Google Kubernetes Engine Reviews

We primarily use Google Kubernetes Engine for hosting applications. We use it for hosting our microservices-based applications.

Google Kubernetes Engine (GKE) takes care of managing Kubernetes, including the main control plane. It also offers solutions for monitoring resources and handling external traffic, which is essential for us. Being a cloud-native solution, it relieves us from worrying about these operational aspects. Specifically, I can use infrastructure-as-code with tools like Terraform to provision clusters efficiently. Additionally, GKE enables us to use GitOps for application deployment.

The most valuable feature is that GKE manages the control plane. Control Plane management is a good feature. 

There is room for improvement in the cluster updates process. Specifically, when managing both non-production and production clusters, we need a sequential functionality. This means being able to upgrade non-production clusters first and then the production clusters. Having this sequential upgrade capability would be beneficial.

Therefore, I am looking for a sequential functionality for cluster upgrades.

I have been working with this solution for two years. I am currently working with version 1.25.

I would rate the stability an eight out of ten.  Though it's highly stable, sometimes it takes time for Google to provide support.

It is a highly scalable solution. I would rate the scalability a nine out of ten. It doesn't have any limit to endpoints. 

We currently have around 300+ endpoints for the applications hosted on it. We use this solution extensively and 24/7.

The support takes longer to response. There is room for improvement in the response time.  

Positive

Before Google Kubernetes Engine, we used OpenShift. We switched to Google Kubernetes Engine because OpenShift's support and complexity were causing challenges in maintaining stable impressions. Kubernetes evolved from Google and provided better stability, leading to the switch.

I would rate my experience with the initial setup a nine out of ten, where one being difficult and ten being easy. It is very easy to set up. It took just a couple of minutes. 

I needed to deploy using infrastructure as code, specifically with Terraform. It was done in-house; we deployed using Argo CD and Flux CD. It's a self-service deployment.  

Developers can deploy the solution themselves. We don't require anyone in between. However, the number of people required for maintenance depends on how many clusters we have. As of now, we have around five DevOps practitioners responsible for maintenance.

As for the return on investment, I would not be able to conclusively determine that. However, from a cost-saving perspective and the efficiency it brings, we have likely saved money and required fewer employees to manage the solution.

It has been efficient in that regard. I would say the ROI has been around 60%.

I would rate the solution's pricing a six out of ten, with one being low price and ten being high price. 

There are no additional costs. It's based on usage and the number of nodes and applications deployed.

I have experience with Kubernetes, Jenkins, CI/CD solutions, and GitOps. We evaluated other cloud providers, but we ultimately finalized and switched to Google Kubernetes Engine.

My advice would be to go for Google Kubernetes Engine if they seek stability, a well-tested product, and a reliable solution. It's suitable for those who value those qualities.

Overall, I would rate the solution an eight out of ten.

We use this solution to handle big data workloads in that specific NGK.

The solution is the latest and greatest. It has everything in it. You can have service and everything that you need.

There is room for improvement in terms of visibility and observability of solutions. One of the things I missed a bit is the visibility and availability of solutions. If I compare it to a different solution, it is a bit behind.

I have been using this solution for three years. We use the tool’s latest version; it was Kubernetes V1.24

The solution is quite stable.

I rate the solution’s stability a nine out of ten.

It is a scalable solution. We are using this solution for small enterprises.

I rate the solution’s scalability a ten out of ten.

The customer service and support are not too good.  Usually, the vendor acts as the middleman for support on GK, and it's not good. 

They should be more professional.

Neutral

We used automation for the initial setup. It was okay. So it wasn't too complex.

With automation, the deployment took about a week. But if you do it manually, it can take even just minutes or hours.

The deployment was done in-house with the help of one DevOps engineer. 

Maintenance is required for the solution. Moreover, maintenance is a bit of an issue because we don't have good observability for those issues, so I'm less positive about that. It was hard to maintain. Only one person is enough for the maintenance.

The pricing is the same, as far as I recall. So it's the same pricing. It depends on the compute pricing, so the pricing is relative. 

It's a monthly solution for the Control Plane, and pay-as-you-go for the workers, and the compute — it depends on how you define it. I don't think there are any extra costs. It is only pay for the Control Plane, and that's it.

I worked with AWS, specifically EKS (Elastic Kubernetes Service) and Postgres.

In brief, I would say that Amazon's support is better. The solutions are quite equal, but there is better integration for EKS with AWS services.

My advice to others looking to use Google Kubernetes Engine is to pay attention to maintenance and utilize automation and platform tools to build and manage it. Do not do it manually. 

Many maintenance errors should be managed automatically, especially by Google. Otherwise, you need to be very attentive to the cluster due to maintenance issues. I suggest automating most of the manual tasks. There is a distribution of Google called Autopilot that handles it, although I haven't personally worked with it. I recommend considering its usage rather than doing everything manually. Maybe it's related to the specific solution we chose, but ultimately, it's about pricing.

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

I am using Google Kubernetes Engine as a customer primarily for test cases and self-research. I mainly use their VMs with the free credits they have provided, and I am learning more about DevOps technology with DevOps tools integration with the Kubernetes clusters they provide with their free trial credits.

Google Kubernetes Engine is a cloud platform where I can host any applications for containers. It is a reliable cloud platform for hosting VMs and containers on the Kubernetes platform.

In terms of scalability, Google Kubernetes Engine is very convenient. Going through their portal to scale based on machine resource requirements is straightforward. It is convenient to add nodes.

The installation process for Google Kubernetes Engine is not stressful at all.

Regarding deployment in the cloud platform, it is simple because there are pre-configured configurations. All I have to do is select how powerful my machine needs to be, and they provide the business end. The entire process is stress-free.

I have no comment about the learning curve of Google Kubernetes Engine.

Regarding AI integration and features in Google Kubernetes Engine, there are currently none available.

I would appreciate seeing AI features added to Google Kubernetes Engine in the future. One potential feature could be AI scanning for configuration errors. This could help inexperienced users who might have trouble configuring their platform, acting as a guidance system.

I have been working with Google Kubernetes Engine for two years, though not very frequently.

Regarding stability with Google Kubernetes Engine, it is based on regions. While it can be region-dependent, I have not experienced any stability issues.

The most challenging aspect of Google Kubernetes Engine depends on one's understanding of the infrastructure side, particularly how to tune a particular machine to specific needs. It should not be problematic beyond one's experience level.

I have not used any other cloud-providing Kubernetes Engine solutions for comparison.

There are definite savings from Google Kubernetes Engine, particularly in terms of time management. I would estimate the savings to be around 40 percent.

Google Kubernetes Engine solution is expensive, as are all cloud solutions in general. On a scale of one to ten for pricing, I would rate it between seven and eight.

I have not used any other cloud-providing Kubernetes Engine solutions for comparison.

I currently have no specific disadvantages to report about Google Kubernetes Engine. I prefer to be called JD, which stands for Jedidiah. On a scale of one to ten, I rate Google Kubernetes Engine an 8.

We used to deploy microservices on the Java platform. It took a lot of work to manage these skill sets. With Kubernetes, it is easy to use and deploy. It was very convenient, mostly for scalability purposes.

The product could be cheaper.

I have been using Google Kubernetes Engine for one year.

The product is stable.

We started with 20 people who were migrating. Later, we migrated to other teams.

In the initial stage, It'll depend on our understanding level and how we've undergone training because we have a dedicated Engine. We were more inclined to learn something new. It is easy to use.

Google Kubernetes Engine integrates with your existing CI/CD pipelines. It's quite straightforward. Someone knowledgeable in DevOps helped develop a script for us. This script facilitated the integration of both pipelines with Kubernetes and streamlined the process for us.

The solution was pricey. If you have options, consider OpenShift as another platform that does the same.

We had a training session where they covered the features of Google Kubernetes Engine, allowing us to become familiar with all the commands that can be used in Kubernetes.

You won't need to have its feature to encrypt the data. Instead, a config map and secret feature are available. There's ample data recovery capability, particularly during operations like saving and performing other tasks. It's pretty impressive.

Google Kubernetes Engine provides certain features for free, especially for self-learning purposes. We install it on my local machine and deploy applications without incurring costs.

Overall, I rate the solution an eight or nine out of ten.

We use Google Kubernetes Engine, usually for containerizing.

Google Kubernetes Engine has helped our organization to deploy classes faster.

The most valuable feature of Google Kubernetes Engine is how you can automatically scale and load balance.

Google Kubernetes Engine's cost should be improved because it is high.

It would help if Google Kubernetes Engine could be made more customizable.

I have been using Google Kubernetes Engine for three years.

Google Kubernetes Engine is a pretty stable solution.

I rate Google Kubernetes Engine an eight or nine out of ten for stability.

Google Kubernetes Engine's scalability is pretty high.

I rate Google Kubernetes Engine a nine out of ten for scalability.

The solution’s initial deployment is pretty easy.

Our clients have seen a return on investment with Google Kubernetes Engine, which is diminishing because competitors now have better products.

I am using the latest version of Google Kubernetes Engine.

Google Kubernetes Engine is deployed on-cloud in our organization.

I would advise users to pay attention to the vendor lock-in. Sometimes, they reduce access to infrastructure. I would pay much attention to implementing the solution to have better visibility of the performance issues, especially concerning direct access to virtual machines.

Google Kubernetes Engine is pretty simple to use. It is pretty good as long as you use the solution within Google Cloud.

The solution's ease of use comes with the cost. Whoever wants to use the solution must weigh what's more important to them: the cost they'll pay to Google or the cost they'll pay their staff to make it work as well as they need.

Overall, I rate Google Kubernetes Engine an eight out of ten.

We use Google Kubernetes Engine primarily for our production clusters, running several microservices and main services. We have one main separate cluster for production testing, and for our actual production, we manage separate clusters.

Google Kubernetes Engine has helped us manage our infrastructure more securely, especially when separating projects and assigning permissions. This categorization enhances security as we streamline roles and permissions management.

The most beneficial feature is the ability to separate each project and manage permissions more effectively. This categorization is especially useful for security purposes. I find managing IAM roles in GCP to be better than AWS.

The primary area for improvement would be the complexity involved when working with Google Kubernetes Engine, especially when using Terraform. It can be more complex compared to AWS. 

Additionally, the process of managing IAM roles and integration with other Google services can be cumbersome and could use some simplification.

I have been using Google Kubernetes Engine for about one year to one and a half years.

We have not encountered any major stability issues with the Google Kubernetes Engine. Aside from the usual errors that occur day-to-day, such as image pull-back errors, we maintain a stable environment by using versions that are one or two versions behind the latest release.

The auto-scaling performance is really good in both GCP and AWS. I have not experienced any issues with auto-scaling capabilities, and they meet our demands efficiently.

Usually, our upper management takes care of any escalations to tech support, so I do not have direct experience with their customer service.

Neutral

The initial setup of Google Kubernetes Engine took me about two days. I primarily used Terraform scripts for deployment and testing.

Initially, when starting with Google Kubernetes Engine, I required some help, especially with configurations involving Helm charts and additional components such as the ingress controller. Once everything was set up, maintaining it became more manageable.

Google Kubernetes Engine has been cost-effective and has improved our operational productivity. However, GKE can be more expensive compared to AWS when it comes to certain services like Compute Engine. Integrating with multiple cloud providers is easier with GCP, making it a flexible solution for our diverse requirements.

I'm aware of the normal pricing, but it's not on top of my head. AWS is generally cheaper than GCP for most use cases. Costing fluctuates based on different purposes and sizes.

If you are using multiple cloud provider services, such as DNS management from DigitalOcean or S3 buckets from AWS, integrating with Google is simpler than AWS. For smaller functions, services like AWS Lambda can be more cost-effective than running them on GKE. It is important to utilize the proper tools for easy maintenance.

I'd rate the solution seven 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. 

In our company, the microservices are deployed into the containers in Google Kubernetes Engine.

Google Kubernetes Engine itself is quite a revolutionary concept. The scalability and reliability features of the product are fascinating, and they help a lot. With Google Kubernetes Engine, the area around deployment and the CI/CD implementation is easy.

The monitoring part requires some serious improvements in Google Kubernetes Engine, as it does not have very good monitoring consoles. If Google Kubernetes Engine comes up with monitoring consoles, that would be helpful.

During deployment, if the product provides users with an interactive kind of proper dashboard, which gives status or feedback on deployment, it will be helpful.

I have been using Google Kubernetes Engine for around two years.

I am satisfied with the stability offered by the solution. Stability-wise, I rate the solution a nine out of ten.

Google Kubernetes Engine is an industry leader. Scalability-wise, I rate the solution a nine out of ten.

More than 200 people in my company use the solution.

The use of the solution is increasing day by day in my company as Google Kubernetes Engine is the main platform we use for development. Our organization is rapidly growing, and new teams are being introduced.

Though I have not contacted the solution's technical support, through our company's regular channels, we keep watch for regular updates. If there is any escalation or ticket that was raised, our company gets good support from Google. I rate the technical support an eight out of ten.

Positive

I rate the product's initial setup phase a seven out of ten.

The solution is deployed on a hybrid cloud.

The time required to deploy the product depends on how many services you want to be deployed at a time in your environment. In general, deploying the product doesn't take much time since it can usually be done in ten to fifteen minutes. If everything goes smoothly during the deployment process, it won't take much time, and if something gets stuck, then it may require time for a person to deploy.

Initially, Google Kubernetes Engine was a little bit cheaper, but now its prices have been increased compared to the pricing model and the features that are made available by its competitors.

I recommend others try the solution and see if it suits and meets your budget. I recommend the solution to others because of the scalability, reliability, and ease of use it offers.

I rate the overall tool an eight out of ten.