Google Kubernetes Engine Reviews

The product helps us to manage Docker easily using automation. 

The solution simplified deployment, making it more automated. Previously, Docker required manual configuration, often done by developers on their computers. However, with Google Kubernetes Engine, automation extends to configuration, deployment, scalability, and viability, primarily originating from Docker rather than Kubernetes. Its most valuable feature is the ease of configuration. 

The tool's configuration features need improvement. 

I have been using the product for two years. 

We had some stability issues in the past. I rate the tool's stability a nine out of ten. 

I rate the solution's scalability a ten out of ten. Google Kubernetes Engine has around 100-200 users in my company. 

Google's support is good and fast. It's available 24/7. 

It will take some time for someone to get used to it, and there's a learning curve that shouldn't be skipped or neglected. But then, things will start to click, and you'll notice that the product is easy to deploy. The deployment setups are readily available from Google or Microsoft. You need to configure them, which can be done with these scripts and by automating your CI/CD processes. It's all interconnected with CI/CD.

Google Kubernetes Engine can be deployed in-house. 

The tool's licensing costs are yearly. 

The inter-system communication, including the ports used, is all described within Docker. The product manages these Docker pieces and builds the bigger picture. 

We integrate it as part of our DevOps script. It's all connected, with actions for the desktop, the CD Engine, and deployment on managed Kubernetes instances on Google Cloud. It's all automated and works well together.

I rate the overall product a nine out of ten. 

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.

I have deployed the solution as a service into my private cloud, as well as into Azure infrastructure.

Google Kubernetes Engine is useful for cloud-native business applications, especially microservices-based architectures since business applications require scalability and resilience and must be highly available. Typically, Google Kubernetes Engine is used to deploy business applications and also to manage the integrations with the cloud services. There are a lot of SaaS solutions as service offerings provided by the Google Cloud Platform, so it helps with the integration to compile the solutions in the business space or, basically, the cloud-native space.

Google is the founder of Kubernetes. Google invented Kubernetes platform, and then later on, at some point in time, they had open-source scripts. Since Google started offering open-source scripts, a lot of other players in the market have adopted the same strategy for their products. Google Kubernetes Engine made a late entry into the market, but the good part that I like about it is that you have a seamless way of creating highly scalable and highly available solutions with it. On the tip of a command, you can scale in or scale out, and it offers every robust platform to implement DevOps processes for your automation solutions. The product fully supports the IaC concept.

The product's stability is an area of concern where improvements are required. Google Kubernetes Engine needs to mature more to be able to offer more stability compared to its competitors like Amazon and Microsoft, which have allowed for aggressive growth due to the area covered in terms of offering the complimentary services offered around Kubernetes. Google is behind even though it offers a robust platform. Google needs to offer more intensive services to fulfill the needs of customers and serve as a one-box or one-stop solution that covers everything enterprises need. Google needs to evolve more in terms of the richness of the services offered.

I haven't worked full-fledged with Google Kubernetes Engine. since I have used it from an experimentation perspective. It is mainly Kubernetes that I have worked for for more than three years. Google Kubernetes is basically a managed service, but Kubernetes 1.24 is what I have extensively used.

Stability-wise, I rate the solution a seven out of ten.

Scalability-wise, I rate the solution a six to seven out of ten.

My company's clients who use the solution are enterprise-sized businesses.

I have no experience with the solution's technical support because I have not done any production-related work revolving around Google Kubernetes Engine. I believe that Google provides better technical support, but I don't have the relevant background to speak about it.

I rate the product's initial setup phase a five or six on a scale of one to ten, where one is a difficult setup phase, and ten is an easy setup phase.

The concept revolving around Kubernetes is inherently complex when it comes to its setup phase. Kubernetes is not an easy domain to design and operate. The adoption of Kubernetes from a production perspective can be a bit of a complex task, not only for Google but for every other vendor in the world. The complexity is not much for a person who understands Kubernetes. With Google, considering its lack of maturity compared to the competitors, I will say the complexity during the setup phase may be a bit higher, based on which I rate the setup phase a six out of ten.

The solution is deployed on a public cloud by Google.

The solution can be deployed in a week since the major effort is in building the application, and getting the application to the production stage takes at least a week or so.

From an ROI perspective, the tool should be better, but since I have not done any production-grade application deployment on Google Kubernetes Engine, I won't be able to comment on the product's ROI part. As per my understanding, the overall Kubernetes ecosystem ensures a high ROI because it promotes the ability of a business, and that's what the platform is all about.

I rate the product's price a six on a scale of one to ten, where one is low price and ten is high price. The product is competitively priced.

I rate the overall product a seven 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.