Amazon EKS Reviews

We are currently using Amazon EKS as a production environment where we deploy multiple services because we serve banks using our services for identifying threat analysis and synthetic identity. Our main use case for Amazon EKS involves deploying our services based on scoring to determine whether a particular user is valid or invalid based on their social security number and any fraudulent entity they provide. We analyze this information and use Amazon EKS as the platform for deploying that application. We mainly deploy applications using Kubernetes deployments, and based on that, we deploy pods which contain the container that runs the application.

Amazon EKS helps us manage these deployments for threat analysis and synthetic identity because the controller part is managed by AWS. This addresses our concern about managing it ourselves, as we are managing a large environment where Amazon EKS ensures we can confidently manage our application rather than relying solely on the controller. We have implemented Karpenter, which manages the nodes and continuously monitors to see if any nodes or pods are underutilized or unable to load. It identifies the requirements from the pod side, automatically creates a node, and schedules the pod based on its resource needs. This automation allows us to respond quickly, especially during high load times when pods may get stuck or unable to upload images. The alerts help us react promptly, and another pod will be scheduled to fulfill the user's request within seconds.

The best feature Amazon EKS offers is automation, particularly with the automatic scheduling of pods on nodes. Karpenter, the new feature added recently that manages the node initialization, is something I really appreciate as it makes independent decisions based on the requirements, unlike older autoscaling configurations. Karpenter prioritizes cost-effectiveness by selecting the cheapest options for nodes, whether they are spot instances or on-demand. Additionally, whenever there is an issue, the pod can be automatically recreated using the defined replica set, providing a significant advantage of Kubernetes.

Karpenter helps keep costs down by consistently evaluating whether it should take on-demand instances or lower-cost alternatives. It constantly monitors for the lowest price model available in AWS. However, because the cheapest instance can be terminated with little notice, Karpenter quickly transitions to the next available on-demand instance. This proactive cost management is a key feature.

Amazon EKS has positively impacted my organization as Kubernetes offers orchestration of container-based applications, allowing us to rapidly deploy and fulfill user requests. During busy business days or promotional offers, we experience increased traffic, and Amazon EKS enables quick deployment of containers to meet this demand. If a pod is unresponsive, Amazon EKS can easily launch another pod to maintain service delivery. This adaptability not only enhances user service but also contributes to cost savings since we leverage Karpenter to manage nodes dynamically based on usage.

Since I joined this company ten months ago, we have reduced the number of failures significantly. Earlier, before using Karpenter, issues with pods hindered our efficiency and resulted in higher costs, as we did not have the option to minimize expenses effectively. Now, with Karpenter, costs have decreased and our efficiency has improved because we can swiftly address alerts and redeploy applications without delay. This transition has greatly improved our operational performance.

After adding Karpenter to our Amazon EKS setup, we have seen efficiency improvements of approximately thirty to forty percent, along with a reduction in our costs and a decrease in the number of issues our team encounters.

In my experience with Amazon EKS, I have not encountered aspects that require improvement, as AWS has invested intelligently in its development, especially with the addition of Karpenter. I do not have any particular improvement feedback for Amazon EKS or Kubernetes at this time.

I have been working in my current field for the last ten months. In terms of my total experience, I have been using Amazon EKS for the last three years, and in my current company, I have been using it for the last ten months.

Amazon EKS is stable in my experience.

Customer support for Amazon EKS is excellent, particularly at the enterprise level, as we can readily raise tickets and receive prompt responses. This interactive support is incredibly useful, allowing for quick resolutions and solutions through live sessions and screen sharing.

I have been using Amazon EKS since I started. Although I know about Docker Swarm, it poses issues for large environments like ours, which is why we opted for Amazon EKS.

We evaluated Docker Swarm before choosing Amazon EKS, as it is not well-suited for expanded environments and long-term deployments, making Amazon EKS the clear choice based on insights from my seniors.

I have experienced a return on investment with Amazon EKS. Since implementing Karpenter, costs have been reduced and operational efficiency has increased. We can deploy applications swiftly, and our monitoring tools such as DataDog alert us to any pod issues so we can act quickly. This responsiveness enables us to focus on critical issues that require our immediate attention.

I appreciate the overall pricing model of AWS, where you pay based on usage, which allows for a clear understanding of costs associated with services. The setup cost is reduced significantly since Amazon EKS simplifies the laborious process of arranging the controller plane, which typically requires substantial human resources and effort. Licensing is straightforward, making it easy to start using the service.

I would certainly recommend using Amazon EKS due to its managed services, which alleviate the complexities of controlling the Kubernetes cluster. The scalability features ensure issues with any pods are managed effectively by automatic relaunch processes, maintaining desired states. Karpenter's cost-efficient design is another highlight worth noting for anyone looking to balance container orchestration with spending.

Amazon EKS has proven to be an exceptional product, particularly as it gains popularity due to its scalability and rapid application deployment capabilities, benefiting organizations across various sectors. This review has been rated nine out of ten.

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.

It is a managed service, a Kubernetes cluster, specifically for Amazon EKS. Whatever application is going to deploy on the cloud, cloud provided this solution, a managed service cluster, a Kubernetes cluster. In that scenario where we will use for seamless and zero downtime, we are using Amazon EKS.

The major advantage of Amazon EKS is that it is a managed service. Whatever error or downtime, if we are dealing with an on-prem Kubernetes, we have to understand the root cause. If the control plane is down, understanding and fixing takes time. But AWS provides a solution, Amazon EKS, where we are not worried about any control plane components, such as ETC, other API servers, etc. It is a significant advantage, as AWS continuously checks for problems. If they occur, they will fix them immediately. They will also configure the backup from the background. As an end user, we are not able to understand any kind of downtime. For us as end users, it is always working for the managed services.

When dealing with Amazon EKS, as an end user, we also configure the IAM policies, role, and responsibility for users managing the cluster and node cluster. The user-specific permissions determine whether they are able to deploy applications to the managed service, whether at root level, admin level, or developer level with view access. We make decisions accordingly and provide the IAM permissions.

We have RBAC and context, two major parts of the Kubernetes services that provide security and the authentication and authorization process. We implement context and RBAC to secure our Amazon EKS cluster.

Because it is Kubernetes, these services need to be integrated with the Kubernetes repository. ECR is a repository, an Elastic Container Registry. When creating or integrating any images with updated builds, we create updated Docker images, push them into ECR, and integrate our Amazon EKS services with ECR. It syncs with that repository, so whenever it identifies new Docker images, it will pull and deploy them into the Amazon EKS cluster.

When setting up an Amazon EKS cluster, we define the number of nodes with minimum, actual, and maximum parameters. For example, with a minimum of two nodes for normal load, only two nodes will always be running. If it identifies increasing server load, it will automatically increase to two more nodes if we have set the maximum to four. In the Amazon EKS cluster configuration background, we specify load thresholds at 70% or 80%. It will identify that and increase or decrease nodes accordingly. If load changes persist for more than 15 minutes, it will take appropriate action. We define an auto-healing process there.

The automatic patching is valuable because it is a managed service. Whatever patching is required, the vendor itself will provide communication. If we provide confirmation, we will provide the upgradation time window. AWS itself will do all kinds of patching during that specified window to upgrade the Amazon EKS cluster.

On-premises Kubernetes requires daily updates. With managed services, the Amazon EKS version upgrades are very helpful. The managed services handle the control panel upgrades, and they will upgrade node dependency software by default. Sometimes we will check if the node dependency software needs manual updates.

The major advantage is reduced setup time. The Amazon EKS setup is much simpler compared to on-premises AKS setup, where the control plane configuration is very difficult. It is very flexible as we configure the required number of nodes into Amazon EKS, and it starts working. We get high availability and scalable architecture. Even if the control plane has issues, AWS will understand, control, and take immediate action.

We only need to ensure that Docker images are pushed to ECR are correct, and Amazon EKS will handle the deployment. The major advantages include reduced time, high availability, and scalability. From a security perspective, AWS has multiple security layers. We also implement IAM roles, different ILBs, ingress controllers, and multiple security features. CNI implementation on top of Kubernetes is also available.

The costing perspective could be improved. With normal on-premises servers using Kubernetes services, the costing might be slightly higher compared to other Kubernetes vendors. If the pricing becomes more comparable and they match other vendors while providing more flexibility, it would be more advantageous for AWS.

The solution has been in use for more than four years.

The deployment has been confirmed as successful.

There have not been any gaps felt between Amazon EKS and AKS. Whatever capabilities AKS has, Amazon EKS has similar capabilities feature-wise.

The service is very straightforward. The official manuals provided are very helpful. We have not experienced any discomfort or hidden aspects.

Whenever we face challenges or have questions about different platforms or tech stacks, or if we need to verify support or integration possibilities, we raise a ticket. They will set up a call, guide us, or provide solutions regarding integration with AWS or Amazon EKS.

The service is very professional, rated five out of five. When we raise requests, they follow their process and are always available to support us.

Positive

Having worked on both AWS and Azure, AWS is very straightforward and helpful to implement, both as a support engineer and as a developer. The AWS support team is very knowledgeable and helpful. When requests are raised, they take immediate action. It is recommended that everyone should consider AWS.

Our organization maintains a strong team. For major projects, we first work on the architecture perspective. With well-designed architecture, 90% of potential problems are prevented. Being a managed service, we focus on security and managing node services, along with the application perspective.

We are not concerned about the Amazon EKS cluster setup as it is a managed service. We only need to add nodes and utilize the features Amazon EKS contains. This reduces our effort and is very helpful for our organization.

The reviewer rated Amazon EKS 10 out of 10.

My main use case for Amazon EKS is for implementation and sustainable services and microservice application on a critical structure and services deployment.

On our application, we have more than 20 services and microservices such as authentication, login, account management, a notification service, and a billing service, which all work together to structure a heavy, useful application.

The best features Amazon EKS offers are scalability and deployment control, the ingress configuration regarding path pattern and host header to get all the services and microservices, and the HPA configuration.

The biggest difference, or the most important aspect to me, is the scalability, because you can easily scale any service or microservice to handle security during high changes in connection flow, and it is useful for the application and helps day-to-day by giving us reliability and stability so we can perform all maintenance and deployment of our system.

Reliability is a very important thing. Security and operational consistency are very important aspects, and the flexibility offered in node management and network options is also valuable. Amazon EKS is a service that is reliable and scalable, and it gives us a solid and dependable solution.

I think sometimes the documentation is not so clear and not so fast to provide more in-depth instruction and examples of bigger and critical implementations, so some difficulties for us sometimes take a lot of time to understand, test, and to put into production with security and guarantees.

I have been using Amazon EKS for almost five years now.

I advise doing a POC first and getting all the details, testing, and having a very good alignment between DevOps and development departments, and prepare all the CDN and how the connections get into your cluster, and how you configure your ingress and how to prepare every service or microservice to receive that with secure and optimized code, process, and communication with other resources. I would rate this product an 8.

I have been working in my current field since I work in the cloud, and I worked for AWS and for Amazon EKS because all of my customers are using Amazon EKS or application container solutions.

My use cases for Amazon EKS involve working for an AWS partner, one of the biggest in LATAM, where we have many customers or clients around the world with different solutions. I have a client that had many applications in Amazon EKS, and I had the full administration of the cluster. I manage not only networking, pods, or resources but also security, monitoring, the billing for the expenses, access to the cluster, and to the AWS account. I think that is a big field that I can handle within Amazon EKS.

What I appreciate most about Amazon EKS is that I use tools such as Datadog for monitoring and reporting, and if I have a problem with the cost, I use Prometheus, Grafana, and Loki, as this Prometheus package is cheaper than Datadog. I use Helm to install packages or applications, making it easier and secure to install, uninstall, or update them. I also use Argo CD for CI/CD workflows. In general, these are the main package solutions that I use for Amazon EKS.

Regarding the downsides of Amazon EKS, I remember a case where I used a network add-on different from what is provided by AWS because the pods request one IP address for each pod. The solution had many pods, and the blocks in the VPC were limited. I didn't have enough addresses to assign to the pods, and I had to change the add-on to handle the IP address using another third-party solution not from AWS. This was one of the first challenges I encountered with Amazon EKS.

Since then, AWS still hasn't fixed this issue or given me an opportunity to use the IPs that I needed.

Basically, the problem was that we did not have enough IP addresses for the pods, and we had to change the network add-on in Amazon EKS.

I have been using Amazon EKS in my career for three and a half years since I worked in the cloud.

It took me approximately one month to learn how to use Amazon EKS. The tricky part was implementing Amazon EKS cluster completely from Terraform, as creating all of the resources is challenging. If you create the cluster from the AWS console, many resources are created behind the scenes, but in Terraform, you must create each resource one by one, which was quite difficult. Overall, it took about one month.

Regarding stability, I have not experienced any lagging, crashing, downtime, or instability with Amazon EKS. I think that Amazon EKS, and Kubernetes in general, is stable. I have had problems with billing because it's expensive, but not with stability.

When it comes to scalability, I use Carpenter with Amazon EKS because it is a tool that offers significant granularity for configuration, and it works really well and fast. The inherent scalability of Kubernetes is not the best for me based on resources, but Carpenter works really nicely.

I have contacted the technical support of Amazon EKS when I had issues with the IP addresses, and they helped me solve it by installing another network add-on. On a scale from 1 to 10, I would give the support of Amazon EKS a nine because it was nice and fast.

Positive

I have used a direct alternative to Amazon EKS, which is ECS in AWS. I have many clients using ECS, Elastic Container Service, which is the native service for containers in AWS. It's not the same as Amazon EKS; it's another orchestrator, but it works fine when your application is not big.

The initial deployment with Amazon EKS was easy, but I remember that my first deployment was done with a YAML file, just using kubectl. I used kubectl run and the YAML file, and after that, I learned about Argo CD, which made the process much easier.

Amazon EKS does require maintenance on my end. Last year, Kubernetes had many updates, which was a difficult task. This is why I use Helm to install all of the applications in the cluster. If the application is built for you, you can create the Helm chart for this application and install it using this tool. I think that is the best option when you need to update the cluster. I know that AWS now offers many new applications add-ons included in the console, making it easier, but I still think that maintenance is one of the most complicated aspects of the cluster.

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

For Amazon EKS, the usual use cases I have been working with include many microservices where we cannot orchestrate in a better way in the ECS, which is an AWS native component. The major reason for moving to Amazon EKS is that if we have a microservice that takes more time to do the job, we need to return it while also running some other small microservices in parallel with that application, which we cannot do in ECS.

We moved to Amazon EKS where we have the feasibility to do parallel jobs with different microservices within the same pod, since we can run multiple containers in one pod. This helps us mitigate challenges in the company, and it works smoothly and fast, providing good performance and strong security. That has been our journey towards Amazon EKS across all customer platforms.

The most valuable feature of Amazon EKS is the add-ons service, which includes the Ingress feature that allows us to connect to both public and internal-facing load balancers. The best thing I have found is the management; using Rancher management, we can connect to Amazon EKS and manage the deployment from the UI without always needing to use the AWS console. We can create our own Rancher portal and directly manage the deployments and all other tasks from there.

Amazon EKS is a major tool for our application functionality and job purposes; it helps us at the orchestration level, allowing us to not worry about the entire deployment and service migration. We manage everything from Amazon EKS, and it's also very convenient to set up CI/CD deployment through GitHub. Additionally, we can utilize AWS native services such as CloudDeploy, so in both ways Amazon EKS has been convenient for running our applications.

I believe there is room for improvement in Amazon EKS, particularly regarding security; if Amazon EKS would provide more options for cluster-based security, it would be beneficial. Currently, it's completely managed by AWS, but I suggest that if Amazon EKS could allow monitoring of the backend of the nodes or workflows, it would greatly help users. Sometimes, AWS's shared responsibility model means that if any issues arise, the misconception lies with the users.

For instance, failures from containers running on nodes in AWS data centers can halt our workflows, especially when running in single availability zones. If AWS could enhance user interaction for improving security, it would be very helpful.

I have been working with Amazon EKS since 2017, which amounts to approximately eight years.

I have utilized Amazon EKS's integration with IAM through the service account, which is a great feature because we don't need to depend on storing secrets in Amazon EKS. We can directly use service accounts and rotate our tokens every 24 hours, which helps us achieve fine-grained access for both the user and the cluster-wise.

Compared to different cloud providers, AWS EKS pricing and licensing is absolutely reasonable and one of the best options available.

In terms of stability and reliability, I can say that among all options in the market, Amazon EKS is very reliable. I haven't experienced much downtime in the Amazon EKS cluster, so I can confidently say it is stable.

Amazon EKS has been quite scalable; people nowadays are moving to multi-AZ setups. When we choose Fargate, the beauty of Amazon EKS is that we can run multiple containers from different availability zones within the same pod. This is beneficial for availability and scalability because, using ReplicaSet, we can ensure that our containers remain at the desired count, automatically pulling new containers whenever one goes down.

I often communicate with Amazon EKS technical support, and my impression is positive. When I was initially setting up, I needed to understand a few things from AWS, and they provided substantial support, being very professional and helpful.

I had to address technical support when one of our nodes was suddenly terminated while utilizing a single availability zone, which caused application downtime and business disruption. However, AWS management tackled this situation very well by providing us with a solution that enabled us to shift to multi-AZs, as AWS guarantees 99.9% availability but acknowledges the need for users to avoid relying entirely on a single AZ.

Positive

I usually participate in the initial setup and deployment of Amazon EKS; I've done this in four projects, giving me good hands-on experience with Amazon EKS.

My usual deployment and initial setup process for Amazon EKS is straightforward. First, we need to spin up the cluster, which involves providing the cluster name, VPC details, subnet details, security details, and network mode—either AWS VPC or a customized network mode. There are several options, including attaching an IAM role and adding on features such as proxy connection and network protection. After spinning the cluster, we start the Kubelet client installation from where we can manage the cluster and begin deployments using YAML scripts and manifest workflows.

Recently, Amazon EKS launched an automated patching feature that allows us to schedule a time frame for cluster scaling up, down, and patching, which has been very helpful across all aspects.

I usually measure the impact of Amazon EKS on managing complex workflows by evaluating performance, specifically how the containers are available and performing. Based on application latency, we can determine that Amazon EKS performs well. We measure in this way because latency is the differentiator between every service; with ECS, latency can be slightly higher, which causes user difficulties when accessing applications.

Overall, based on everything I've described about Amazon EKS, I would rate this solution eight out of ten.

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.

I describe my use cases as being for web applications and for API applications.

Simplified application deployments and infrastructure management

What I find best about Amazon EKS is its simplicity and that I don't need to care about control plane. IAM authentication has been a great feature, and with the latest changes, we don't need AWS ConfigMap.

The benefits I have seen from using it include simplified Terraform code, and the fact that we don't need to configure OIDC anymore. Additionally, we don't need to manage ConfigMap.

I don't know how Amazon EKS can be improved; it's ideal already.

I have been using it for five years, since 2020.

I don't remember any issues at all regarding stability.

The scalability is great with Carpenter; however, I don't know about the scalability of control plane, but worker nodes scalability with Carpenter is great.

I have used their support team from Amazon a few times, and it was good, as I remember.

Positive

I did not previously use a different solution.

The initial setup was not complex.

The pricing is cheap, around two USD per day for one cluster, and I think it's a good price.

AWS ECS

I have used Amazon EKS integration with IAM.

I can't remember any challenges while using it, maybe in past years, but not now.

On a scale of 1 to 10, I would give Amazon EKS a rating of 9.

I would definitely recommend it to other people.

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.

The main use cases for Amazon EKS included testing some POC concepts to see how Amazon EKS works. Additionally, we can use the Kubernetes service as a VM, and AWS provides Amazon EKS, which allows us to get directly connected nodes and all the VMs without having to provision additional VMs for Amazon EKS. This feature enables us to test how it works easily.

I have used self-healing nodes with Amazon EKS, and on one occasion, I mistakenly stopped the Amazon EKS cluster. While configuring the PVC on the nodes for the pods, the node went down, and the new pods were in a waiting period because there was no node available for pod scheduling. The automatic healing feature created a new node, as I had set the minimum node size to two. Since one node was unavailable, my pod could not schedule, but the auto healing created the second node automatically, which was the easiest part.

What I appreciate about Amazon EKS is the autoscaling feature. When you configure the Kubernetes cluster manually on the VMs and need to add new VMs or if you run out of storage for the VM, you don't have to worry about that with Amazon EKS. It automatically scales the nodes and provides another VM ready for you automatically, which is a great aspect of Amazon EKS.

The main benefit of using Amazon EKS is the automation for the cluster. When creating it manually, it takes a long time to set up the VMs and configure them as server, master, and worker nodes. With Amazon EKS, you can run just one command to configure the whole cluster with the desired number of nodes.

Regarding improvements for Amazon EKS, I am unable to specify anything at the moment because it has been a year since I used it, and some problems I faced might have been due to my mistakes.

I cannot specify improvements for Amazon EKS at the moment. However, I believe they could improve pricing, as I currently find Azure Kubernetes Service to be less expensive than Amazon EKS.

I have been working with Amazon EKS for around three to four months during my internship period before I joined this organization.

The initial deployment of Amazon EKS was straightforward, although I faced some challenges due to a lack of knowledge about the service. Once you fully understand the service, you won't encounter challenges or problems while deploying the cluster.

The integration part was not very challenging; I faced just a few configuration issues, and then we were good to proceed.

I have not utilized Amazon EKS's integration with IAM; I have just used it normally and did not use that feature much.

I have not integrated Amazon EKS with AWS services; however, I have hosted the cluster in Amazon EKS and used it with Jenkins and Argo CD, focusing on CI/CD pipelines and deployment.

I have not escalated many questions to AWS support, but I did raise a question regarding the cost because I was not aware of the total pricing for the cluster, which cost me around $100 or $150. I escalated this to AWS support, expressing my confusion about the pricing, and they waived the issue away as it happened by mistake.

Neutral

I have experience working with Kubernetes and the Azure AKS product.

I cannot recall all the key differences and both pros and cons of Amazon EKS compared to Azure AKS because it has been a long time since I used EKS. Currently, I am using Azure, so I cannot compare them at this moment. If you ask me about Azure separately, I can provide insights on it, but comparing both is difficult as I do not remember all the services offered by each platform.

The initial deployment of Amazon EKS was straightforward, although I faced some challenges due to a lack of knowledge about the service. Once you fully understand the service, you won't encounter challenges or problems while deploying the cluster.

I find the pricing for Amazon EKS to be quite expensive. The EKS service itself is free, but you will incur costs for the VMs used as nodes in that cluster. The pricing is similar to provisioning EC2 instances, which may be much higher than normal EC2 instances, but the automated provisioning is worth the cost.

In my opinion, they are pretty much the same.

Regarding your organization's social media presence, I inquired about a certificate that I can share on LinkedIn to show that I have participated in this review and reviewed some products.

I would rate the impact of Amazon EKS on the organization's ability to manage complex workflows as nine or ten out of ten.

For users evaluating Amazon EKS for their environment, I recommend gaining knowledge first about the service, as it becomes quite easy to use afterward.

The documentation for Amazon EKS is quite good; I do not see any areas needing improvement in the knowledge base.

I would rate Amazon EKS as a solution an eight out of ten. I am not completely aware of the service and have not explored all the parts, which may affect my rating. I might be wrong at that part, but I give it an eight due to my self-doubt regarding not using the service in all aspects.

I decided to go with AWS because during my graduation, we had a course on AWS in our extracurricular activities, which sparked my interest in it. Additionally, during my internship, there was a need for a Kubernetes cluster, which led me to land in the Amazon EKS service.