solution that optimizes cloud costs thanks to spot instance automation. The platform automatically secures spot capacity for workloads, helping to cut costs and ensure high availability.

Pros

Spot.io breaks down the infrastructure costs of clusters and offers insights into each layer. You can break down expenses into namespaces and individual workloads within every namespace, and you can further filter them.

For each workload, you get both compute and storage costs. You can use this data to analyze your application costs, perform chargebacks without extensive resource tagging, and estimate future cloud spend.

Spot.io offers a handy rightsizing recommendation mechanism. The tool monitors workload utilization in real-time, providing you with recommendations for manually adjusting the resource requirements, both per container and the entire workload. This allows for easier high-level visualization and quicker implementation.

Spot.io continuously checks for unschedulable pods. If it finds one, it scales your infrastructure up to ensure that all your pods have a place to run. In addition, Spot.io prioritizes downscaling the least utilized nodes and automatically removes them if it detects that it’s possible to move all pods running on them. In the case of scale-down or instance replacement, Spot.io terminates all pods and nodes.

Spot.io generates even more savings thanks to bin-packing algorithms. When it identifies an instance with workloads that can be distributed across the cluster, it triggers a scale-down to drain and terminate the instance. It lets you run clusters on spot instances without having to provision or scale instances.

Cons

The tool reduces cloud costs thanks to its focus on spot instances. That’s why its recommendations mostly revolve around running workloads on more spot instances, potentially missing out on other cloud cost optimization opportunities, which may generate even more savings. One of such areas is rightsizing, currently not automated in Spot.io.

As valuable as it is for managing spot instances in single cloud infrastructure, Spot.io currently doesn’t support multi-cloud functionality. It also provides no visibility across its solutions for containerized applications.

Final verdict

Spot.io is an excellent choice if your team wants to delve into more efficient use of spot instances. However, while this may be a great source of savings, at some point, you may discover that in particular situations, other optimization methods may deliver better results.

That’s why you may be better off with a platform capable of automatically analyzing workload requirements and matching them with optimal cloud resources.


Harness – Automated Cloud Cost Management For Improved Transparency, Optimization, and Governance

Harness.io is a continuous delivery and integration platform with a cloud cost management module and Business Intelligence tools focused on improving cost transparency, optimization, and governance.

Pros

Harness brings in-depth Kubernetes visibility by displaying the utilized, idle, and unallocated resources per workload and cluster. It visualizes cost information by projects, teams, business units, departments, and more. Additionally, Harness allows you to create periodic reports on your crucial cost and usage metrics. Governing cloud usage becomes easier with Harness thanks to its custom budgeting, forecasts, and accounts for cost showbacks and chargebacks.

Harness offers in-depth reporting and practical cloud optimization suggestions. These may involve cluster utilization, rightsizing, autoscaling, cleaning underutilized or orphaned resources, but also picking the optimal cloud service tier based on your usage trends. Before implementing the recommendations, Harness lets you run a what-if analysis.

The platform enables you to set budgets and keep track of expense variations. In addition, Harness continuously monitors your usage and alerts you when your consumption diverges from the expected levels, which is possible thanks to analyzing your historical spend trends.

Harness allows you to stay on top of cost and usage across your multiple-cloud resources. The tool displays insights on custom, data-driven dashboards to help track resources across every public cloud provider your team uses.

The platform embraces the power of spot instances. Harness users can run workloads on fully orchestrated spot instances without having to worry about interruptions. The platform handles this part smoothly.

Finally, Harness offers a range of automated cloud cost management and optimization features. For example, AutoStopping can automatically turn off non-production resources whenever they’re not in use. Harness provides cost information about your apps, services, and environments without the need for human tagging, reducing both the time and effort teams would need for this task.

Cons

Harness provides excellent cost allocation and visibility across multi-cloud setups.

However, as valuable as these insights are, you still need to implement them manually, as the platform doesn’t support full multi-cloud cost optimization. It also misses important cloud optimization and automation features such as autoscaling, rightsizing, and spot instance use.

Final verdict

Harness is perfect for companies looking to get in-depth recommendations about their cloud use and expenses across multiple clouds. However, due to limited automation capabilities, platform users need to have resources to optimize their infrastructure manually.


Apptio Cloudability – Powerful Insights for Cloud Cost Optimization and Multi-Cloud Automation

Cloudability offers robust financial management tools for monitoring, allocating, and analyzing public cloud costs. You can use it to track your cloud expenses, make better-informed cloud budget decisions, and automate some cloud optimization tasks.

Pros

Cloudability detects and monitors cloud resource consumption, helping teams balance risk and cost and reduce waste. The tool collects your usage data from the last 10 to 30 days and uses its algorithms to create rightsizing suggestions for your resources.

Cloudability lets you create custom dashboards for various products, departments, or roles within your organization. The solution’s True Cost Explorer enables visual exploration of cloud costs and used data. You can easily connect your use and expenses to relevant data dimensions such as business units, apps, and teams.

The tool helps you quantify the ROI of spot instances and offers other cloud optimization recommendations. As a result, your team can create a more consistent budget and a baseline for forecasting in the future.

Budgeting for multi-cloud configurations is challenging, but Cloudability makes it a lot easier. Users can display multi-cloud data together in a single pane of glass. All data is continuously refreshed with each new update from service providers.

Another benefit of Cloudability is its use of automation in several areas. First, you can set up and schedule daily cleanups of detached EBS volumes. The tool can automatically shut down operations during periods of low usage. It also lets users schedule the scaling of ASGs or the stopping/starting of EC2 and RDS instances, checking how many resources this will affect.

Cons

While Cloudability offers excellent cloud cost management features and data-rich dashboards, its multi-cloud optimization and automation capabilities are limited. It’s certainly a head start over other solutions in this product category.

However, its range of automation may be too narrow to guarantee the expected cost savings and streamline work with Kubernetes.

Final verdict

Cloudability is a great option for small and mid-sized companies looking for a solution that tracks and analyzes cloud costs, provides actionable insights, and automates their implementation. Larger organizations with more complex processes and infrastructure may require more advanced automation features.


Cloudcheckr – Cloud Cost Management and Visibility Insights and Recommendations

CloudCheckr is a cloud management tool focused on reporting and creating recommendations for cost optimization. While the platform started as a cloud security tool, it was later expanded with cost management, tracking, optimization, and resource inventory solutions.

Pros

CloudCheckr offers a detailed view of cloud cost allocation data, granting you instant visibility into expenses across resources from all top cloud service providers. Its reports display cloud costs over time in a monthly format, allowing your team to interact with the data and improve your billing accuracy. Alerts paired with cloud governance will give your team more control and help to avoid costly surprises.

CloudCheckr generates resource purchasing recommendations thanks to predictive analytics. By identifying wasted resources and providing resource resizing recommendations, the platform can help you reduce costs. The solution performs hundreds of checks for idle resources, unused instances, mismatches in reserved instances, and more. However, the engine generates recommendations only for rightsizing and snapshot cleanups.

Teams relying on reserved instances should pay attention to CloudCheckr’s Savings Plan Recommendations report. It helps to check which services they deployed could be covered by their Savings Plans and create or customize purchase recommendations.

Although CloudCheckr focuses on policy-based cloud management, it still delivers some interesting automation features. The platform automatically re-allocates, resizes and modifies reserved instances. Thanks to storing historical data on RI inventory, it supports teams in making future purchases. CloudCheckr automatically enforces tag-or-terminate policies for better infrastructure control.

Cons

One of the most immediate drawbacks of CloudCheckr is that it doesn’t support automated spot instance selection and replacement. This cloud optimization strategy can bring outstanding savings, but this platform won’t let you reap its benefits. Instead, CloudCheckr comes with recommendations on relevant savings plans, which may not be optimal in the long run for many reasons.

While the platform comes with a report presenting expenses on cloud services from various providers, CloudCheckr’s multi-cloud functionality is limited.

Final verdict

CloudCheckr is optimal for engineering teams mainly looking to improve their cloud spend and use visibility. The platform helps to uncover trends and get recommendations on saving across the enterprise, teams, and projects.

However, due to limited automation features, implementing these changes will require further engineering work.


Kubecost – Comprehensive Kubernetes Cost Monitoring and Management Solution For Improved Visibility

Kubecost is a robust cost monitoring solution providing insights into Kubernetes cost allocation, monitoring, and alerts. It delivers meaningful cluster-level insights and recommendations for your engineers to implement.

Pros

Kubecost provides flexible and customizable cost breakdown features. For example, you can divide costs by namespace, deployment, service, and more indicators across all the three major cloud service providers. 

Kubescost’s comprehensive resource allocation allows generating more accurate showbacks and chargebacks, streamlining the ongoing cost monitoring. Users can allocate costs to concepts such as teams, individual applications, products, projects, departments, or environments. 

Kubecost displays costs across multiple clusters and multi-cloud environments in a single view or through a single API endpoint. It enables linking real-time in-cluster costs (CPU, memory, storage, network, etc.) with out-of-cluster expenses from the cloud services – for example, tagged RDS instances, BigQuery warehouses, or S3 buckets. Users get context-aware, cluster-level reports to find an optimal balance between cost and performance matching their service requirements.

Kubecost doesn’t expose private data. Since you deploy it in your infrastructure, there’s no need to egress any data to a remote service. You retain and control access to sensitive cloud spend data at all times.

Cons

Despite in-depth insights into cloud cost allocation and monitoring, Kubecost doesn’t allow you to manage multi-cloud infrastructure. Moreover, as it doesn’t include cloud optimization features, you’ll need to implement relevant changes manually. This will incur extra charges and still doesn’t automatically guarantee savings.

Final verdict

Kubecost rich cloud cost reporting and monitoring features will be perfect for teams looking for in-depth insights and improvement recommendations.

As their implementation will undoubtedly require additional manual effort, combining Kubecost insights with an automated cloud optimization solution like CAST AI may be a great idea. As a result, your team will get an ultimate end-to-end solution for managing and optimizing your cloud spend and usage.

No time to read?

Catch our summary of the best cloud cost management and optimization tools in 2023

Unless stated otherwise, all cloud cost management and optimization solutions covered below are compatible with top public cloud providers – AWS, Google Cloud, and Microsoft Azure.

Here’s what makes each of them stand out:

  1. CAST AI – an autonomous cloud optimization solution embracing the full power of automation to guarantee massive savings.
  2. Spot.io – a cloud optimization solution achieving significant savings and improvements thanks to automating spot instances.
  3. Harness – a cloud management module and BI tools focused on cost transparency, optimization, and governance with some automation features.
  4. Apptio Cloudability – financial management tools for monitoring, allocating, and analyzing cloud costs supporting multi-cloud and automating specific tasks.
  5. Cloudcheckr – detailed cloud cost reporting, allocation, and optimization recommendations for manual implementation.
  6. Kubecost – a comprehensive Kubernetes cost management solution teams can use for improved visibility, allocation, and real-time alerts.