With Kubernetes becoming the go-to solution for container orchestration in cloud environments, understanding the cost implications is critical. The cost of running Kubernetes clusters can vary significantly across different cloud providers, and making the right choice could be the difference between overspending and operational efficiency.

In this blog, we’ll break down the cost structures of the three major managed Kubernetes services—Amazon EKS, Azure AKS, and Google GKE. Whether you’re scaling workloads or just starting with Kubernetes, this comparison will help you make the best decision for your business.

Factors that Determine Kubernetes Cost

When choosing between EKS, AKS, and GKE, several key factors influence the overall Kubernetes cluster cost. These factors can be grouped into two broad categories: objective cloud costs and operational/manageability costs.

1. Objective Cloud Costs

Workload Nature

The nature of your workload significantly impacts costs across cloud providers. Consider the following factors:

• Cluster Size and Configuration: The cost of your Kubernetes cluster is directly related to the number of nodes and their configurations. For example, large, high-performance nodes increase costs due to higher CPU and memory requirements. EKS, AKS, and GKE allow you to tailor the cluster’s size based on your specific workload needs.
• Resource Utilization Patterns: Efficient resource utilization (e.g., how CPU and memory requests are handled) plays a crucial role in reducing cloud costs. Both EKS, AKS, and GKE offer autoscaling capabilities that allow clusters to dynamically adjust based on workload demand, which can optimize resource usage.
• Workload Characteristics: The frequency at which workloads scale up or down also influences the cost. Constantly fluctuating workloads may incur higher costs due to the need for frequent scaling, which affects compute resource usage and networking.

Cloud Provider Pricing Models

Each provider has its own pricing model, which can have a significant impact on total Kubernetes costs.

• Pay-as-You-Go vs. Reserved Instances: EKS, AKS, and GKE primarily operate on a pay-as-you-go model for computing resources, but each offers ways to reduce costs through reserved instances or committed-use discounts. Amazon EKS, for instance, charges $0.10 per hour per cluster, which is an additional cost on top of the EC2 instances you use. AKS, by contrast, does not have a control plane charge, which may reduce costs for some workloads.
• Storage Costs: Depending on the type of storage used (e.g., SSDs, HDDs), storage costs can vary significantly across EKS, AKS, and GKE. For example, Google Cloud’s GKE offers Persistent Disks for storage, ranging from $0.17 per GB/month for standard persistent disks to $0.32 per GB/month for SSDs.
• Networking Costs: Networking costs include traffic ingress and egress as well as load balancing. In many cases, these costs are underestimated but can significantly add to overall expenses. AWS EKS charges for data transfer out of the cluster, while AKS and GKE offer slightly more competitive rates for internal networking within the same cloud region.

Optimization Efforts

The cost efficiency of your Kubernetes environment hinges on your ability to optimize resource usage effectively.

• Resource Optimization: Right-sizing your workloads, whether by configuring pod autoscaling or allocating optimal resource requests, can help reduce costs. Tools like AWS’s Cluster Autoscaler or GKE’s Vertical Pod Autoscaler automatically adjust node size and resource allocations based on workload requirements.
• Unused Resource Reduction: Cloud-native cost-saving techniques, such as shutting down idle resources, can have a noticeable impact on cost. Each provider offers tools and services to optimize resource usage, such as Azure Advisor for AKS or Google Cloud Cost Optimization tools for GKE.

2. Manageability and Operational Costs

While objective cloud costs are paramount, operational overhead and manageability should not be overlooked. Managing Kubernetes environments effectively also adds to overall costs, which can be driven by human resources and third-party tools.

Operational Overhead

• Managing the Kubernetes Environment: Keeping your Kubernetes environment operational involves regular monitoring, updates, and security patches. For example, Amazon offers AWS CloudWatch for monitoring, while Google provides Operations Suite for GKE. These tools add a layer of management and monitoring but at an additional cost.
• Third-Party Tools and Services: You may need additional tools for backup, disaster recovery, or automation (e.g., Weaveworks, Datadog), all of which come with their own costs and subscriptions.

Human Resource Costs

• Training and Skill Development: The complexity of managing Kubernetes environments means that ongoing training for DevOps teams is essential. Organizations often need to invest in training programs for team members to ensure they can manage Kubernetes clusters effectively. This is particularly true if your team is managing multiple cloud platforms (e.g., EKS and AKS), as each provider has unique nuances.
• Security and Compliance: Meeting security and compliance standards (especially for industries with strict regulations) requires additional spending on security audits, monitoring, and compliance tools. While EKS, AKS, and GKE offer built-in security features, maintaining compliance may still require third-party tools, which adds to the overall costs.

To know more about Kubernetes Cost Management and the best tools available, refer to Sedai.

EKS, AKS, GKE: Kubernetes Cost Comparison

When choosing between Amazon EKS, Azure AKS, and Google GKE for Kubernetes cluster management, cost is a critical factor. The price you’ll pay depends on various components such as cluster management, compute resources, networking, and storage. In this guide, we’ll break down the pricing structures of these three managed Kubernetes services in detail to help you make an informed decision.

Pricing Structures: EKS vs. AKS vs. GKE

Understanding the core pricing structure of each service is key to controlling your Kubernetes cluster cost. Here’s a detailed comparison of Amazon EKS, Azure AKS, and Google GKE, focusing on the major cost drivers: cluster management, compute resources, and networking.

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Amazon EKS Pricing

1. Cluster Management Costs

Amazon Elastic Kubernetes Service (EKS) charges $0.10 per hour per cluster for cluster management, translating to about $72 per month for a single cluster. This is a flat fee for operating the Kubernetes control plane, regardless of the cluster size or region.

This management fee is exclusive to Amazon EKS and is a cost you won’t find in Azure AKS (which offers free control plane management). For businesses running multiple clusters, this fee can add up quickly.

2. Compute Costs

EKS nodes run on Amazon EC2 instances, and their costs depend on the type and number of instances you deploy. EC2 instance prices range from $0.0126 per hour for small t2.micro instances to $13.338 per hour for large compute-optimized instances. Additionally, Amazon EBS (Elastic Block Storage) is used for persistent storage, with costs starting at $0.10 per GB per month.

EKS offers several ways to reduce compute costs. You can use Savings Plans or Reserved Instances, which provide discounts of up to 72% if you commit to using specific resources over a long period.

3. Networking Costs

Amazon’s networking costs can sneak up on you, particularly for data transfer. Outbound data transfers from the EKS cluster to the internet start at $0.09 per GB, and VPC (Virtual Private Cloud) costs are based on usage and configuration. While data ingress is free, outbound traffic can quickly drive up costs, especially for data-heavy workloads.

Azure AKS Pricing

1. Cluster Management Costs

One of Azure Kubernetes Service’s (AKS) main advantages is free control plane management. Unlike Amazon EKS, AKS does not charge for the cluster management itself, making it an attractive option for small to medium-scale workloads.

However, keep in mind that while the control plane is free, you may incur costs for services like Azure Monitor and Azure Advisor if you require advanced monitoring and optimization, which are essential for complex workloads.

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2. Compute Costs

AKS leverages Azure Virtual Machines (VMs) for running worker nodes. VM pricing starts at $0.008 per hour for basic instances, and higher-performance VMs can cost significantly more. Like EKS, you’ll also need persistent storage, with Azure Managed Disks starting at $0.0005 per GB per hour.

Azure also provides Reserved Virtual Machine Instances, allowing users to lock in discounts of up to 72% for long-term commitments.

3. Networking Costs

Networking in Azure is competitively priced, with data transfer charges starting at $0.087 per GB for outbound traffic. Additionally, AKS requires Load Balancers to manage network traffic across nodes, with prices starting at $0.005 per hour for basic configurations.

Google GKE Pricing

1. Cluster Management Costs

Google Kubernetes Engine (GKE) offers a free tier for one zonal cluster, which means no management costs for small deployments. However, for multi-zonal or regional clusters, GKE charges $0.10 per hour per cluster, matching EKS’s pricing model.

Google also offers GKE Autopilot, where Google manages the infrastructure on your behalf, handling configuration, scaling, and upgrades. While this simplifies management, it does come with additional costs based on resource usage.

2. Compute Costs

GKE uses Google Compute Engine (GCE) instances, with prices starting at $0.010 per hour for smaller instance types. GKE also uses Persistent Disks for storage, with pricing starting at $0.04 per GB per month, making GKE storage more affordable compared to EKS and AKS.

For long-term workloads, GKE offers Committed Use Discounts, reducing compute costs by up to 57%.

3. Networking Costs

Google Cloud’s networking costs are similar to Azure and AWS, with outbound data transfer starting at $0.085 per GB. However, GKE provides discounts for intra-region traffic, making it more cost-effective for workloads that involve frequent communication between resources within the same region.

Detailed Cost Comparison: EKS vs. AKS vs. GKE

The pricing models for Amazon EKS, Azure AKS, and Google GKE have clear differences that can affect your Kubernetes cluster costs. Amazon EKS provides flexibility and scalability but comes with a control plane charge that can increase costs for multiple clusters. Azure AKS offers free cluster management, making it a strong contender for smaller workloads, but additional services may drive up costs. Google GKE stands out with its free tier and competitive pricing for storage, making it ideal for data-heavy applications.

Kubernetes Cost Comparison: Dollar-to-Dollar Analysis

When selecting a Kubernetes service, your deployment size plays a critical role in determining costs. In this section, we break down the costs of Small to Medium-Sized Deployments and Enterprise-Scale Deployments on Amazon EKS, Azure AKS, and Google GKE. We’ll also explore the financial implications of using Kubernetes across multiple cloud providers and hybrid cloud environments.

1. Small to Medium-Sized Deployments

For smaller Kubernetes deployments, where workloads are less demanding, choosing the right cloud provider can save significant costs. Below is a detailed comparison of the pricing structures for small to medium Kubernetes clusters across Amazon EKS, Azure AKS, and Google GKE.

• Amazon EKS: Amazon charges a fixed $0.10 per hour for each cluster, adding an extra $72 per month to your bill. This control plane cost, combined with compute and networking, makes EKS slightly more expensive for small workloads.
• Azure AKS: Azure offers free control plane management, making it the most cost-efficient option for small deployments. However, costs for additional services like Azure Monitor or other add-ons may increase the total cost.
• Google GKE: GKE provides a free tier for the first zonal cluster, meaning no control plane costs. However, for regional clusters or larger environments, GKE charges $0.10 per hour for management, similar to EKS.

Azure AKS generally provides the lowest cost option for small workloads, with Google GKE as a close second, especially if the free zonal cluster is used. Amazon EKS tends to be more expensive due to its control plane fee.

2. Enterprise-Scale Deployments

Large-scale enterprise Kubernetes environments demand significant compute resources, storage, and networking bandwidth. Here’s a breakdown of the costs associated with deploying a Kubernetes cluster at the enterprise level.

• Amazon EKS: For large, compute-optimized instances like c5.9xlarge, EKS compute costs soar. Along with the $72 per month management fee and higher networking costs, Amazon EKS becomes a pricier option for enterprises.
• Azure AKS: AKS shines for enterprise deployments with its free control plane management and slightly lower compute and networking costs. It’s a great choice for large-scale, resource-heavy environments.
• Google GKE: GKE is a competitive option, especially for high-memory workloads, thanks to its cost-efficient n2-highmem instances and cheaper storage. GKE’s regional clusters, however, incur additional control plane fees.

For enterprise-scale deployments, Azure AKS tends to be the most cost-efficient, followed closely by Google GKE, particularly for data-intensive applications. Amazon EKS is often the most expensive option due to its additional management costs and networking fees.

3. High-Performance Computing (HPC)

For high-performance computing (HPC) workloads—demanding specialized hardware and vast amounts of compute power—the costs of running Kubernetes clusters can quickly escalate. HPC workloads often involve large-scale parallel computing tasks, such as simulations, data processing, and AI training, which require GPU-accelerated instances.

• Amazon EKS: For GPU-accelerated instances like p3.2xlarge, EKS is the most expensive due to high per-instance costs and networking fees.
• Azure AKS: AKS offers GPU-optimized instances like NC6s_v3, which are slightly cheaper than their AWS counterparts, making Azure a solid option for HPC.
• Google GKE: GKE’s n1-highgpu-4 instances provide a balance between performance and cost, with more affordable storage pricing.

In the HPC use case, Azure AKS often provides the most cost-efficient solution, followed by Google GKE. Amazon EKS remains the most expensive option for GPU-based high-performance workloads.

4. Multi-Cloud and Hybrid Cloud Strategies

Multi-cloud and hybrid cloud strategies are becoming increasingly popular, especially for enterprises seeking flexibility, disaster recovery, and the ability to optimize costs across cloud providers. However, using multiple Kubernetes services across different cloud providers introduces new layers of complexity—and cost.

Multi-Cloud Strategies

In a multi-cloud setup, businesses run Kubernetes clusters on multiple cloud platforms (e.g., AWS, Azure, and Google Cloud), distributing workloads across providers to optimize for performance, cost, and redundancy. While this approach offers flexibility and the ability to avoid vendor lock-in, it also incurs additional costs due to:

• Data Transfer Between Clouds: Moving data between cloud platforms is expensive. Each provider charges for egress traffic, with costs as high as $0.09 per GB on AWS, $0.087 per GB on Azure, and $0.085 per GB on Google Cloud. Transferring large volumes of data between clusters in different clouds can significantly increase networking costs.
• Management Overhead: Managing Kubernetes clusters across multiple clouds requires additional tools and infrastructure. Solutions like Anthos (Google), Azure Arc, and Rancher enable centralized management, but they come with their own fees.
• Operational Complexity: Running Kubernetes across different cloud providers increases the complexity of security, compliance, and governance. While tools like Istio and Linkerd can help manage multi-cloud environments, these solutions add to the operational overhead.

Hybrid Cloud Strategies

In a hybrid cloud environment, businesses run Kubernetes workloads across on-premises infrastructure and cloud platforms. This strategy is often used for data residency requirements, latency reduction, or disaster recovery, but it introduces its own cost challenges:

• On-Premises Costs: Running a Kubernetes cluster on-premises requires upfront investment in hardware, storage, and networking infrastructure. These costs vary based on the size and scale of the deployment.
• Cloud Bursting Costs: When workloads exceed on-premises capacity, hybrid clouds can “burst” to the public cloud. While this ensures flexibility, bursting often involves significant data transfer and compute costs in the cloud, which can be higher due to the temporary nature of the burst.
• Infrastructure Management: Managing a hybrid cloud environment requires specialized tools (e.g., Google Anthos, Azure Arc, AWS Outposts, or Rancher) to orchestrate and manage both on-premises and cloud Kubernetes clusters. These tools typically come with additional licensing or usage costs. While they simplify the management of hybrid environments by offering centralized control, the complexity and costs of integrating on-premises infrastructure with public clouds can increase operational overhead.
• Data Transfer and Storage Costs: In a hybrid cloud, data transfer between on-premises systems and the cloud can lead to significant costs. Cloud providers often charge for data ingress and egress, with fees similar to those for multi-cloud setups (e.g., $0.09 per GB on AWS, $0.087 per GB on Azure, and $0.085 per GB on Google Cloud). Additionally, hybrid cloud setups that store large volumes of data in both on-premises systems and the cloud may need to duplicate storage, which increases overall costs.
• Security and Compliance Costs: Hybrid cloud environments often require stricter security controls to ensure that both cloud-based and on-premises components meet regulatory requirements (e.g., GDPR, HIPAA). Implementing robust security practices and conducting compliance audits across these environments may require additional investments in third-party tools, security teams, and specialized consulting services.

Cost Implications of Multi-Cloud and Hybrid Cloud Strategies

Multi-cloud and hybrid cloud strategies allow businesses to optimize their Kubernetes clusters for performance, scalability, and disaster recovery. However, they can also introduce new financial challenges:

• Multi-Cloud: While multi-cloud offers flexibility and can protect against vendor lock-in, it comes with higher costs due to data transfer fees between clouds and the need for cross-platform management tools. These costs can escalate if not carefully managed, especially if workloads require large amounts of data to move between platforms frequently.
• Hybrid Cloud: Hybrid cloud strategies can help businesses balance on-premises workloads with cloud resources, but the integration of on-prem and cloud infrastructure introduces complexity. Costs associated with hybrid cloud setups often stem from infrastructure investments, bursting to the cloud, and data transfer between on-prem and cloud environments.

In both strategies, businesses need to carefully weigh the financial benefits against the increased complexity and operational overhead. Multi-cloud and hybrid setups are generally more suited for large enterprises that need the flexibility of spreading workloads across different environments for strategic, performance, or compliance reasons. However, without careful cost management, these strategies can lead to unforeseen expenses.

Hidden Costs and Considerations: EKS vs AKS vs GKE Cost Comparison

When evaluating the true cost of Kubernetes services, it’s easy to focus on core metrics like cluster management fees, compute costs, and storage. However, hidden costs—like operational overhead, support fees, and data transfer expenses—can have a significant impact, particularly when scaling up or managing enterprise workloads. In this article, we’ll dive into the often-overlooked expenses associated with Amazon EKS, Azure AKS, and Google GKE to help you make a well-informed decision.

1. Operational Overheads

Managing and maintaining Kubernetes clusters involves a range of operational costs that extend beyond the initial pricing of the cloud platform. These include costs for monitoring, maintenance, upgrades, and the tools required to keep your clusters running smoothly. Below, we’ll compare the operational overheads across EKS, AKS, and GKE.

Amazon EKS Operational Overheads

With Amazon EKS, operational overhead can be significant due to the added complexity of managing worker nodes through EC2 instances. AWS provides Amazon CloudWatch for monitoring and alerting, but this comes with additional costs, depending on the volume of logs and metrics generated.

• Monitoring and Logging Tools: Amazon CloudWatch, Amazon CloudTrail, and third-party solutions can add costs based on the data ingested and stored.
• Upgrades: While AWS automatically manages the control plane, upgrading worker nodes requires manual intervention, which can increase labor and tool costs.

Azure AKS Operational Overheads

Azure AKS offers free control plane management, but operational overhead may arise in areas like monitoring and scaling. AKS integrates with Azure Monitor, which is a paid service that provides real-time insights into the health of the clusters. Additionally, Azure Security Center offers Kubernetes security management, which is another cost to consider.

• Monitoring and Logging Tools: Azure Monitor and Azure Log Analytics provide observability but with charges for data storage and query processing.
• Upgrades: AKS manages both control plane and worker node upgrades automatically, reducing manual maintenance costs compared to EKS.

Google GKE Operational Overheads

Google GKE offers Cloud Operations for GKE, which integrates monitoring, logging, and debugging features. GKE is well-known for its ease of use, offering automatic upgrades and scaling, which can reduce operational overhead. GKE's Autopilot mode goes a step further by abstracting away infrastructure management tasks, though this comes with higher costs.

• Monitoring and Logging Tools: Google Cloud's Operations Suite is deeply integrated with GKE and offers cost-effective monitoring, but large-scale deployments can still incur substantial costs for log retention.
• Upgrades: Automatic node and control plane upgrades reduce management efforts, especially for enterprises.

2. Support and Licensing Fees

Enterprise-level Kubernetes deployments require robust support and service-level agreements (SLAs) to ensure uptime, security, and efficient scaling. Each platform offers its own support tiers, and there may be additional licensing costs for third-party tools and services.

Amazon EKS Support and Licensing Fees

AWS offers three main support plans—Developer, Business, and Enterprise—which vary in pricing based on the level of access to technical experts and SLAs. EKS may also require additional licensing for tools like AWS Cost Explorer and AWS Trusted Advisor to optimize and monitor costs.

• Business Support: Starts at $100 per month or 10% of AWS usage, whichever is higher.
• Enterprise Support: Starts at $15,000 per month for businesses needing round-the-clock support and faster SLA guarantees.

Licensing fees may apply for third-party tools like Datadog or New Relic for comprehensive monitoring and security.

Azure AKS Support and Licensing Fees

Azure offers several support options, including Standard, Professional Direct, and Premier. For enterprise Kubernetes deployments, Professional Direct support starts at $1,000 per month. AKS also integrates with third-party tools for logging, security, and monitoring, which may require additional licensing fees.

• Professional Direct Support: Includes architecture guidance, rapid response, and escalation management.
• Licensing Fees: Integration with services like Datadog or Sysdig can add extra costs for monitoring and security.

Google GKE Support and Licensing Fees

Google Cloud provides Basic, Standard, Enhanced, and Premium support plans. For large enterprise deployments on GKE, the Premium Support option starts at $12,500 per month, offering 24/7 technical support, proactive monitoring, and advanced SLAs.

• Premium Support: Provides the highest level of coverage, including architecture reviews and dedicated technical account managers.
• Licensing Fees: GKE integrates easily with third-party tools, but additional costs may arise if using solutions like Prometheus or Sysdig for monitoring and security.

3. Data Transfer and Networking Costs

Networking and data transfer costs are frequently overlooked when calculating Kubernetes costs. These fees can quickly accumulate, especially in multi-cloud environments or when moving large volumes of data across regions.

Amazon EKS Data Transfer and Networking Costs

Amazon EKS charges for outbound data transfers starting at $0.09 per GB for traffic going out of AWS. VPC peering within the same region is free, but cross-region VPC peering incurs additional charges. Elastic Load Balancer (ELB)costs vary based on usage but typically start at $0.025 per hour.

• Data Transfer: $0.09 per GB for egress outside AWS.
• VPC Peering: Free in-region, additional charges cross-region.
• Load Balancer: $0.025 per hour plus data processing charges.

Azure AKS Data Transfer and Networking Costs

Azure’s networking costs start at $0.087 per GB for outbound data transfer. Load balancers in AKS are generally cost-efficient, with the Standard Load Balancer starting at $0.005 per hour, though costs can rise as traffic scales.

• Data Transfer: $0.087 per GB for outbound data.
• Load Balancer: $0.005 per hour for basic configurations.

Google GKE Data Transfer and Networking Costs

Google Cloud’s networking costs are similar to AWS and Azure, with data egress charges starting at $0.085 per GB. GKE also offers Cloud Load Balancing, which is priced at $0.025 per hour plus traffic processing fees.

• Data Transfer: $0.085 per GB for egress.
• Load Balancer: $0.025 per hour plus usage.

When evaluating the cost of Kubernetes services, it’s crucial to go beyond basic pricing models. Hidden costs such as operational overheads, support fees, and data transfer charges can significantly impact your total Kubernetes spend. Amazon EKS typically incurs higher operational and support costs, especially for enterprises. Azure AKS offers cost-effective monitoring and networking, though support fees can accumulate depending on the service level. Google GKE stands out with its strong support options and lower data transfer fees, particularly for high-volume deployments.

How to Calculate Kubernetes Costs?

Calculating the total cost of running a Kubernetes cluster involves accounting for several key components, including cluster management, compute, storage, and networking costs. Here’s a formula to help calculate the total monthly cost of your Kubernetes environment:

Total Kubernetes Cluster Cost =
(Control Plane Cost per Hour × Hours in a Month) +
(Node Cost per Hour × Number of Nodes × Hours in a Month) +
(Load Balancer Cost per Hour × Hours in a Month) +
(Data Transfer Out Cost per GB × GBs Transferred per Month) +
(Storage Cost per GB per Month × Storage Volume in GB)

This formula gives a detailed breakdown of the major components you need to consider when calculating the monthly cost of your Kubernetes clusters across different cloud providers.

For instance:

• Control Plane Costs: EKS charges $0.10 per hour, while AKS and GKE provide free options for the control plane.
• Node Costs: Compute costs depend on the instance type and size, e.g., a t3.small instance on EKS costs $0.0126 per hour.
• Load Balancer Costs: AWS charges $0.025 per hour, Azure starts at $0.005 per hour, and Google Cloud charges $0.025 per hour.
• Data Transfer Costs: Data egress starts at $0.09 per GB for EKS, $0.087 per GB for AKS, and $0.085 per GB for GKE.

By using this formula, you can estimate the monthly cost of your Kubernetes deployment and plan your cloud budget effectively.

Wrapping Up: Key Insights and Recommendations

Throughout this article, we've explored the differences in Kubernetes costs across Amazon EKS, Azure AKS, and Google GKE:

• EKS has a flat control plane charge of $0.10 per hour, which can make it more expensive for smaller workloads. It offers strong integration with AWS services but has higher operational overhead.
• AKS offers free cluster management, making it highly cost-effective for both small and enterprise-scale workloads. Its support costs are also relatively low, but monitoring and data transfer fees can accumulate depending on usage.
• GKE provides competitive pricing with a free tier for zonal clusters and lower storage and data transfer fees. GKE Autopilot offers a fully managed experience but at a higher cost.

Choosing the right Kubernetes service depends largely on your specific business needs:

• For small to medium workloads, Azure AKS tends to be the most cost-effective due to its free control plane and low operational overhead.
• For enterprise-scale deployments, Google GKE offers robust tools, competitive pricing, and strong support options, making it ideal for large-scale operations.
• For AWS-centric environments, Amazon EKS integrates seamlessly with other AWS services and offers significant discounts via Savings Plans for long-term workloads, but it comes with higher control plane costs and operational complexity.

Managing Kubernetes environments across multiple cloud platforms can be complex and costly. With Sedai, you gain access to advanced cloud management solutions designed to streamline your Kubernetes operations. Our intelligent automation and optimization tools can help reduce operational overhead, improve resource utilization, and ensure that your clusters are running efficiently at all times.

Book a Demo today to learn more about how we can help you maximize your Kubernetes investments and enhance the operational efficiency of your cloud workloads.