Amazon EKS Reviews

Our client in the healthcare industry has multiple clinics and patients who use the solution to interact with their portal and insert patient details. Patient information is managed via databases created in the solution. 

We are still exploring how the solution benefits us because we are enhancing many things on the application side including bug fixes or other items at the code level. 

On the cluster side, we are exploring options to enhance application performance. We are not sure if the solution has created a drastic change, but before we were able to perform and now we are performing well. 

The solution's Autoscaler option allows for an increase in worker notes whenever particular thresholds are exceeded. In our client's case, this is beneficial because the application sits idle the whole night and peaks in the morning hours of 9-10 am as everyone starts interacting with it and processing their workload. 

The solution is quite intelligent and is enhanced every day. They recently introduced a carpenter service that provides added advantages and are working on auto-scaling enhancements which have already allowed us to scale up our Kubernetes Clusters. 

The solution should include a popup for clusters so that all relevant information is visible at the bottom of a page. 

When clusters exist or are running, there isn't much detail on the first phase so navigating and clicking on different options is required to search for relevant information. 

I have been using the solution for three years. 

I really like the stability of the solution. 

We are using the solution to its full capacity to manage various environments and clusters that segregate our client's workload.

The solution is scalable and includes the ability to instruct a cluster to automatically upscale or downscale depending on thresholds written in the code. 

Support is quite good. I haven't used technical support for this solution but have raised tickets for other Amazon products such as IAM or S3 and received help with documentation and tutorials. 

I started my journey as a DevOps engineer with this solution per our client's requirement. 

I was not involved in the initial setup because all customers already had the solution in place before I started interacting with them. I know that setup requires streamlining but is quite easy and just takes time. 

I use some pipelines to deploy workloads such as Terraform or Argo CD where I build artifacts or codes that interact with the solution. Whenever a merge occurs, the pipelines get triggered and automatically deploy in the development environment. If test pieces pass, then they move to the next phase and are deployed on the production level. 

A team of five would be a good fit for a mid-level customer because they can simultaneously work on writing home scripts for the EKS Cluster, building the whole network, and reviewing existing queries. A larger company might require more developers. 

The solution is quite costly and developers will start exploring other solutions or moving their workloads to other clouds if costs aren't reduced.

Our client pays the licensing fees so I don't have specifics about its cost, but I hear that the solution is expensive so I am rating it a five out of ten. 

We are analyzing the solution's behavior but might switch to ECS which provides dedicated resources to an application and runs on its own. 

If you are interested in implementing the solution, first refer to the documentation or existing use cases. 

For example, a streaming company similar to Netflix can adopt and modify a use case related to the Amazon portal. There are resources that help with deciding to implement the solution. 

I rate the solution a nine out of ten. 

We use this solution for containerization and push containers into the EKS or CI/CD pipeline in the DevOps pipeline. It's very easy and well-managed for autoscale as we can manage our node groups. In addition, we can tailor autoscaling to our needs.

Amazon EKS with AWS is very good because we can connect our AWS Kubernetes Services with our CI/CD pipelines. We can integrate our EKS with our CloudWatch and Grafana, and other monitoring services are also available. We can also monitor as per our requirements.

The best solution is in AWS, in Elastic Kubernetes Services. We have general control if we want to give access to any user. Also, whenever we push a container or image, we can create any ingress and then connect to our cluster by the Load Balancer directly.

It is very easy, and we can deliver access to customers or users. Also, we can autoscale for any deployment or compute service. In addition, the control panel is completely managed by AWS, and we only have to think about a data plan and what type of deployments, services, and DaemonSets we need.

The main area of improvement is that a cluster is required on-premises, which takes a lot of time. For example, we must drain the total nodes during an upgrade from version 1.21 to version 1.22 with on-premises. After draining the total nodes, our container will shut down, and it will be recreated after upgrading. But with the AWS Kubernetes Services, the upgrade from version 1.21 to 1.22 is completed with one click. It's straightforward for the users.

In any secure services, nodes are working on the EC2 services. Whatever the EC2 services, the specified AMI is available. This AMI is an auto-security package that is automatically upgraded per the company's need. It is also secure.

We have used this solution for one year and use versions 1.15 to 1.22. It is deployed in the public cloud only, in AWS. We were initially working on an on-premises basis of Kubernetes and started working in Elastic Kubernetes in AWS. It is a managed service, and its control panel is managed in AWS. We have to work for our data plan only.

We have about 20 users pushing their container to Elastic Kubernetes Cluster. Most companies want source codes like Python, Node.js, and Java and push them to the Elastic Container Services. It makes it easy for the CI/CD pipeline to build and push images to Elastic Kubernetes Services. We recently started the containerization in Elastic Kubernetes Services.

Regarding technical support, we have the job, role, and responsibilities within our company.

If there is an issue, we must determine whether the solution is working correctly or not. We check if our node group has more or less workload than we need and if the autoscale is defined correctly. We can degrade these instances per our requirement if the node group is less. We added Grafana and Prometheus to monitor the total CPU, memory, and nodes. We can monitor requests, CPU utilization, and whether our node is behaving correctly or if we need any more memory. We also look for any issues with the HTTP request or time out.

The calculation of the pricing is dependent upon instance type. So when we make a cluster without defining any instance type, it will default enter a large instance type. So as per our requirement, we can create our node group and define our instance types per our workload.

I rate this solution a nine out of ten. Amazon EKS is the best service because it has proper security packages and manages AMI. Also, I'm working on GCP and have seen GKE services. With Amazon EKS AWS, we can do a lot of integration with our Kubernetes Cluster.

I have tried to host the enterprise content management application of IBM FileNet on Amazon EKS. That's the main use case. 

The solution has very good basic features.

The provisioning is very good we use it for the containerization of COTS applications.

The product is stable. 

If a company needs to scale the solution, it can.

The initial setup is simple. 

We've found the solution's technical support to be helpful and responsive.

There isn't something that is unique or outstanding. 

I'd like to see the solution add a service catalog.

I've used the solution for quite a number of years. It's been around three so far. 

We've found the solution to be stable. Currently, it's used on standard VMs. If we put it on Kubernetes clusters, it is highly reliable as well as easy to monitor, manage, and operate. It's great.

The solution is absolutely scalable. There are many enterprises running their businesses on this.

I'm not deploying anything for customers or a certain number of users. I'm just doing it for my own purposes. I'm learning about it and I'm trying new things. I propose these ideas to customers for various solutions and the implementations are done by another team, the delivery team, later. I can't speak to how many people ultimately end up using it.

Technical support is very good. There is no issue. There's no delayed response for their support. There's no lack of support. They are very helpful and we are quite satisfied. 

The initial setup is not overly complex or difficult. It's very simple, very straightforward. The instruction guides are all available and it's enough to get a user through the setup process. They are quite helpful guides. 

We have a professional services team that does the job day in, day out. That said, I do it for my learning and I practice something on my own too. Therefore, I am also very capable of handling the initial setup myself. 

We already have costs built into the service given by the particular vendor. If it is on-premise, we buy the software, and we pay some support costs and license costs. However, if it is on the cloud, it is a pay-per-use model. 

I'm an integrator of the solution. 

The solution can be deployed both on the cloud and on-premises. 

We are using the latest version of the solution at this time. I can't speak to the exact version number, however.

I would recommend this solution to others. 

I'd rate the product at a nine out of ten. We're pretty happy with its capabilities so far. 

We run all our microservices across the globe with Amazon EKS. We also use it for development, testing, and maintenance.

In the past, we have faced challenges with scalability and maintenance while running clusters. Amazon EKS is very easy to maintain. So it allows us to focus on our deployment.

The most important aspect of Amazon EKS is that it is easy to set up and very easy to upgrade. So we can focus on maintaining and deploying our microservice. It is also easy to scale and easy to monitor.

Amazon EKS provides very minimum information during the upgrade of the node group. When the upgrade doesn't work well, it doesn't give enough information for us to troubleshoot. So it would be great if Amazon EKS provided more information in such cases. 

Amazon EKS should enable some AIOps.

I have been using Amazon EKS for the past three years.

As a Kubernetes-managed platform, it is pretty stable. You can stabilize the new version when it is available in AWS.

It is easy to set up, and the Amazon EKS control plane accommodates scaling.

Whenever we experience any challenges, we always get a very fast response from AWS support. We are happy with the support provided so far.

We shifted to Amazon EKS because we faced some issues with our old system on OpenShift. OpenShift also has a high license price as compared to Amazon EKS.

We had some challenges at the beginning. It took us a few weeks to get one cluster up. Later, we improved our approach by using Terraform to manage it. Now, we can set up many clusters within one or two hours. We use around 60 clusters now.

We implemented it through our in-house team.

Amazon EKS is very cost-effective. I rate the pricing a ten on a scale of one to ten.

Other teams in the organization are trying to explore Google Kubernetes Engine. However, for our team, AWS is a lot easier. Our team might not move to other cloud providers because running Terraform is very useful for us.

In the internal cluster, we have four hundred people working with Amazon EKS. We have a lot of customers running billions of transactions. Overall, I rate Amazon EKS a nine out of ten.

Our client is doing some image analysis, and we need a robust system that won't go down during the image rotation, so we are using Amazon EKS. With this solution, our services will not go down during their work, and data will remain safe and available to the user.

Firstly, whenever a service goes down, EKS automatically makes up that part, enabling the services to remain available. And secondly, whenever we deploy anything, we don't have to consider security between services because EKS provides that as well. We need to configure some supportive plug-ins and tools, which is relatively easy. This feature also provides monitoring, so if our service goes down, we have an alert mechanism and logging.

We can deploy EKS microservices on any service we are developing.

The solution could be improved by adding monitoring, filtering, and logging capabilities to its current CloudWatch features.

We've been using the solution for one and a half years.

We haven't faced any major issues in one and a half years of use. We had an issue with storage, which we capped, giving us access to more space from the cloud. There are some other minor issues, but nothing major.

I would rate the solution's stability as eight out of 10.

We use the solution because it allows you to scale your application up and down. 

We have 500 data scientists actively using our EKS tool at any time.

We usually get support on time, but sometimes we have critical issues or something they need more time to deal with. 

We would give them nine out of 10 for the quality of support.

The initial setup is straightforward.

When deploying the solution, we used Jenkins to develop a CI/CD pipeline. It was a one-person job that took about 20 to 25 minutes.

On a scale of one to 10, we would give the product an overall rating of eight.

EKS is for deploying microservice projects. If you have multiple services in your application, you can deploy them and design your application accordingly.

We can deploy EKS microservices on any service we are developing.

I would certainly recommend the product to new users, but it would depend on the technology stack and the project. If a certain use case requires EKS, I would definitely advise using EKS rather than Google or Azure's EKS. I recommend Amazon Cloud Services for its reliable support and minimum downtime. 

Amazon EKS is used in containerization, which means that you deploy any application and package it into its own miniature server. Then, store that application in an encapsulated form within a server which is an operating system, and keep it aside so that the repository recurses.

It has always helped me. It is the repository where we store our images.

It's a cluster service. So Amazon EKS is essentially a Kubernetes service, which is a product created by Google and is open-sourced, meaning it can be downloaded and installed on a server in a company's data center without needing the cloud for containerization or microservices. With Kubernetes, you can build and deploy microservice applications within a Kubernetes cluster. So, all your microservices will be running under Kubernetes within a cluster. Kubernetes is what that particular class of software is called, and we refer to it as an orchestration tool. It'll figure out and make sure that your microservice is always available. So, you can go and tell them before starting Kubernetes about the number of properties, files, or variables and issue commands to determine the instances of microservices available, including setting a minimum of one or two instances. To shut down a microservice, you can set the instances to zero. Essentially, Kubernetes allows an organization or anyone to have a cluster of microservices served without needing a cloud. Amazon AWS offers Kubernetes as a service because they found that many people are using Kubernetes.

The microservices appear to be well-made, and I don't have any comments on them as I don't see any flaws. Essentially, each microservice has a substantial ephemeral space available, providing gigabytes of storage. It would be helpful if this default storage allocation could be reduced to avoid the need for excessive resources when running microservices.

The goal and idea behind microservices are to always be available and capable of handling any load, no matter how many requests come through. At times, there might be millions of requests from people. All of these services are great, but I also think it would be useful to have the same technology available in a miniature resource size, enabling the same applications and services to run on a small machine. Increasing resources should enable microservices to handle the demands of the world. I would like to see the technology scale up to the point where individuals can run a service from home even with fewer resources.

I have been using Amazon EKS for about four years, and there is no specific version of the tool because it automatically gets updated. So, the latest version is always available.

I personally prefer this solution to Amazon Fargate and would rate it an eight out of ten.

Our primary use case for Amazon EKS is for running production workloads. The microservices-based modules are broken down and then hosted using EKS.

The most valuable feature to us is orchestration when it comes to deploying. The main ideology behind Kubernetes is that you are breaking down your application into smaller modules. Instead of having a monolithic application, you make it a microservices-based module. Using an e-commerce website as an example, we would break down login's as a single module, registration as a single module and then in the event of an issue one does not impact the other. 

With your small modules, in most cases, they share a backend, and that's how at the service layer you connect them by using an API gateway or a service mesh. This ensures scalability and they don't have any dependencies when it comes to failures. This means you can easily scale and optimize. 

For now I can't suggest any improvements or additional features, the features we currently use we are very happy with. 

We have been using Amazon EKS for 8-9 months.

The Kubernetes solution has been very stable for us, there are no issues to report on that aspect. 

The beauty of Kubernetes is that you can scale it. You just have to define the workload and the scalability capability is managed itself. We just need to define the number of bots or services we want to run and it manages to scale up when needed. 

We have found Amazon to be quite responsive. We have experienced some minor issues and the response time was good. 

With regards to setup, you would need to have a basic understanding of Kubernetes and how it works before you start deploying your production workloads. Once we started working with Kubernetes and got hands-on experience there was not much hassle to roll out to production workloads.

There is no up front licensing cost, as this is a cloud based solution you pay-as-you-go.

The advice I would offer on Kubernetes is with the configuration of your applications. Some are compute-extensive, some are compute-optimized. If you don't configure this correctly it can lead to deadlocks. The compute power has to be enough when it comes to your applications. Some applications need more memory, for example, e-commerce sites need a good response time. In this example, you would want to configure a memory-based application. 

Our primary case is using Amazon EKS with all of our data in our MapReduce, map clusters, and our data clusters. And from there, we just input the information using Python and do our analysis using that.

We have problems with setting up virtual environments and installing the right packages. I believe the initial setup could be a better experience and faster customer support.

I have been using Amazon EKS for the past one and half years now.

The stability is excellent.

The scalability is not a problem we currently have five to six thousand employees using Amazon EKS.

Technical support or customer support is good but could be faster.

For us in our company, it is a very straightforward process because they had built a layer that is very useful for the users with just a couple of clicks. But normally, if you ask me in person, I think it is a bit cumbersome.

It can be done in-house but they have to read a lot of documentation from the AWS provider in order for it to make sense.

When you compare it to on-premises it is much better because, with on-premise, we have to look into data security and all these items. Amazon EKS eliminates that and becomes a cost-benefit for us.

On a scale of one to ten, I would give it a six. With the correct technical support individual, you can do well with implementation. If you are not sure about the technical support side for implementation I would wait until you are ready.