Google Kubernetes Engine Reviews

We have somewhere around 20 microservices that we need to deploy for our product. We are using Kubernetes Engine to deploy those 20 microservices.

The feature that I like the most is the ease of use as compared to AWS. Its ease of use is very high, and I can quickly deploy clusters with a simple template.

Their documentation is a little here and there. Sometimes, the information is not clear or updated. Their documentation should be a little bit better.

They have a good marketplace, but it is still evolving and is not as mature for some services.

I've been using this solution for about a year.

It is pretty stable. I did not encounter any problems.

In the last 10 months, scaling was easy. There is an auto-scaling feature where I can just provide them with how many nodes I require, or I can create custom node pools where, for particular applications, I can deploy certain nodes. I haven't had any issues with scalability.

We have four or five users. They are DevOps engineers. Only two users are the owners. They have deployed Kubernetes Engine, and they manipulate the workload. Its usage would be twice or thrice a week.

I haven't encountered any issues so far, and I haven't raised any doubt with them. So, I haven't interacted with them. We are currently managing four or five projects with Kubernetes Engine. We haven't had any issues with any of them.

It is easy to set up. In AWS and other clouds, the support for Kubernetes is minimal, but in Google Cloud, it is much easier to set up. I would rate it a five out of five in terms of ease of setup.

It was set up in-house.

It is competitive, and it is not expensive. It is almost competitive with AWS and the rest of the cloud solutions.

We are spending around 3K USD per month. There are four projects that are currently running, and each one is incurring a cost of around 3K USD.

For Kubernetes, the components have to be broken down into machine cost, storage cost, and application cost, if you are using any private applications or any images. If you look at the compute instances for GCP, there are hundred different tiers. For example, you have general-purpose E2 machines, then you have high-compute machines, and then you have the GPU machines for T4. Those are pretty standard compute instances. Kubernetes Engine is just a layer on top of these compute instances to control your entire microservices architecture.

I would rate it a four out of five in terms of pricing.

I am yet to explore all of its features. I would rate it an eight out of ten.

We use the platform for transforming our product from VM-based to container-based. It involves migrating old monolithic applications to containers, which takes years.

One valuable feature of the product is openness to global networks, which allows for integration and deployment across multiple regions, which is only sometimes possible with other cloud providers.

The product's integration with third-party vendors needs improvement. 

I have been working with Google Kubernetes Engine for approximately two to three years.

I rate the product stability an eight. 

I rate the product scalability an eight. 

The initial setup process is simpler and more user-friendly than other cloud providers.

Google Kubernetes Engine has made the deployment process easier than Amazon and Azure. It is a good product and often more cost-effective.

I recommend it to others and rate it an eight out of ten. 

The Google Kubernetes Engine is used for managing data workloads. As a part of the platform engineering team, we are uncertain about the specific data workloads running. Primarily, the application teams wanted to run specialized workflows, while the data engineering workflow preferred to opt for GKE. After a thorough evaluation of the different versions of the Kubernetes platform over a week, we informed the application teams about the available options. In case of confusion, we clarify the advantages and disadvantages of each feature. However, when the application teams express their preference for GKE, we support their decision, as they comprehensively understand the use cases for both EKS and GKE. This invariably leads to a smoother onboarding process, as we are well-equipped to cater to their specific requirements.

We are working and monitoring HTTPS on GKE. It has a great manager for license management. The controller policy item for that particular feature doesn't seem visible anywhere, which might be a bonus, but we are unfamiliar with it. As we explore the multiple flavors of Kubernetes clusters, we aim to enforce similar policies across all clusters. Overall, everything looks good, and hand tools are one of the unique features that set us apart from other vendors.

The solution's support is terrible. Even the GCP engineers have been tracing some concerns. The dedicated GKE support engineer often tries to find solutions when raised tickets. Support engineers don't know about it. Regarding AWS or Azure support, GKE support needs a lot of improvement. The documentation is another issue. Even though the support engineers keep referring to the documentation, it's not current because the cloud keeps evolving. They need to update the documentation frequently. The controller policy will be compatible with version 1.26 of Kubernetes. We assumed we needed to upgrade to 1.26 fast, as we were running 1.25. However, after spending two and a half months, we realized it works with 1.25 as well. Even the GCP engineers were not aware that it was compatible with 1.25. 

Google Kubernetes Engine has a limited layer of support, and not many workloads are feasible. Some application teams need the Kubernetes platform. However, we can't recommend GKE, even though the cost would be lower than EKS and OpenShift. We can't trust GCP support when major issues arise.

I have been using Google Kubernetes Engine as an integrator for one year.

The initial setup is relatively easy, but unfortunately, some issues repeat. For instance, we always try to showcase our capabilities during working sessions with vendors, like when they come for a demo or even with AWS. However, when we require assistance, the installation seems straightforward, yet when an issue arises, we struggle to resolve it. We're trying to schedule a working session with GCP, but they are unavailable. Despite multiple follow-ups, when they finally arrive, the experience is not very productive, as the person often searches for solutions. Overall, the installation process is smooth. If we stick to the application, it seems to be working fine.

We use Terraform. It will take some time, but the cluster installation on the Google Kubernetes Engine will be completed within four or five hours.

I'm familiar with Kubernetes, but not many customers are using GKE. For instance, I've been involved in one project using GKE for about six to seven months; before that, another project used GKE for a year. However, I can only recall one project that used GKE for four months, about one and a half years ago. My work revolves around Kubernetes, but it's not exclusively focused on GKE.

The maintenance of the solution is at an intermediate level, as there are some issues. We encounter problems with the Ingress controller and the GKE clusters. We have some open cases with GKE and have been trying to find solutions. Some aspects seem easy, while others are challenging to troubleshoot. Moreover, the documentation lacks comprehensive recommendations for GKE; we often have to rely solely on Google's official documentation.

Overall, I rate the solution a five out of ten.

Mainly, we target SMEs for Kubernetes services. Currently, we have a few customers, and they expect more customized experiences.

The features are typical Kubernetes, but Google One offers a better GUI-based deployment. It's more sophisticated and integrates well with other services, providing a better customer experience.

There is room for improvement in this solution. For example, auto-scaling can be complex. We expect it to be easier to set up and manage, even for our customers.

We started recently. I have around one and a half months of experience with it.

The stability is good. I would rate it a nine out of ten.

It is a scalable solution. I would rate the scalability a nine out of ten.

The customer service and support are good. 

Positive

The initial setup is pretty simple; we can deploy a cluster within a minute. Just choose a region and the required parameters.

One person can handle it unless they're inexperienced.

Pricing is a bit expensive compared to some other products, but it's acceptable.

I would rate the pricing an eight out of ten, where one is a low price, and ten is a high price. 

The auto-scaling can be complicated, so they should be prepared for that. It is difficult to hand over the solution to customers because of scaling up and scaling down issues. If Google improves that aspect, it'll be easier to manage.

Overall, I would rate the solution a nine out of ten.

I use the solution to orchestrate different containers that need microservice architecture.

The product’s dashboard is very intuitive. The solution is very useful for monitoring.

The solution does not have a visual interface. 

The solution could be improved by adding some visual drag-and-drop features.

I have been using the solution for the past three years.

The solution is very stable.

The solution is very scalable.

The initial setup is a little bit complex.

The deployment can be done in one to three months.

The product is a little bit expensive.

The solution is cloud-based. There are more tools available that are more visually intuitive. Overall, I rate the solution a nine out of ten.

We use it for all applications.

The logs are important for detecting problems in our clusters. I use the fragment with this property, which is valuable.

The current version is quite good. However, a new version, 1.26, is not yet stable. GKE offers regular, stable, and rapid versions, but this one is being used for the rapid version and hasn't been thoroughly tested yet. I think DCP may be quicker in releasing more stable versions.

I have been using Google Kubernetes Engine for two years. For SunTrust, we use version 1.21, which is old. But on ComMaster, we use version 1.24.

It is not very stable, I would rate the stability an eight out of ten. 

I would rate the scalability a ten out of ten. Around 30 users are using Google Kubernetes Engine in your organization.

The customer service and support team is quite good. 

Positive

We can't say the initial setup was easy, but it wasn't difficult either. The deployment process was pretty fast. 

The pricing is average. For example, Tanzu Build Service is very expensive, but generally, it's okay. However, I understand that the on-to service is very expensive.

Overall, I would rate the solution a seven out of ten. 

We use this solution to run the AI models that we have developed for anomaly detection, cloud workload prediction, as well as setting up clusters.

We appreciate that it is quite easy to set up a Kubernetes cluster in Google Cloud, using the managed services within this solution.

We would like to see some improvement in the ease of integration with this solution.

We would also like to see the addition of some automated realization of data pipelines.

We have been using this solution for nearly three years.

We have found the stability of this solution to be good during our time working with it.

This is an easily scalable solution.

The setup for this solution is reasonably simple.

We implemented this solution using our team of in-house, GCP-certified architects and operators.

We would rate this solution an eight out of ten.

The autoscaling feature is the most important feature in Google Kubernetes Engine. It also supports containerization. The solution is available across AWS, GCP and Azure and is seamless.

It does not require much investment if you move from AWS to GCP or Azure. The entire cloud process remains the same, with only minor changes.

The console for this solution could be improved because it is very limited. In addition, features like a desktop for the Docker image, drag and drop into a node could be added.

In terms of visualization, the solution could also provide some integration with other tools. We have heard about Grafana and AppDynamics offering these features, but they still require better tools. Google is going in the right direction because they believe in open source integration and give opportunities to other players to work with them. However, they should provide packages where they integrate more features to demonstrate more encouragement in the marketplace.

Training, tutorials, tooling, samples, and more case studies should be included in the next release.

We used this solution for one year.

The solution is stable, and I think even more stability will occur over time. Google Kubernetes Engine is moving in the right direction, especially when you consider concepts of Docker image, pods, nodes, clusters, control planes, data planes, gateway, and the ingress. Many projects run in production on Google Kubernetes Engine, and companies partner with AWS, GCP, and Azure to provide training and assist in completing modules regarding portals.

Google Kubernetes Engine is a scalable solution.

The setup was confusing. We were able to install it locally, but it was slow.

Because I worked in production, I did not use technical support directly. It was required but most likely very minimal.

I do not know specific details about the price, but I believe Google Kubernetes Engine is cheaper than Pivotal Cloud Foundry.

We compared Google Kubernetes Engine with Pivotal Cloud Foundry and found that Google was better.

I rate this solution seven out of ten. I believe Google Kubernetes Engine is the best solution in the market.

Google Kubernetes Engine's most valuable features are microservices and its acquisition rate, which is very useful for scaling perspective.

The user interface could be improved. In the next release, I'd like to see better notifications.

I've been using Google Kubernetes Engine for a few years. 

Kubernetes is stable because it has scalable architecture, so if any part goes down, it starts from the other parts. 

Kubernetes is scalable.

The initial setup was simple.

I would rate Kubernetes' pricing four out of five.

I also evaluated VMware, which is more expensive than Kubernetes.

I would give Kubernetes a rating of eight out of ten.

Google Kubernetes Engine is used for orchestrating Docker containers. We have 30 or 40 customers working with this solution now. We'll probably see 10 to 15 percent growth in the number of customers using Google Kubernetes Engine in the future. 

We've been using Kubernetes Engine for five years.

Google Kubernetes Engine is less stable in some highly complex deployments with many nodes. However, those are probably edge cases.

Google Kubernetes Engine is scalable 

The ease of deployment for Google Kubernetes Engine is about average.  

Google offers yearly and monthly subscriptions. 

We don't prefer Google over Amazon or any other Kubernetes solution. It depends on the technology stack that our customers choose based on project needs. It's not better than the others.

I rate Google Kubernetes Engine eight out of 10.