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.

Amazon Web Services (AWS)

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.

Amazon Web Services (AWS)

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.

Public Cloud

Amazon Web Services (AWS)

We use Amazon EKS for hosting our applications. It is also a version of compute service with its own perks. Amazon EKS is built on Kubernetes. Kubernetes is complex and is not something used for basic or simple applications due to its complex nature. It is really meant for complex apps such as banking applications or AI-enabled applications that have many services.

When dealing with microservices, if an application has around 20 microservices, then Kubernetes generally begins to make sense. Then it becomes a question of whether to host it on Amazon EKS, Azure Kubernetes Services, or Google Kubernetes Engine. That is basically what we use Amazon EKS for.

Amazon EKS is fairly reliable. The latest feature that was added last year, Amazon EKS auto mode, helps manage compute instances and EC2 instances. Amazon EKS auto mode is a very good addition as it helps reduce stress since users do not have to worry about upgrading Kubernetes versions. For example, when Kubernetes 1.34 is released, Amazon EKS handles the upgrade automatically.

Another beneficial feature of Amazon EKS is the Fargate offering. It helps run some compute instances on AWS Fargate, which means they only run when needed. Unlike typical EC2 instances that keep running once turned on, with Fargate, charges only apply when someone visits that service. For instance, in a banking app with multiple services, including a reviews service, Fargate can be utilized to ensure charges only occur when someone actually uses the review feature.

Amazon EKS is fairly stable and highly available. Once configured properly, it requires minimal maintenance. It integrates effectively with other services such as API Gateway, security groups, and load balancers.

The integration capabilities could be improved compared to Azure. While AWS services are integrated with Amazon EKS, there is room for enhancement.

For example, Azure DevOps provides better pipeline integration. When writing pipelines in Azure DevOps, users can easily import various built-in tasks into pipeline YAML files, such as kubectl tasks or native Kubernetes plugins, once a service connection to Azure is created.

We encountered challenges with WebSocket integration when implementing chat functionality on Amazon EKS. The chat service, which was part of our microservices running on Amazon EKS, needed to be exposed on application load balancer. Despite both application load balancer and network load balancer having native WebSocket integration on AWS, the connections were unstable. This required extensive tweaking of network load balancer configurations to manage API calls through the API Gateway. AWS could improve WebSocket integration across API Gateway, network load balancer, and Amazon EKS.

We have not used it recently because we prefer to make patches ourselves.

When auto mode is enabled, self-healing functionality becomes active. If a node encounters issues or someone makes incorrect configurations, Amazon EKS automatically resets it to maintain standard configurations. This is particularly useful when someone SSH's into Amazon EKS instances and modifies Linux kernel configurations, as the self-healing node resets it to normal, helping reduce administrative burden.

We only escalated questions regarding increasing CPU and memory allocations for Fargate. We contacted AWS through their service quota system. The process required submitting a request with justification for increasing the quota for CPU and memory on Fargate. The resolution was quick after providing a brief justification for the quota increase.

Positive

The setup process is very straightforward.

When considering Amazon EKS, it is important to use Infrastructure as Code (IAC), not just Terraform. Having a repeatable configuration of infrastructure as code is essential for creating clusters, as manual cluster creation is not common in professional production environments.

It is crucial to consider Fargate carefully, as it can help save costs. Fargate is particularly useful when parts of an application or the entire application are not used constantly, as it can reduce costs compared to running on EC2 instances.

On a scale of 1-10, this solution rates as an 8.

Public Cloud

Amazon Web Services (AWS)

The main use cases for Amazon EKS are that we use it normally in some new projects to optimize our costs. Instead of having many ECS services running, we prefer to set up a Kubernetes cluster and set everything there. For me, it is primarily for optimizing our resources.

What I find valuable about Amazon EKS is that it helps us manage all the Kubernetes. It isn't the workload, it is the main part of the Kubernetes, the head of all the cluster. Automatic updates are available, and we can set everything we created in AWS in Kubernetes, including IAM configuration. We can create policies such as creating a private endpoint for S3. The integration of Kubernetes with the AWS ecosystem is the best feature that Amazon EKS provides.

The IAM integration in Amazon EKS helps enhance the authentication processes because we can do this in a more granular way. Using IAM, you can set exactly what the service needs. If a service or application needs to upload objects or data to S3, connect to RDS, or perform other tasks, using IAM is the easiest way. The benefit is that it works in a granular way and it's easy to set up and validate. When you examine the permissions and rules to ensure everything has the correct permission at the correct moment, using IAM is perfect because you can validate and set up everything effectively.

Amazon EKS's support for different AWS tools integrations has accelerated our application development because we can think about all aspects comprehensively. We can architect using AWS services and objects, and Amazon EKS accepts this seamlessly. We don't need to translate the idea for AWS. We can write this idea using AWS objects and services, and Amazon EKS corresponds to that. It accelerates projects and is easy to manage because we can use Terraform to implement it.

I am using the self-healing nodes in the Amazon EKS solution. We have a client with a production workload running on spot instances. When a spot or node crashes, Amazon EKS starts a new node and moves everything before the node stopped. This self-healing is excellent because we don't experience disruptions. We don't face situations where a node stops and we need five minutes to start a new one. We use it in specific environments and can observe the difference when enabling or disabling Amazon EKS self-healing.

We are utilizing the automated patching in Amazon EKS. The valuable benefits I have experienced using the automated patching feature for the Kubernetes clusters directly increase security. Kubernetes typically releases patches focused on security rather than new features. It's beneficial because we can focus on our work without constantly thinking about new patch releases or upgrade deployments. Amazon EKS handles this automatically for us.

We face some issues with Amazon EKS when using the node group to control which nodes can start. We have a limitation where we need to set just one kind of instance - only large instances, only small instances, or only extra-large instances. This is a problem. It would be beneficial if we could specify that certain containers or services start on small instances rather than large ones.

I am uncertain whether Amazon EKS supports all LTS versions, and I think this would be something beneficial. Additionally, AWS has great AI features, so when we need to make updates to Amazon EKS, it would be helpful if AI could assist with planning, identifying migration requirements, and considering costs.

I have been working with Amazon EKS for about two years in production. Including study time and other experiences, I have been involved with it for approximately four years.

I faced challenges in the initial stages with Amazon EKS. The main challenge is that when we set up the cluster, it appears as a huge infrastructure just for a small application. When you set up Amazon EKS, it is configured at a large scale by default. You can't start small and gradually expand. This makes sense because for smaller applications, ECS works effectively. If you want a more integrated ecosystem, you can use Amazon EKS. The challenge lies in migrating everything, as you can't start using Amazon EKS on a small scale. It typically requires a big cluster with one, two, or three nodes. We also faced challenges with developers needing to adapt their mindset to the new way of doing things.

I have escalated questions to the technical support of Amazon EKS two or three times, and they always provided good solutions. When we don't understand the questions, we schedule a call to demonstrate the issue, and we always receive the correct answer.

I reached out for technical support with Amazon EKS because we faced issues starting a service. The way we declared the services was incorrect, but we weren't aware of this. We called AWS support for assistance. Another issue involved a security problem that we identified and reported to AWS.

I would rate the technical support of Amazon EKS a 10. The documentation is good, and when human interaction is needed, it's readily available.

Positive

From my perspective, I don't see any disadvantages of Amazon EKS compared to competitors in the market. Amazon EKS represents the state of the art. While Google has a powerful engine that offers more granular control, the additional configuration can be overwhelming. Amazon EKS balances the power of custom configuration with ease of setup.

I find the pricing of Amazon EKS complicated because I live in Brazil, where we use reals. With the exchange rate and taxes, the price appears six times higher. However, when viewed in dollars, it offers great features at reasonable pricing. Lower prices are always beneficial, and a reduction in hourly cost or promotional discounts would be appreciated, but the current price-to-benefit ratio is worthwhile.

My advice to other organizations considering Amazon EKS for their environment is to plan carefully. I strongly recommend planning and reading the documentation because Amazon EKS is resourceful and typically offers multiple ways to accomplish the same task. Careful planning, reviewing case studies for comparison, and thoughtful migration to Amazon EKS are worthwhile investments. Overall, I rate Amazon EKS a 9 out of 10.

Public Cloud

Amazon Web Services (AWS)

I have a total of around four years of experience in multiple clouds, especially in AWS, and many times I used Amazon EKS for our multiple products and projects.

In our environment, we already have all the other infrastructure and services running on AWS, so we benefit from using Amazon EKS because the other services can easily communicate with it. For example, some of our services need to access S3, and our application objects reside there, so we can easily integrate them with Amazon EKS. We also use IAM rules for integration to provide granular access to resources. As per your question, in our environment, most of our clients and resources reside in AWS, which is why we prefer to deploy other services there, as most of our development environment uses Lightsail. This gives us an edge, allowing us to easily move from development to staging or production environments within the same cloud.

When we compare other clouds, AWS has an edge among all the crowded options right now. My observations and reviews with AWS also affirm this because it provides a user-friendly experience and offers many options that other clouds do not provide. When my team and I work with AWS, we always feel comfortable. I do not know the exact reason behind it; maybe we have a lot of previous experience, and we are familiar with AWS. That is why other reviews from my colleagues at previous companies indicate that AWS has some edge compared to other clouds.

I would recommend Amazon EKS to other organizations because it provides simple configuration, easy management, safety, granular access, and vast monitoring capabilities where we can easily monitor our clusters using CloudWatch. However, I would think about a clearer dashboard for Amazon EKS, but overall, I think it is sufficient.

When we need to deploy the application, we require a large number of instances. Therefore, I hope and believe I will not face out-of-capacity issues in AWS, especially since I have not yet experienced traffic around 50,000 plus, and I believe I will not face such issues in Amazon EKS the next time we deploy with a large number of nodes and worker nodes.

Additionally, the upgradation process of Kubernetes rapidly rolls out new releases, so it should be easier for our production environment to upgrade Amazon EKS clusters. Sometimes when we are going to upgrade the Amazon EKS cluster, we need to check the backups, and we should have options to export our configurations, such as exporting the configuration to S3 or somewhere else to find backups. Other tools, such as Velero, provide this functionality to back up configurations, so I hope this backup process will help us fulfill our backup policies and other requirements.

For the pricing aspect of Amazon EKS, one specific issue arises when we deploy applications, especially as we provide SaaS services to our clients. We would like to know the cost for each customer, but we face issues because AWS charges $70 USD for the Amazon EKS engine. We struggle to divide the worker nodes' fees and the engine cost among clients, as some users have low traffic and visibility while others have large amounts of visibility and traffic. Thus, we face cost-related issues when running multiple customers on the same Amazon EKS cluster.

I have been using the solution for approximately four years.

The initial setup and deployment of Amazon EKS was straightforward; I easily provisioned the correct cluster. Sometimes, due to the depreciation of the AMIs, AWS provides warnings to use the latest version of the EKS AMIs because some of our scripts or Terraform scripts are old. I think it is good practice for AWS to provide messages to the console to upgrade your cluster, but overall, my experience with provisioning the Amazon EKS cluster is good, and I highly appreciate it.

I have not faced any issues that require escalation to customer support, and until today, I do not feel any need to escalate anything to the support team. I am happy with the service.

To meet our requirements, our services need a large amount of CPU and memory, so we need high-spec machines. When we deploy applications, we require a large number of instances.

I have not faced any issues that require escalation to customer support, and until today, I do not feel any need to escalate anything to the support team. I am happy with the service.

Positive

I also work with other clouds, such as Oracle Cloud, but I feel comfortable with AWS because I faced some issues, such as out of capacity when we designed the infrastructure for our large traffic.

The initial setup and deployment of Amazon EKS was straightforward; I easily provisioned the correct cluster. Sometimes, due to the depreciation of the AMIs, AWS provides warnings to use the latest version of the EKS AMIs because some of our scripts or Terraform scripts are old. I think it is good practice for AWS to provide messages to the console to upgrade your cluster, but overall, my experience with provisioning the Amazon EKS cluster is good, and I highly appreciate it.

I used Amazon EKS through its console rather than through the AWS Marketplace.

I have not checked the pricing yet, but I will look into it to see if EKS brings ROI or a return on investment for us.

Regarding self-healing nodes in Amazon EKS, I have not worked on that self-healing feature.

For automated patching in Amazon EKS, I have not used that feature.

Regarding disadvantages of Amazon EKS compared to competitors in the market, I think every cloud provider has the same Kubernetes engine and worker nodes. However, I believe AWS provides a more user-friendly environment, which is why many of our customers are trying to deploy their infrastructure or applications on AWS. I do not think there is any specific reason not to prefer Amazon EKS.

I have not integrated IAM tools with Amazon EKS yet, but my other teams have. I think they used Okta, but I'm not certain about it. I have some demos from a long time ago, but I think Okta is for SSO.

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

Private Cloud

Amazon Web Services (AWS)

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.

Public Cloud

Amazon Web Services (AWS)

My usual use cases for Amazon EKS are for my company's projects, as they instructed us to set up Amazon EKS and then deploy the applications.

I use Amazon EKS mainly for my company's projects, where we deploy applications according to company requirements.

The features and capabilities of Amazon EKS have proven to be valuable, as we use EKS in most of our projects. Our company has selected AWS as one of our three cloud preferences, which are AWS, GCP, and Azure.

The specific features I find most useful in Amazon EKS include the ability to deploy our applications directly using the pipeline file in YAML, the capacity to create multiple instances, and the capability to scale as per the requirement.

Amazon EKS's self-healing nodes help minimize administrative burdens in my organization by automatically creating a new node if any node crashes, allowing us to manage only the minimum and maximum nodes as needed.

To use Amazon EKS, we create the cluster first, and then we deploy the applications using the YAML file.

I have not used the automated patching feature for my Kubernetes clusters in Amazon EKS yet.

I think if new features, especially AI capabilities, are developed for Amazon EKS, it will enhance the product as it allows us to continually improve our applications.

I have been working with Amazon EKS for the past three years.

I participated in the initial setup and deployment of Amazon EKS.

My impression is that Amazon EKS is very stable and reliable as a product.

I have not noticed any outages, delays, or downtime with Amazon EKS; everything operates smoothly.

Amazon EKS is easy to evaluate in terms of scalability; we can auto-scale easily as needed.

I would rate the scalability of Amazon EKS as a nine out of ten.

I do not often communicate with the technical support of Amazon EKS as I have not needed their assistance.

For our work with Amazon EKS, we utilize the available documentation and guides, which are useful for understanding and starting with any AI tool or prompt.

I am satisfied with the documentation that Amazon offers.

Neutral

Amazon EKS was my first Kubernetes platform. Prior to that, I had only used Minikube locally, and after that, I have worked exclusively with Amazon EKS.

During the setup process for Amazon EKS, I set it up locally by configuring AWS config, and then I focused on the necessary setups like kubectl.

To start working with Amazon EKS, I first configure it with AWS, install kubectl, and then begin working after creating the cluster.

I chose Amazon EKS to work with because I have not yet started using GCP's or Azure's Kubernetes services. I have experience only with Amazon EKS so far.

I have only worked on one application in Amazon EKS, so I haven't fully developed it. I have only deployed the front end, and I think I need to gather more knowledge about EKS.

The interface of Amazon EKS is very good, but I prefer to use the CLI for creating clusters. I initially used the UI just once to understand everything before starting to create using the CLI only.

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

Public Cloud

Amazon Web Services (AWS)

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.

Public Cloud

Amazon Web Services (AWS)

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.