Amazon EKS Reviews

I am working mostly on AWS infrastructure services, such as EC2, EKS, RDS, CloudFormation, IAM, and CloudWatch. I have around one year of experience with Kubernetes and have been using AWS services continuously for three years. My responsibilities include working on server storage, containerization, monitoring, and access policies.

Simplifies Kubernetes setup and management.AWS handles cluster upgrades, patches, and availability.Seamlessly integrates with AWS services like IAM, CloudWatch, and VPC.Access to advanced networking, security, and monitoring tools.EKS automatically deploys the Kubernetes control plane across multiple AWS Availability Zones for fault tolerance.

I have around one year of experience using Kubernetes with AWS.

In my project, AWS EKS has shown stability without any issues.

EKS offers excellent scalability, especially compared to Docker Swarm. The ability to scale based on requirements by deploying additional containers is a strong point for Kubernetes.

I have not contacted technical support regarding EKS.

Positive

I have explored Google Kubernetes Service in my personal projects but did not work on any other Kubernetes projects before EKS.

The initial setup is relatively straightforward when using the AWS Management Console. Setting up clusters and nodes is simplified through AWS's interface compared to on-premises. It took approximately 15 to 20 minutes to complete the setup.

I do not have specific details on EKS's pricing and licensing compared to other services. However, in general, deploying in the cloud offers lower latency and high availability and reduces manual intervention and responsibility, leading to some operational efficiencies.

I have worked with Google Kubernetes Service in my personal space but have not evaluated others for professional use.

For large-scale enterprise solutions, Kubernetes is recommended due to its scalability. Despite costing considerations, EKS alleviates the burden of procedural complexities, making it suitable for enterprise-level applications.

I'd rate the solution eight out of ten.

For EKS, we deployed a Django application. The application built the whole image and stored it in ECR (Elastic Container Registry). We stored the code repository in GitHub, but the image was in ECR. We also had another repository for the Kubernetes manifest files. So we were deploying it in a different image, and the code was in a different image. We had a whole pipeline for deployment, from CodePipeline to ECR, and then from ECR to Kubernetes.

I work with different AWS solutions, such as Elastic Beanstalk, AWS Lambda, DynamoDB, and VPC. I use services like EC2, S3, and VPC every day, so I'm not including those. I've also used API Gateway, and currently, I also use AWS Bedrock.

The good thing was the integration of services. The only thing we had to think about was how we were pushing the code to GitHub or Bitbucket. After that, everything was taken care of by AWS. 

Everything was connected: the code and the real-time deployment. Testing was done within the same pipeline using CodeBuild. CodeBuild was handling multiple tasks: testing the code, deploying it to ECR, and then running it on AWS Fargate for development or testing. Once it was working fine, we had an approval stage. After approval, we deployed it to EKS using the command line from the same AWS CodeBuild process.

The scalability of EKS is good. We've compared it with multiple platforms, and we've also worked with GCP. There are more good options available in GCP compared to EKS.

But the good thing about EKS is that we can use it for serverless deployments using Fargate. It gives you two options: deploy on EC2 or deploy on Fargate. EC2 runs 24/7 and costs you money, but Fargate only runs when you need it. So EKS was really helpful for saving costs with that serverless capability.

I would like to see a warm-up time for AWS Fargate, similar to what GCP Cloud Run has. This would improve internal security. I would also really love to see lower costs compared to other cloud vendors. AWS can get quite expensive.

I've been working with EKS on and off for the last two years. Some of the projects were my own, and some were development projects.

They have good documentation and lots of blogs on Amazon AWS, so we mostly follow those. We haven't reached out to technical support directly. We had a plan for technical support, but it took them more time to fully help us. 

Sometimes the issue is on our code side and not on AWS's side. Getting the customer service and support involved in our whole process takes a long time. It's better to research for a few hours and fix it yourself rather than waiting for a week or so.

GKE gives you really good monitoring and logging, where you can see every bit of information flowing in your environment. AWS provides the same thing with CloudWatch, but it's much easier in GKE to see what's exactly going on. So monitoring and the transparency of what's happening would be one thing AWS needs to improve.

The pros of EKS are that it makes deployment really easy. You just need to package your image in ECR, and then everything goes very smoothly. You don't have to worry about running or managing Kubernetes. It gives you a managed control plane, and they replicate the control plane over different regions. So there's very little chance that it will go down. Reliability is really high with AWS.

When we started we had an issue with rollbacks. We had problems because we had to specify certain AWS parameters in order to deploy it properly. We consulted the documentation and resolved it that way.

We did some testing, and that took about one month with it. Then we started with a very small infrastructure on EKS, migrating some of our traditional websites to EKS directly. So, the initial setup took about two months. 

But we didn't use it for microservices; we only used it for two services: one was our platform service, and the other was Redis.

In my case, I handled the deployment part. I had a manager, so I just took his approval and gave him the deployment design. He was overseeing everything, but I was doing almost all the AWS work. The developers were really helpful in making the code run correctly with the image versioning.

Users have to maintain things. For example, we faced an issue where we had a lot of requests coming in, and we weren't ready with enough resources at the time. We had to manually increase the Kubernetes nodes. That was an issue with horizontal scaling. It was our mistake because we didn't automate it.

We shifted from EKS to GKE (Google Kubernetes Engine). We are saving around 20% with that change.

I already have recommended it to many people. If you're using AWS for other services, definitely go with EKS because it doesn't make sense to move to another cloud vendor if you're already using everything in AWS. The integration is really good. You get AWS WAF (Web Application Firewall) on top of it, load balancer, GuardDuty, and Inspector. So security-wise, it's really nice to have EKS surrounded by those security tools.

My advice would be to try to go with AWS Fargate initially. Try to understand how ECR (Elastic Container Registry) works because it also costs you money, so make sure your image isn't too big. And if you can, go with AWS CodeCommit, it makes things very fast. And for EKS, they can use Fargate with EKS as a service. So, users don't have to worry about scalability and reliability. It's totally managed from the user's end.

Overall, I would rate it an eight out of ten. 

I am using Amazon EKS as an integrator.

Regarding Amazon EKS integration with IAM, I do not use it.

To use Amazon EKS as a cloud provider and as a Kubernetes cluster managed by a cloud provider, it offers more benefits because you don't have to configure the cluster on your own. You can use the default configuration and just set the right networking space, set the subnet, and a few other things, but you don't have to raise up or configure your own cluster.

Self-healing nodes help to minimize administrative burdens in the organization. It helps to keep the nodes up and running. Then you can use other solutions to minimize costs or to keep the nodes running most of the time.

You can use Amazon EKS to raise up clusters and deploy applications in the cluster. The cluster is managed by Amazon, so you don't have to configure it. You can use the basic configuration of Amazon, and you don't have to interact with etcd or with the Kubernetes most inner parts. It's more simple to use.

Amazon EKS can give you more flexibility to configure on their own. In general, it's a good product. There are many different products that can fit the needs of the user or the customer in every part of AWS. In Amazon EKS, they can give a class that can be more configurable from the user or expert user rather than just using the default EKS.

Amazon EKS support for AWS tools integration has an impact on application development and management because everything is deployed on the cluster. You have to debug the various pods in Kubernetes. There isn't a direct impact, but there is an impact because everything you deploy through the pipelines goes to the cluster and there you have to integrate the cycle.

The main problem or area for improvement is flexibility in configuration. This is the only concerning part and nothing apart from this.

I have been using solutions similar to Amazon EKS from other vendors. I used GKE from Google, the cluster of Azure, and I also used KMinikube. Of course, it's not the same thing, but in general, it can be compared. For testing, K3s are just different distributions. In general, I have used other cloud providers.

It's quite easy to install Amazon EKS.

In Amazon EKS, I see it as a stable product. I don't see any particular issues in terms of nodes or performance.

I believe Amazon EKS is scalable.

I have never used the technical support from AWS.

Neutral

I see return on investment with Amazon EKS. You can save in terms of time because you can raise up a cluster or more nodes, and you can raise up the storage of the particular node in a few minutes. You don't have to take care of managing the machines directly. There is significant time-saving. You don't have to take care of the rack system because AWS has a team that works that part. You have just to pay. In terms of price saving and money saving, it depends on everything, but in general, you're going to save money.

In general, the price of Amazon EKS is expensive, but it depends a lot on the user knowledge of the tool and how we can manage the cost, which solution offers better, which solutions they can use to reduce the cost. For example, the different VM types, the Preemptible VMs or the Preemptible nodes, or you can pay one time for the use, you can reserve the machines. There are many different ways to reduce the cost.

I see big differences between Amazon EKS and GKE. The way you install the cluster is different. In GKE, when you install the cluster, it raises the nodes for you. In AWS, you can install the cluster and then you have to raise up the node using Auto Scaling Group or whatever. It's more integrated maybe. Also in terms of documentation, Google is different from Amazon.

Regarding the automated patching feature for Kubernetes clusters in Amazon EKS, I don't know any patching feature.

On a scale from one to ten, I rate Amazon EKS an eight.

Our typical use case for Amazon EKS is that we have a number of applications and microservices that we host in EKS. We have a separate code base for the infrastructure platform, and the microservice team and the application team will be deploying their microservices on their own. We have configured it in a way that it could be easily accessible for developers as well as the platform engineers; we just platformize things. Earlier, I was using ECS, and the reason we use Amazon EKS is for better adaptation of Kubernetes, fitting our multi-tenant model.

The best features of Amazon EKS are that it is very plain by itself, but we use a number of optimizations, such as Carpenter for scaling and node auto-scaling, and Keda for application and microservices auto-scaling, as an event-based auto-scaler. Additionally, we use Portainer less, and for configuration, we utilize Cert Manager and Istio. It's not only Amazon EKS but a combination of various components within it.

By default, if you just install Amazon EKS, you can deploy your application, but to have it enterprise-ready, you have to configure a number of other things that will boost productivity.

Amazon EKS's deep integration with AWS services, such as IAM and elastic load balancing, has created some challenges. For example, we have something in place already, and there are some issues with enabling FIPS, which is FedRAMP compliant for the load balancers. You cannot change the SSL policy for the load balancer; I am not sure if it has been patched by AWS yet. However, apart from that, we use it effectively, and it is more flexible.

Regarding built-in observability in Amazon EKS, there is CloudWatch and CloudTrail. However, you cannot profile the applications; we can collect logs in S3, but there is no streaming solution available. Only CloudWatch exists, so we use other tools for observability and do not depend solely on CloudWatch, only relying on it for crucial workloads and infrastructure logs.

Amazon EKS can be improved by having the maintenance of Kubernetes versions managed better, as everything is handled by the Kubernetes team and possibly a separate team at AWS. We have to constantly maintain upgrades and ensure EKS add-ons are up-to-date, requiring us to upgrade the Kubernetes version and releases. They could provide a managed service in the backend instead of making customers handle it; we are currently doing it, but it's a regular activity we do per quarter.

I have around six years of experience with Amazon EKS.

Amazon EKS is a stable solution, as it is only available in AWS alone.

It is a scalable solution for us.

Before using Amazon EKS, I was using ECS. I switched from ECS to Amazon EKS because our product design changed. With numerous small services that you don't want to manage the backend infrastructure for, you can easily deploy and let it be with ECS; it is a more straightforward solution. However, considering cost with Amazon EKS, it may be pretty high, but it serves its purpose very effectively without management overhead.

If you are going with Amazon EKS, you must change your deployment strategy and develop applications for Kubernetes, writing deployments and pods, or stateful sets, which provides more flexibility. There are pros and cons to both solutions, and you have to evaluate which will suit your use case. In our situation, we had some applications in ECS as in Amazon EKS, and that was an architectural decision discussed internally within teams.

The initial setup with Amazon EKS was hard initially, but being accustomed to it now, it's not that difficult; it's relatively easy.

We have seen ROI with Amazon EKS; we have a separate team actively working on it. We have cost explorer available, and a bill forecast based on usage allows us to determine whether resources are underutilized or overutilized. You can generate reports and analyze them. I have done this for ECS, but for Amazon EKS, I haven't worked on cost savings directly, as there is a separate team responsible for that.

My experience with pricing for Amazon EKS is limited as there's a separate team for that, and I do not have much knowledge of specifics. However, the pricing is based on the instance type we use in the EKS node group, so it should cover that aspect; their pricing is generally easy to understand in terms of instances.

We are using a cloud deployment model. On a scale of one to ten, I rate Amazon EKS an eight.

As integrators, we are the user of Amazon EKS. Our customer's main use cases for Amazon EKS are mostly internal services automation and development and deployment automation, which we are using for the digital applications of our customers in the AWS cloud.

The most valuable features in Amazon EKS include a suite of different services, such as code versioning, pipelining, code deployment, and code quality checks; we are using the total suite of the Amazon EKS.

From a project management standpoint, the automated node provisioning feature in Amazon EKS helps to streamline the application deployment process because the benefit I see with this product is that our deployment turnaround time reduces considerably, and all compliance standards are met. Code quality is maintained, and there are specific indicators designed in the product to identify quality issues with minimal effort. The Agile mode of project execution methodologies can also be implemented due to the code version controls and pipelining controls.

Most importantly, the deployment side of code releases and release management features are maintained without major hassles, within a short span of time, and without delays to customer experience. From both operational management and project management angles, these tools address human as well as programming side hurdles, eliminating most gaps and enabling timely project execution without surprises and ensuring quick turnaround time while meeting delivery deadlines.

Amazon EKS's deep integration with AWS services such as Identity Access Management impacts the approach to security and compliance because it integrates with IAM authentication and the multi-factor authentication process, allowing access only to those who need it.

I recommend that Amazon EKS could be improved by integrating AI intelligence with its components because EKS or the Kubernetes cluster has not yet undergone an AI wrapper. An AI component integrated into Amazon EKS, such as failure analysis and intelligent recommendations when failures happen, would be very helpful. Although automation is present, this AI feature would enhance the overall capability.

I have been working with Amazon EKS for almost four or five years now.

I have not faced any challenges with Amazon EKS; it's good and quicker. Initially, implementation can be a bit time-consuming, but once set, it becomes a 'code it and forget it' sort of environment.

I have no complaints about the stability of Amazon EKS; it is good, with no concerns at this point in time.

Amazon EKS is good regarding scalability; it suits conventional services and has room for improvement with upcoming agentic AI and GenAI resources.

My experience with Amazon support is good; we always had a good association with them, so no concerns on that. I would rate the support of Amazon EKS above seven.

Positive

Customers have seen a return on investment with Amazon EKS because they are happy and see value in the services; however, as the volume grows, the OpEx cost also increases, so any respite on OpEx cost for customers with exponentially growing volumes would be helpful.

Regarding the cost of Amazon EKS, I would say it's relative to the organization based on release management processes; for big organizations where customer experience matters, such as in the retail segment, the cost can be very high due to numerous daily changes. For companies in telecom and retail, as Amazon is a pay-per-use service, our usage levels are high, so I would desire if Amazon could provide certain discounts or credits for customers who utilize a lot of resources.

Our customers use the solution on the Amazon AWS cloud. They purchase Amazon EKS through AWS only.

For those looking into using Amazon EKS, my advice is that it is a good product, although the downside is that if the volume grows, the OpEx cost increases significantly. I would strongly recommend it for small and medium companies. For big companies with more releases, it also attracts more OpEx costs, so if there is a mechanism to control costs, it can be suitable for everybody.

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

The use cases for the product involve provisioning of infrastructure and auto provisioning of infrastructure.

I have managed on-premise deployments in my use case with a Helm chart.

The biggest advantages of Amazon EKS include load balancing, auto scalability, and platform integration.

The solution includes automated node provisioning features.

The integration with AWS services involves platform services only.

We usually get deployed and only need to tweak the source code; however, I think the monitoring part and observability part could be improved.

I have been selling it for almost two years.

The scalability of Amazon EKS deserves a perfect rating of ten.

The technical support from Amazon deserves a rating of ten.

Positive

I would rate the ease of installing Amazon EKS in the middle area, giving it a five.

I have moved to pre-sales activity now.

I am selling Kubernetes Engine from Amazon.

I can rate Amazon EKS as nine because I just need to see some improvement.

I want to be a reference for Amazon.

The overall rating for Amazon EKS is 9 out of 10.

I mainly use the service for competition purposes, specifically for a specific competition.

The tools we are trying to see align with R&D's use cases, and then we are going to integrate them.

It provides benefits in terms of operational efficiency.

I consider Amazon EKS to be cost-effective.

The way we are using Amazon EKS is quite good, and it is fulfilling all the purposes we wanted to use it for until now. All the tools we are using in this project are AWS tools, and we are fully satisfied.

Nothing comes to my mind right now that could be improved in Amazon EKS, and I am not facing any issues.

I joined this project later, but I have been working with AWS for more than one and a half years now.

I have not contacted AWS technical support in this project, but in previous projects, we contacted them twice regarding database and other issues. They are quite good, and because it is a build project, we received immediate support within twenty-four hours. During the call, issues were solved immediately.

Positive

I have not worked with that tool currently or previously in Germany as we were not using it at that moment.

I am currently conducting POCs.

I have about four to five AI tools, with around one month of experience so far.

This is a new initiative that has not happened before.

I do not have hands-on experiences, and I have not tried Google Gemini yet. It is just a new feature we are trying to implement with AI.

With the POC, we are trying to figure out all those things, as it has already been done as part of POC, so I do not anticipate any issues later on.

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

I use this to develop my products. I use it internally in my company and in the other projects I have been working on for the deployment and managing the services which I'm deploying into the Amazon EKS infrastructure. I have not actually been involved with automated patching, as my role has predominantly been as a developer setting up how we deploy our applications into Kubernetes. That's primarily where I've gained experience, not on the server management side where the patching is done, so I'm not sure how the patching works or what benefits it could offer in that context. However, I can discuss how I manage my CI/CD pipelines, application deployment, and how I use Amazon EKS for deployment. That is the part I have experience with.

I have been using Amazon EKS, and I started with ECS first, which is the Elastic Container Service where I can deploy my workloads. ECS is also one of other managed services from AWS, but it is not supporting Kubernetes. We wanted a platform where we could have an orchestration platform for Kubernetes. Hosting our own Kubernetes server is a very tedious job. Kubernetes itself is a very complex tool to manage and requires a lot of resources and knowledge to build a working solution. That's where Amazon EKS comes into the picture as a managed service built on top of a Kubernetes engine, offering many tools, such as CLI integrated tools or through their console to quickly set up a Kubernetes cluster, which otherwise is a tedious job.

With that offering, it is very easy to set up the Kubernetes cluster in Amazon EKS, and it is very easy to manage the nodes we have there, such as what instances we need. Since it's an AWS offering, we select a variety of EC2 instances available, and it integrates with it nicely. The same applies to the infrastructure as a service tool, IaaS, such as Terraform. It is very easy to create and manage Amazon EKS clusters through Terraform. Overall, it offers a lot of tooling and saves a lot of time compared to setting up and managing a Kubernetes server ourselves.

A specific feature of Amazon EKS is that Kubernetes is open source, and all its capabilities are based on that. The main advantage is launching and managing a Kubernetes server becomes very easy, as I receive out-of-the-box support for other AWS service integrations with Amazon EKS. For example, services such as AWS IAM directly integrate whenever I want to set up access control or security measures on my Kubernetes server. EC2 offers out-of-the-box support when setting up Kubernetes nodes. All this setup we need to do otherwise becomes much easier with Amazon EKS.

Regarding measuring the impact of Amazon EKS on my organization's ability to manage complex workflows effectively, there are measurable metrics we use. Whenever we set up any project, it is crucial to ensure we understand the availability and scalability of our applications. When I set up any application, I look at how we will be able to scale whenever there is a requirement for higher loads. To measure the Amazon EKS platform's effectiveness in this regard, I evaluate the different methods available for scaling the application. For instance, based on CPU and memory consumption, I can scale or use scalability tools such as KEDA. KEDA helps us scale based on various factors, such as the number of requests my application receives or the load on my service based on metrics. These tools can be easily installed on my Amazon EKS server without restrictions. Availability is crucial when setting up a Kubernetes cluster, especially when designing for a global audience using Amazon AWS. The options to configure multi-region and multi-AZ setups are incredibly valuable, as these features ensure high availability without complex traditional setups required for on-premise hosting.

One area I observed during setup was that while managing it through CLI and Terraform, there are many possibilities for setup and infrastructure updates. However, I believe the console experience could improve. In the AWS console, when trying to set up an Amazon EKS cluster, there were limitations on certain features I encountered a few months back while checking. EKS frequently updates, so I don't know if there's a new release. However, I found some features that I could not manage through the console, requiring me to use CLI or Terraform. It would be beneficial if we could have all features supported through the console, providing full management capabilities there.

I have been working with this tool for around two years now.

My current organization has not been using self-healing nodes, but I have used it in some earlier projects and organizations I worked with. When we decided to move away from containerization services such as ECS, we wanted a better orchestration platform that could easily handle those requirements. Kubernetes comes with many features for scalability, which otherwise we would have to manage ourselves with scripts. While Kubernetes is a good choice, it comes with its own learning curve, and understanding all the details is a big task. Services such as Amazon EKS, or maybe GKE for Google, provide the confidence that we will benefit from the orchestration framework that Kubernetes offers while also setting it up and managing it easily. We gain all the advantages that Kubernetes has as an engine without having to invest a great deal of time learning and configuring everything thanks to managed services such as Amazon EKS.

Regarding technical support, I recall one instance with Amazon EKS. I faced an issue with configuring pods in EKS that required access to other AWS services, such as IAM roles or S3 buckets. The setup was through OIDC providers in EKS, which set up trust relationships with IAM roles. There was a problem with OIDC provider setup a few years back when EKS was newer. I reached out, and I received good support when I submitted a ticket for the issues with the OIDC provider. They helped resolve the issues related to the trust relationship, identifying mistakes that needed fixing.

Positive

In my current company, I don't use it, but in my earlier company, we started with ECS, another AWS offering where we deployed our containers. However, as our deployment expanded, the limitations in scalability prompted us to explore better options. We began to reach a point where more than 30 or 40 instances of our services were running, and there was a need to support these across different regions. ECS offered some level of scalability, but it was not as customizable as Kubernetes, so we decided to transition from ECS to Amazon EKS to harness its full capabilities.

Using Amazon EKS as a cluster is free. The pricing only applies when I add the instances and set up nodes. For instance, when I add memory-optimized nodes, the applicable AWS pricing for those instances comes into play. Essentially, the pricing revolves around the nodes added, not the other configurations I'm attempting to set up.

Regarding the pricing of nodes, I find that it generally offers good value. I'm not certain what the comparative costs look against other platforms, such as OCI from Oracle that is known to offer lower pricing, but it ultimately depends. For example, AWS has recently introduced Graviton-based servers, which claim to be cost-saving, although I haven't used them myself. AWS provides several options, allowing me to choose configurations that suit my needs regarding CPU and memory. While I don't have firm details about enterprise pricing options or upfront reservations that may provide discounts, what I appreciate is the flexibility in selecting from various instance categories to meet specific requirements.

Based on my experience with Amazon EKS support, I would rate it a nine out of ten overall.