Kubernetes Reviews

We use Kubernetes to deploy a software solution that the company sells to enterprises. Originally, our company offered their software installed without Kubernetes, but they plan to move all future customers to Kubernetes. I would say it's extensively deployed, and they plan to increase it as much as their customer base will accept it.

Kubernetes provides a standardized way to deliver software in a scalable form. The customers of the software already have people who know how to manage Kubernetes, or they can easily hire employees who do. Packaging up the software to run would require a lot of specialized knowledge.

Kubernetes provides scalable clustering for containers and other means of deployment.

Kubernetes is incredibly complicated, so one area of improvement is the ease of administration. I would like a user interface that you can run to help you debug and diagnose problems and suggest how to configure things.

I've been using Kubernetes for about four months. I started using it at HPE and actually switched to be able to work more with it at the new place.

Kubernetes is generally stable. 

Kubernetes is scalable if it's well-administered. 

As far as I know, there's not any customer support. There's customer support for the cloud instances. If you are running Amazon EKS, they might have support for that. It's open-source software, so there isn't Kubernetes support, but I could be completely wrong about that.

The complexity depends on how you deploy it and what flavor you choose. If you're using a cloud provider like Google, AWS, or Azure, they each have a flavor of Kubernetes you can deploy. It is easier to deploy one of those than downloading and installing it on your servers. There's also something called K3S, a lightweight version of Kubernetes that can run much more easily. It's designed to be used in the Internet of Things. It's relatively scalable and can be used independently, but there are different packages, just like Linux has different distributions.

The maintenance required also depends on how you implement it. It's going to require at least one person who knows Kubernetes. I imagine it might need multiple people to maintain the solution if you're not using the cloud versions.

Kubernetes is open source.

I rate Kubernetes 8.5 out of 10. My advice is to hire people who have demonstrated experience or are prepared to spend significant time taking courses because it's deep and broad, and there's a lot to learn. It isn't straightforward, but it would be hard to simplify it, considering what it does.

This solution is deployed on cloud with Azure.

Managing the container was a challenge. The cloud-managed Kubernetes allow us to take care of a big system and deployment and container management without having a big operational team.

It's still difficult to manage based on my experience. There are a lot of things that need to be done to get it up and running initially. It's very complex. The whole system required a big team, and that's why we were using the managed version. If we were not using the managed version, then it would have been very difficult to manage the system. Overall, it's very powerful, but there are also a lot of complexities to manage.

In the version that we're currently using, we still have to pull in a lot for different tools, like the distribution data, distribution tracing tool, etc. For it to be fully functional, we still have to deploy more tools into it. It should come with more default rules built into it for log aggregation, distributed tracing, and monitoring, so they can definitely improve upon those things. If they had better tool integration for monitoring and log aggregation, then it would be much better.

I've been using this solution for two years.

It's stable.

It's scalable. There are two different ways you can do it. You can manage it yourself, and then you're responsible for scalability software. But if you use a cloud solution, Google GKE and Azure have AKS and AWS had EKS. If we use those kinds of services, the scalability becomes easier to manage. It's definitely scalable, but even that part is very complex to manage unless you're using a cloud managed service.

It was very complex to set up the initial structure for Kubernetes. Using managed services made it simpler.

I would rate this solution 9 out of 10.

Kubernetes is used t deploy all our applications. 

The deployment is one of the most valuable feature. The solution is also easy to use. 

The user-interface in regards to the other solution can be improved. 

I have been using Kubernetes since 2020. 

It is a highly scalable solution. There are twenty people using Kubernetes.

The initial setup and deployment is quite easy. We have one tech team and one Data Science team. 

If you are building an MVP or you are starting small, then Kubernetes might not be the best option because there are some charges associated with it.\  But if you are building an application that might scale rapidly, then you should definitely go with Kubernetes. 

If your deployments happen very frequently, then it is definitely the solution you should use, because you can restore previous versions if something fails.

I rate the overall solution a nine out of ten. 

I use the product for microservices. 

I am impressed with the product's coupling of resources and flexibility. 

The tool needs to improve its UI. The tool is very complex and basic. 

I have been using the solution for six months. 

We haven't encountered any issues with the product. 

I would rate the product's scalability an eight out of ten. 

The solution's setup is difficult and we need to write a lot of commands. It takes one day to complete the setup. We require two people for the solution's deployment and five people for its maintenance. 

I am using the solution's open-source version. 

I would rate the product a seven out of ten. 

Our organization has an extensive online platform available to our customers, who are geographically spread between the United States, Japan, and other parts of the Far East. The platform's backbone comprises around 120 microservices, and we use Kubernetes to host most of them.

The Desired State Configuration is a handy feature; we can deploy a certain number of pods, and the tool will ensure that the state is maintained in our desired configuration.

The features regarding scalability are also valuable. As part of our DevOps, I am involved in some enhancements where we plan to use pod scaling and the available AKS node scaling features. These are available native to AKS, but we do have to set up some matrices to control scaling and define scaling rules. The fact that we can achieve that dynamically is a significant part of why we use the solution.

Kubernetes is an excellent platform for hosting microservices, especially container-based microservices.

The solution has some issues regarding availability during high loads. Worker nodes are sometimes unavailable, affecting the overall availability of the applications. This is a bug or underlying problem with the tool, and Azure and other providers are looking into improving this by releasing new versions of Kubernetes that fix some of the platform's issues.

We usually encounter a few bugs, and as part of our partnership with Microsoft, we tend to share that data and receive active support from them. They are constantly improving the product.  

Many options are available from third-party vendors and open-source providers that build upon AKS, or Kubernetes in general, especially regarding monitoring and telemetry. Perhaps incorporating similar features into the native solution would be a good improvement. However, the solution, with the core engine and the supporting ecosystem of open-source projects and other available features, covers the entire spectrum of what we need to do.

I've worked on different projects using Kubernetes as an application hosting platform for two or three years.  

The product is stable; it has benefited from a few years of worldwide production-level experience and customer feedback. That's the base, open-source version of Kubernetes. There are numerous vendors with their own flavors of the solution, like AKS and Amazon, which are also pretty stable. Rancher isn't open source, but it has many features that make it easy to maintain, so it's also stable.

We have around 2000 total users, including end users and DevOps users. 

I have contacted technical support on a couple of occasions.

Neutral

We used a version of Rancher Kubernetes to manage an on-premise instance of the solution. I'm very familiar with the tool, but I'm not up to date with any of the new offerings available with Rancher.  

AKS and other managed Kubernetes instances are quite easy to set up. However, depending on the project requirements, it can become more complex.

For example, a previous project I worked on had some stringent rules around networking policies, traffic routing, etc. The tight security policies meant we had to use a highly customized virtual network upon which the AKS instances were hosted. We went with a Kubernetes networking model, which might have been called a container networking model. This model required each pod to be provided with an IP that was part of the actual IP range within a network, so pods had real IP addresses. This kind of implementation becomes more complex.

In terms of native setup, Kubernetes has its own internal networking system and cluster IPs, which facilitates easy pod scaling, so native implementation is relatively easy. When projects have higher security requirements, the implementation gets a little more complex, but it's still much more straightforward than a self-hosted cluster.

An entirely self-hosted Kubernetes cluster is the most complex. We have to set up every aspect, including the master nodes, worker nodes, and networking, which requires dedicated Kubernetes administrator resources. We previously implemented an on-premise Kubernetes cluster, and it takes significant effort and dedicated resources to manage that sort of cluster.

I would say the solution is worth the money, but it depends on the required workloads, the type of workload, and the scaling requirements etc.

Ultimately, we're using the computing power on the nodes, so they need to be appropriately scaled according to the workload. With intensive workloads requiring large machines, I'm curious to know how much savings one would have purely in hardware cost compared to using standalone VMs.

I would rate the solution an eight out of ten. 

The solution is deployed on a private virtual network belonging to our organization and in the Azure cloud. The interconnections with on-premise are purely through VPN gateways and so on.

Regarding POC-type projects, I recommend using a trial version of Kubernetes with Rancher or a very lightweight configuration of AKS. It's essential to consider the factors involved in analysis and precisely what you want to find out. Based on that, tests can be conducted to determine the solution's available benefits. It also depends on the kind of workload; if that consists of microservices that can be easily containerized, then it's worth investing some time and effort into AKS. POCs can generate some numbers regarding costs, performance, scalability etc. 

If the setup is well designed and the appropriate workloads are shifted to Kubernetes, there's a lot of flexibility available for DevOps to scale their applications. There are also many available monitoring, telemetry, service discovery, and service mesh features. If the architecture is well-planned and devised, the Kubernetes platform can provide significant benefits.

We have multiple use cases. We use it for pharmacy applications, databases, MySQL and web servers. We use Kubernetes for anything that runs normally.

The high availability of containerization is most valuable. We get density with planning containers, and the self-serving feature allows our developers to grab a container and complete testing. The self-serving feature is always in the cloud or locally integrated with Ceph or cluster.

The front end of Kubernetes could be built better as the front end is very rudimentary.

We have been using this solution for about five years. It is deployed both on-premises and on cloud but mainly on-premises.

It is a stable solution, and we don't have any issues.

It is very scalable. We can scale up, add notes, scale out horizontally, and scale the number of containers in a web server. We add triggers to the cluster, and it scales as needed. We have quite a few users of Kubernetes at our company, and it is very easy to add new developers as users.

The initial setup was straightforward. For testing, we fire up Kubernetes clusters about once a week for different departments. Depending on the containers, it generally takes about four hours to get a cluster up and running and connected to the storage. We've completed this many times and are familiar with the setup. We completed the setup ourselves.

The Kubernetes community edition is free, but we use OpenShift in production, which is the Red Hat version of Kubernetes.

We evaluated Swarm and some other solutions, but we eventually chose Kubernetes and OpenShift.

I rate this solution a nine out of ten. Regarding advice, in the retail field, where clients would require mobility and portability, and disposable computing, there is no comparison to Kubernetes.

We use this solution to assist with our infrastructure development work.

This solution provides a comprehensive way to scale up our ports and containers, without having to use multiple products.

The solution does not work with third-party tools, or alternative cloud providers, which limits the extent that we can utilize it to.

We would like to see visualization support added to this solution, in order to provide a wider single view of the infrastructure. 

We have been working with this solution for six months.

We have found this solution to be very stable; the only issues that have occurred have been from human error in the configuration.

This solution is extremely scalable, if a business has the budget available to do so.

The technical support for this solution is good, as long as you can provide extensive details on the issue that has arisen.

The initial setup of this product is quite complex, and requires time to understand what is needed to implement it properly. However, once the expertise has been gained, the deployment is quick and straightforward.

The solution was deployed using a third-party consultant.

This solution provides a platform for all development projects, which means that once it is implemented for one project, it can then be used for all future ones. 

The solution itself is open-source, so there is no cost attached to it. However, it requires a virtual machine to operate, which does come at a cost; a choice of a pay as you go model, or a monthly charge via an enterprise agreement. 

There is a pricing calculator available, where organizations can determine the level and number of virtual machines required, and how much that will cost.

It is important to understand the structure of the solution as a system in its own right, and we would recommend that organizations invest in vendor neutral training before implementation begins.

I would rate this solution an eight out of ten.

Our setups are all Kubernetes-based. Orchestration and all of that is done through Kubernetes.

The clustering is the most valuable aspect of the solution. Reviewing all the servers and hardware from one common place is great. That is the best part of it.

The solution is stable and reliable.

It's scalable. 

Maybe it's not the scope of this product, however, some analytics information could be more available through this. Otherwise, we have to integrate Dynatrace or some kind of tool. When it has all the servers maybe it's a different scope and it wouldn't work. Some analytics would be so great, however. We'd like insights on the services and their uses, which are very limited. We have to use a third party and paid services like Dynatrace or AppDynamics.

Sometimes what happens is, if we find, let's say, OutOfThread or OutOfMemory, where our threads are blocked. If you are doing real-time analysis, you can find them. However, if it's 24 hours after somebody reports, the product is already restarted. We don't have any information about that. Thread dump and memory dumps are not available. So then we have to wait for another crash to happen. There's a lack of backup storage. That's a daily problem. With Kubernetes, whenever we get this kind of production issue, we are clueless. We can see that time OutOfMemory happened, however, we don't have much information to work with.

Therefore, having a thread dump and memory dump, and seeing how many objects were created would be useful. 

Sometimes we go to drill down. It says CPU utilization is very high. If you go inside, you'll see nothing, no information as to why. Similarly, when it says there were a lot of network errors, however, there is no information available on the network errors. It just says 10% network error, 20% network error. Yet if you drill down, there is no information available. You don't know whether it was a server that timed out, the port was not available, or some other network issue. We need more transparency in that regard. 

Sometimes the DNS Lookup service does not work very reliably unless you enable cache or something. Recently, I used the latest version of Kubernetes, and DNS cache was available, which was not available in the earlier version. Now we notice we're facing a lot of difficulties, like ENOENT errors, or "Host not found" exceptions. Every day they'd say it was an application problem, however, we ultimately figured out the DNS cache was not working properly. With the latest version, when we enabled it, things sorted out. However, when we were trying to drill down in the Kubernetes, it was not giving any information. There's no clear-cut information here as well as to why this was happening. 

I've used the solution for the last five years. 

It's very stable. We have not faced any such problem through Kubernetes. There are no bugs or glitches. It doesn't crash or freeze. 

The solution is scalable. 

We have 15 to 20 people using the solution.

However, it's a two-way setup, and all those things are done by DevOps. That's why I'd say 15 users. As for the users are concerned, we have, let's say, 100 people. All 100 in one or the other form are going to Kubernetes, seeing the ports and seeing that information based on the services they are working on.

I don't think so we have any technical support for Kubernetes. Our DevOps team typically would look into issues. 

I didn't do the implementation. We get all the things set up for us. That said, we see a lot of information. Generally, we are more interested to go through how many parts are running, and what memory is given to each part. All those things we explore. It's very useful and intuitive.

I don't deal with the pricing aspect of the solution. 

I, myself, tried something a long back, however, I'm not able to recall what it was. I am a developer, so my focus is more on the other side of things. DevOps might have looked into other options. I'm not sure. 

We are end-users.

We use the solution both on-premises and in the cloud. 

I'd rate the solution seven out of ten.