Amazon EKS Reviews

Our use cases for Amazon EKS include deploying and managing microservice-based applications, where Kubernetes excels at orchestrating microservices and Amazon EKS handles the heavy lifting of managing the control plane. We also use it for application modernization such as migrating legacy applications to containers and for hybrid and multi-cloud deployments, running Kubernetes workloads across on-premise and cloud environments. Additionally, we run secure and compliant workloads that require strict security and compliances, utilizing AWS IAM, VPC, and security services.

Furthermore, we leverage CI/CD pipelines to automate build, test, and deployment processes, and for machine learning, we implement SageMaker.

The most valuable features of Amazon EKS are the managed Kubernetes control plane, where AWS handles the provisioning, scaling, and maintenance, ensuring high availability and automatic patching. Integrations with AWS services offer seamless access such as IAM for access control, CloudWatch for monitoring, ELB and ALB for load balancing, and storage options including EBS, EFS, and S3. In terms of security and compliance, we utilize fine-grained access control through IAM role service accounts, support for private clusters, and network policies.

Amazon EKS supports both EC2 for full control over nodes and Fargate for serverless Kubernetes pods.

The positive impacts I have seen from using Amazon EKS include enhanced security and compliance with a managed control plane, automatic patching, updates, IAM integration for secure access to AWS services, private clusters, network policies, and encryption options. Additionally, I experience operational efficiency, scalability, performance, developer productivity, flexibility, portability, and observability and monitoring through CloudWatch, Prometheus, Grafana, and OpenTelemetry, which assists in troubleshooting issues and optimizing resources, ultimately leading to cost optimization.

Areas for improvement within Amazon EKS include the management of infrastructure. Prior to using Amazon EKS, we handled manual provisioning, patching, and scaling of our Kubernetes cluster, but now AWS manages control plane operations, automatic patching, and scaling, which has reduced our operational burden and resulted in fewer infrastructure-related incidents.

I believe only operational management could be improved in the next releases of Amazon EKS.

When it comes to stability and reliability in Amazon EKS, the reliability of the control plane managed by AWS is paramount, running across three availability zones in each region to ensure high availability and fault tolerance. AWS also automatically manages the scalability and health of crucial components such as the Kubernetes API server and etcd cluster. We have options for worker nodes, including auto mode, Fargate, managed node groups, and self-managed nodes, ensuring data plane reliability.

Regarding scalability in Amazon EKS, we see managed node groups and Fargate profiles, where we can automatically scale the number of EC2 instances in a node group using Cluster Autoscaler or Karpenter. For serverless pods, Amazon EKS can scale without managing EC2 nodes, and we can utilize horizontal pod auto-scaling based on CPU, memory, or custom metrics, along with support for cluster limits, multi-cluster, and multi-region load scalability.

Amazon EKS is highly scalable, showing improvement in areas such as infrastructure management, security, and cost efficiency, with features such as auto-scaling for pods and nodes, making it suitable for bursty and high-demand workloads.

Before using Amazon EKS, we relied on self-managed Kubernetes on EC2 as well as Docker Swarm for our workloads.

We decided to switch from Docker Swarm to Amazon EKS because it is a managed service that simplifies the handling of complex scalable and modern application workflows.

Setting up Amazon EKS for the first time involves prerequisites such as installing and configuring the Amazon CLI, then installing `kubectl`, and while `eksctl` is optional, I install it for easier setup. IAM permissions are also needed to create EKS resources.

My experience with the initial setup has been straightforward, and I did not face any challenges so far, especially with `eksctl`, although there are common challenges such as IAM role configuration, network complexity, and cluster access control.

We have managed to estimate savings of around 20 to 40% using Amazon EKS, specifically achieving savings on Fargate ranging from $30 to $45 per month based on our usage.

I consider Amazon EKS to be an affordable product overall.

Before choosing Amazon EKS, I did not evaluate other solutions as I found it to be the best one for us after checking the market.

The integration of Amazon EKS with IAM enhances our authentication process as IAM users or roles can be granted access to the Kubernetes API server, managed via the AWS Auth ConfigMap in the EKS cluster, allowing us to map IAM roles or users to Kubernetes RBAC roles.

When it comes to Amazon EKS integrating IAM into application development, we utilize IAM roles for service accounts that allow our application pods to securely access services such as S3 and DynamoDB without storing credentials. We first create a Kubernetes service account and associate it with IAM roles using annotations, enabling the pod to use this role to access AWS services via temporary credentials, providing a significant developer benefit by eliminating the need to manage secrets manually and ensuring access is secure and scoped per pod.

The benefits of Amazon EKS's automated patching feature for our Kubernetes clusters primarily include improved security through the automatic application of critical security patches to the control plane and worker nodes, which reduces exposure to known vulnerabilities such as CVEs and ensures compliance with security standards. A second benefit is the reduction of operational overhead, and thirdly, enhanced cluster stability, minimized downtime, and consistency across environments. With intelligent patch management, Amazon EKS often tests patches before release.

When it comes to managing complex workflows effectively on Amazon EKS, I find that it simplifies infrastructure management by abstracting away the complexity of managing Kubernetes control planes, allowing us not to worry about patching, scaling, or securing the master nodes. It also supports scalability for high-demand applications with auto-scaling features for both pods and nodes and provides enterprise-grade security.

I utilize the AWS EKS official documentation, accessible via docs.aws.amazon.com.

My impression of the documentation is that it is very easy to learn from scratch, making it accessible even for beginners, as it is comprehensive, well-structured, and production-ready. Especially for developers and DevOps engineers such as myself, we find the user guide, best practice guide, API reference, CI tools, and workshops to be highly reliable, developer-friendly, scalable, and flexible for deployment needs.

On a scale of 1-10, I rate Amazon EKS an 8.

In my recent project, I have used Amazon EKS to deploy and scale machine learning and generative AI applications, containerizing LLM-powered APIs with Docker and deploying them using EKS for high availability and scalability. I also integrated the CI/CD pipelines and GitHub Actions to automate deployments into EKS clusters, leveraging IAM roles for service accounts, KMS encryption and VPC isolations for security. I used CloudWatch, Prometheus, and Grafana for monitoring, and Amazon EKS allowed me to build scalable, compliant, and enterprise-ready AI services without worrying about managing Kubernetes manually.

When it comes to the best features of Amazon EKS, there are some measurable properties such as variables we can feed into the model to help with market predictions. For example, for a credit risk scoring model, features might include transaction history, credit score, and income repayment. Selecting, cleaning, and transforming raw data into meaningful features to improve model performance will improve the precision and recall of the model significantly.

Amazon EKS has many powerful features that abstract the complexity of Kubernetes. Simple networking can be used for VPC and CNI, such as service meshes. However, EKS upgrades can lag sometimes when Kubernetes versions move quickly, delaying the adoption and adjustment for the latest features. I also see opportunities for better out-of-the-box monitoring, as integrating Grafana and Prometheus requires effort. Amazon EKS itself would make it easier to unify traces and metrics and allow for secure cross-cluster communications.

The initial setup in Amazon EKS is complex, especially compared to services such as ECS and Fargate, which I worked with in my US Bank project, involving VPC networking, IAM roles, or node groups. However, once set up, the deployment becomes easy. Using infrastructure as code, such as pipelines, I usually automate cluster creation with Terraform and integrate GitHub Actions. We use standardized Kubernetes manifests that make spinning up and scaling clusters much easier, so while the initial setup is complex, networking and IAM integrations make deployment and scaling smooth and easy to handle.

I have been using Amazon EKS for four years, and I have used it in my Accenture projects too, so I have good experience with Amazon EKS.

Regarding the support team from Amazon, I have some experience working with them, as most of the support cases I raised were related to cluster upgrades, networking issues, and IAM permission troubleshooting. In my project, we ran into deployment issues with EKS clusters and network failures across multiple nodes, and the support team helped us identify the VPC subnets.

Regarding the support team from Amazon, I have some experience working with them, as most of the support cases I raised were related to cluster upgrades, networking issues, and IAM permission troubleshooting. In my project, we ran into deployment issues with EKS clusters and network failures across multiple nodes, and the support team helped us identify the VPC subnets.

Positive

Before moving to Amazon EKS, I worked on different solutions such as Amazon ECS, which provides elastic containers that are more flexible for fine-grained scaling, making them a better choice. I have also deployed serverless APIs such as AWS Lambda and API Gateway for the LLM interface, where Lambda's runtime and cold starts differ. On the Azure side, I have used Azure Kubernetes Services.

The initial setup in Amazon EKS is complex, especially compared to services such as ECS and Fargate, which I worked with in my US Bank project, involving VPC networking, IAM roles, or node groups. However, once set up, the deployment becomes easy. Using infrastructure as code, such as pipelines, I usually automate cluster creation with Terraform and integrate GitHub Actions. We use standardized Kubernetes manifests that make spinning up and scaling clusters much easier, so while the initial setup is complex, networking and IAM integrations make deployment and scaling smooth and easy to handle.

The pricing of Amazon EKS varies; EKS pricing is somewhat affordable for small clusters but gets expensive at scale. If we manage it carefully, the control plane can be easier to handle. For bigger clusters, it will be somewhat expensive, but smaller clusters can be affordable depending on the choice.

I would recommend Amazon EKS to other people because it is useful, and I believe they will benefit from using it. Based on my extensive experience with the product in my recent project, I rate Amazon EKS 9 out of 10.

We use Amazon EKS for hosting our policy admin system, and it has its own benefits. The scalability aspect of it is what we considered Amazon EKS for. It is a managed service, so we don't need to take care of the underlying operating system and other things. It was one of the preferred services in AWS which we chose.

The benefits I have experienced with using the automated patching feature are key, because considering that this is a managed service, we want to be more focused on our application rather than doing all these upgrades, especially given the amount of upgrades at each of these microservices level applications. We don't want to worry about that, and there is always this blue and green setup which we can have where, if there are any issues, I should be able to switch over to my blue whenever there is a deployment. Those aspects have helped us.

What I appreciate best about Amazon EKS is the managed service part of it because we don't need to worry about the underlying operating systems or the upgrades we need to have. The flexibility at which we can spin up multiple pods in each of the Kubernetes service and the service availability aspect of it are the key points.

I have used the integration with IAM; we used IAM roles, focusing on security aspects. We had multiple IAM roles and policies defined so that it is quite secure.

A few improvements I can think of for Amazon EKS would be on the monitoring side; they have very good monitoring aspects of it, but it has its pros and cons. Having some access and visibility into their Amazon EKS services and setup would be good because there are instances where some of the pods crash, but we don't have detailed monitoring available since once the pod crashes, we can't get enough logs. If they can have a backdoor or backup capability, whenever a pod is not able to serve, to get all the metrics before killing it, that would help us investigate the reasoning behind it more thoroughly. I think that side of it is missing.

Regarding Amazon EKS pricing, they have corporate level discounts, but one key aspect is the pros and cons. One immediate deploy capability is that I can trigger a pipeline to get an Amazon EKS setup done and start using it, which is much more efficient in the short term. However, in the long run, the scenarios we've seen indicate that it requires integration with other services, and the network egress charges are a bit higher. The intent of starting with reduced costs using Amazon EKS doesn't hold as clearly when we consider it for the long run; we start with a low cost and then realize it doesn't justify that.

I have been using Amazon EKS for almost five years.

The support for AWS tools, such as integration, has significantly influenced our management. Considering that we are a big corporate with direct connects with the AWS solution architect and other people we work with, it's as simple as raising that support request and they will be here. I think we even had the highest level of support we can get from AWS with respect to this.

I think very highly of Amazon's support team; they are really good, especially considering that we have the highest level of support and their support management team is also involved in calls to give any kind of priority to our requests.

Positive

I would recommend Amazon EKS to other people, but it depends on the scenario. Kubernetes for sure, but I suggest going for Amazon EKS if yours is a smaller enterprise. If your load is too high and fluctuating, then it makes sense to try Amazon EKS, learn how Kubernetes works for your organization, and evaluate the cost-benefit analysis. If you are considering it for a longer run, I recommend conducting a cost analysis to see if moving to a local on-prem system could be more beneficial. It truly depends on the case scenario, so it's important to do the cost analysis as well. On a scale of one to ten, I rate Amazon EKS an eight.

Our usual use cases for Amazon EKS include IoT applications for edge computing devices, where we deploy some of our proprietary IoT applications to edge devices running in multiple locations, and artificial intelligence deployment to multiple systems, with a couple of them purely on the cloud where we manage bundled infrastructures into Amazon EKS for several proprietary customers.

The features and capabilities of Amazon EKS that I have found most valuable include the ease of deployment and the interesting part being the cost, which is not as expensive as setting up other cloud infrastructure.

Amazon EKS's support for AWS tools integration has influenced our application development and management process by being quite easy, with the integration being straightforward. Whenever issues arise, we talk to the support team who provide us with documentation, which is how we basically sort out most of those issues.

Amazon EKS's self-healing nodes help minimize administrative burdens in my organization by being wonderful and seamless, as it reduces the need for a whole lot of people on the team to handle issues, and it has really been seamless for us.

An area of Amazon EKS that could be improved in the future is its use for edge computing, which has been a small issue for us, especially since most of our recent work has been on edge computing applications such as Raspberry Pi and Jetson. If they could integrate things such as K3s, that would really be helpful as K8s feels a little bit bulky for edge computing deployment.

I have been working with Amazon EKS since last year, when we started moving some of our solutions to AWS EKS.

My experience with the stability and reliability of Amazon EKS has been very positive, with only a couple of intermittent shutdowns previously, but recently there have been no issues at all.

My impression of Amazon EKS's scalability has been positive, though we have not done very large-scale deployments. Most of what we've done has been on a much smaller but continuous scaling for multiple systems, and there has not been an issue on that aspect so far, although we haven't scaled up to a million or five million devices yet.

I often communicate with Amazon EKS technical support, as they have been our main go-to people.

An example of my interaction with Amazon EKS technical support was during the initial setup when we talked with them, and they provided us an easier route by suggesting how we should bundle our solutions in Docker for easy deployment.

Positive

Before Amazon EKS, I did not use a different solution for these use cases, as our path has always been with Amazon EKS.

My experience with the initial setup of Amazon EKS was straightforward with no challenges at all on my part, although the interns might complain about some snags. It's basically about studying the documentation.

My setup process involves building the application on GitHub, bundling it in Docker, and connecting with Amazon EKS.

I have seen a return on investment with Amazon EKS for time, as it has helped me save a significant amount of time. However, the cost side has not been as positive since some of the applications run in dollars, leading to complaints from customers and ourselves about the cost, particularly when providing services to customers across Nigeria and some African countries. The return on investment has not been great due to the foreign exchange rate, but for time savings, it has been wonderful in helping with deployment.

My opinion on the pricing and licensing of Amazon EKS is that it is quite varied, especially when doing projects in the African continent. It's quite expensive considering the local currency with respect to the conversions to dollars or euros, and if this could be lowered, it would help more deployments on our side with Amazon EKS.

Before choosing Amazon EKS, I evaluated other options or technologies, including Kubernetes on AWS, Google Cloud, and Microsoft Azure, but most of our experiences came from AWS, so we stayed with AWS.

I have not utilized Amazon EKS's integration with IAM solution.

I have not encountered specific benefits using Amazon EKS's automated patching feature for my Kubernetes clusters, but it has been satisfactory as we haven't actually had many issues with using Kubernetes.

The impact of Amazon EKS on my organization's ability to manage complex workflows effectively has been purely managed by my colleague, and it has been quite seamless with no issues on that particular aspect.

Some of the benefits and positive impact that I have received from Amazon EKS include getting cloud credits through Activate and certain deployments around migration, which have been quite beneficial, along with business support credit and support during certain issues. During the initial times of integrations and migrations, AWS connected us with more specialists in different locales with much more experience while also paying for their services.

Based on my overall experience with Amazon EKS, I would rate it an eight out of ten due to the lack of K3s from Rancher.

For our microservice architecture, where we have multiple services for our business use cases, we have been using Amazon EKS from the very beginning.

The integration with IAM enhances the authentication processes as it prevents multiple outages, failures, and mis-deletions from users.

The Amazon EKS support for AWS tools integration is very effective because it's within the ecosystem of AWS itself, integrating almost with everything. Amazon EKS itself uses EC2 instances, which are the basic services that Amazon provides, on top of which we have VPCs, security groups, and all.

The self-healing feature on Amazon EKS identifies when one of the nodes goes down and spawns a new node, degrading the older node, which helps to minimize our administrative burdens by reducing one stage of complexity on our SRE team.

The dashboard of Amazon EKS is very effective, where I can see all the nodes, the pods that are present, and it also shows the current CPU utilization, memory utilization, along with the pods that are scheduled on the nodes. Those insights in one place are very valuable.

We have utilized Amazon EKS's integration with the IAM solution.

We are utilizing the self-healing nodes in Amazon EKS.

I have one suggestion for Amazon EKS. When working on microservice architecture, we need to use that context and have K9s installed for a graphical user interface to check pods and nodes in a clear-cut manner. If that support is added within Amazon EKS itself to check all the config maps and everything within the UI itself, that would be very beneficial.

I have been working with Amazon EKS for one and a half years.

The initial setup of Amazon EKS was completed by other teams, and they performed it straightforwardly as they had some orchestration script which sets up the EKS cluster and has multiple add-ons to be added.

Starting to work with the Amazon EKS product was straightforward for me since I had previously taken a course on Kubernetes.

The main benefits I have seen from using Amazon EKS are the reduced complexity overall, where Amazon manages everything effectively, and the other benefit is the microservice architecture. Amazon is flawless in most cases, though we encountered a few unknowns from the EKS cluster itself. Apart from that, it is always up, and we have the support team for Amazon EKS as well. Our SREs had interactions with EKS, and within minutes or within 10 or 20 minutes, we would get the EKS cluster up if there was an issue.

There is one person from AWS who acts as a bridge between our team and their team, so we can ask them if we have an issue.

Positive

Before Amazon EKS, I was in college and did not use any other Kubernetes solutions or container management products.

The initial setup of Amazon EKS was completed by other teams, and they performed it straightforwardly as they had some orchestration script which sets up the EKS cluster and has multiple add-ons to be added.

The initial setup of Amazon EKS was completed by other teams.

The pricing of Amazon EKS is subjective because it depends on the use case and the instances that we are using. Amazon provides everything, every instance, and it also gives a cost at the fore-end, so it depends upon our use case whether we want them to be higher cost or lower cost.

We have not evaluated any other options. From the very start, we were using AWS only, and it has been good and is working fine, so we never evaluated other options.

I am not aware of the automated patching feature in Amazon EKS.

I work with Amazon EKS and am still currently working with it.

We use Kubecost for managing Amazon EKS, which is an external tool we use to find all the healthy status, memory utilization, cost, and all for our EKS cluster.

My advice for organizations considering Amazon EKS for their environment is to proceed with it, especially if they are trying for a microservice architecture. It's already very good, with no flaws. Just one thing is to have a look at the cost of the instances they are trying to provision.

I rate Amazon EKS 10 out of 10.

I am actually the end user myself without a third party at my company.

I am using Amazon EKS for my Kubernetes with a private ECR on AWS. The application focuses on workforce software as a service.

Amazon EKS adapts and fits with my needs. It provides correct tools since I still need to configure manually some nodes or setting an SSH into the nodes.

I love the automatic automation of Amazon EKS as it manages my Kubernetes. It has a log dashboard for my Kubernetes, and I can manage it easily. Sometimes I need to manually manage using Amazon EKS rather than ECS for fully managed service from AWS. There is more override capability for myself, so I can manually create another group for nodes when needed.

Amazon EKS is integrated with IAM. If I want to allow my coworker to access Amazon EKS, I can allow some permissions with least privileges. For example, if my colleague wants to look at application logs, I can grant permission only to see the logs without editing or deleting the pods.

Amazon EKS helps significantly with the development process because I can rest without worries about outages. If an outage occurs, Amazon EKS automatically replaces nodes. It helps with automation in the development lifecycle.

I am using self-healing nodes on Amazon EKS when deploying new nodes. If nodes become unhealthy, Amazon EKS replaces them with new ones, which helps with my role as a DevOps Engineer.

The benefit of Amazon EKS's automated patching feature saves my time. I can leave it to automatically handle any node issues, which greatly benefits my job efficiency.

From my perspective, Amazon EKS is quite sufficient. The main issue is that Amazon EKS only has an update for Amazon Linux 2023. The challenge occurs when switching to a new operating system. Currently, I am using Amazon Linux 2, but according to AWS information, it will be deprecated. I hope AWS continues to support the operating system for Amazon Linux 2.

I started using Amazon EKS since late 2022.

For stability management, I can allow developers to access Amazon EKS with specific permissions using least privileges. This allows them to perform necessary tasks such as viewing logs without having the ability to edit or delete pods.

Amazon EKS helps significantly with the development process by handling outages automatically. When an outage occurs, it automatically replaces nodes, allowing for continuous development and automated lifecycle management.

I don't frequently communicate with the technical support and customer service of Amazon EKS. They are quite helpful since when I need to verify infrastructure issues from their side, I receive good information. I would rate them seven out of ten because sometimes communication can be challenging due to difference accents

Neutral

Before Amazon EKS, I only used plain containers using Docker on a plain EC2, without services orchestration from AWS.

Initially, I deployed Amazon EKS manually without infrastructure as code. The challenges were related to permissions, but I understood them adequately. It can be accomplished more easily using infrastructure as code tools.

The implementation was done internally.

This solution is very important since my applications must run continuously because many users need the application with minimal downtime.

The price of Amazon EKS is not a major issue since my company accepts it. The price remains good from the company's perspective.

I chose Amazon EKS because AWS provides robust and more complete services than other service providers. I selected Amazon EKS because I wanted to manually override settings. I prefer it over fully managed services like ECS or Fargate. For cost optimization, Amazon EKS fits my needs perfectly.

I am using RDS, EC2, S3, Route 53, and a load balancer alongside Amazon EKS. The overall rating I would give Amazon EKS is 8 out of 10.

We are migrating our services into container services. We build websites and all of our products' backends are based on Amazon EKS.

The simplicity and management portal make it a neat solution. You don't have to fiddle around with too many open source tools, as it's just a comprehensive solution.

We use the pipeline, which is critical for us to deploy automatically. This eliminates manual intervention, which is really helpful.

We initially had some issues getting the logging out of it, because what they're providing into CloudTrail is what we get. If we wanted to go in-depth, we had to deploy third-party tools. We did try the sidecar way of getting the logs. Ideally, if the platform was able to provide those kinds of valuable logs, that would be beneficial. Adding enhanced logging capabilities would be a nice improvement.

We have been using the solution for three plus years.

Time to value is good with fast deployment and very good documentation that is really helpful.

I don't personally deal with the costing part, but I think it's a fair amount. That's the only reason we're using it continuously, as otherwise we would have moved somewhere else.

The implementation was done in-house.

On a scale of 1-10, I rate this solution a 9.

I'm actually working for a company that uses AWS as a cloud platform, and for our clients, we use Amazon EKS. We utilize multiple clusters and other requirements, making Amazon EKS our choice for deployment service or orchestration service.

The usual use case for Amazon EKS is to deploy an application intended for heavy user load and traffic. In technical terms, there are multiple services to choose from, but we choose Amazon EKS for its orchestration, load balancing, and auto-scaling capabilities. With this service, you don't have to worry about manual auto-scaling or manual load balancing. Before Kubernetes, manual intervention was needed for scaling applications, leading to potential crashes if capacity was exceeded. Amazon EKS alleviates those concerns with its auto-scaling feature, where predefined thresholds automatically trigger the launching of additional resources to handle increased traffic. Also, Amazon EKS allows configurations such as minimum and maximum server requirements, ensuring scalability while minimizing costs.

The features of Amazon EKS that I find most valuable include load balancing, auto-scaling, networking, security, and scalability.

Scalability in Amazon EKS refers to the ability to automatically scale up or down your application based on traffic needs. For instance, if you initially expect 10 users but suddenly have 20, Amazon EKS automatically handles the scaling, thereby preventing application crashes and maintaining service availability.

Reliability is crucial when running an application on Amazon EKS, as it ensures your application never crashes. With Amazon EKS, you don't manage the infrastructure yourself; Amazon takes care of it all. You simply need to deploy your container, select the required configurations, and Amazon EKS handles the rest without requiring you to manage the underlying resources.

I have utilized Amazon EKS's integration with IAM, which stands for identity and access management. IAM restricts access to services, ensuring only authorized personnel can access certain capabilities. This prevents mistakes or unauthorized actions, maintaining security throughout the platform.

The support for AWS tools integration in Amazon EKS influences our application development and management significantly. With integrated features related to security, scalability, and billing, we ensure the efficiency of our processes. At my company, we manage around 600 clusters on Kubernetes and emphasize reliability by integrating Amazon EKS with various third-party applications. This integration aids in deployment, security, and ultimately, efficiency, as it ensures that applications remain available and perform efficiently.

One area of Amazon EKS that could be improved is the manual process for adjusting the number of nodes. When I've already defined configurations in Docker or YAML files, it seems unnecessary to go back and make similar adjustments in the console.

I have been working with Amazon EKS for 4.7 years.

I do not often communicate with the technical support and customer service of Amazon EKS.

Negative

Currently, I am using GKE in Google Cloud, which is similar to Amazon EKS. The differences between GKE, Amazon EKS, and AKS mainly come down to minor functional variations; overall, they provide similar capabilities.

Regarding the pricing and licensing of Amazon EKS, I am not entirely certain, but from my perspective, it's somewhat comparable to AWS's compute instances. While it may be on the pricier side due to being a managed service provided by Amazon, the features and functionalities justify the cost, especially for applications requiring reliability and scalability.

I participate in the setup and deployment of Amazon EKS, though I don't do it directly through the console. I use a third-party application called Argo CD, which allows me to deploy Kubernetes applications without accessing the Amazon console directly, making the process efficient and straightforward.

On a scale of one to ten, I rate Amazon EKS a nine out of ten.