Google Kubernetes Engine vs HPE Ezmeral Container Platform comparison

"GKE's plugin management and configuration sync are excellent features. The amount of data it provides is good, and I've been able to integrate it with the things I need."

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

"Management and deployment of a lot of containers could be very easy."

"Google Kubernetes Engine is helping tremendously to make the high availability of the service."

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

"Google Kubernetes Engine is very scalable, in fact, that is one of the best features."

"The initial setup was very easy because it's like a Google platform as a service. It's just one button to set it up. The deployment took only a few minutes."

"The deployment of the cluster is very easy."

"If customers focus on primary apps or if they are using them for data science, this is a good solution."

"If customers focus on primary apps or if they are using them for data science, this is a good solution."

"The stability of the HPE Ezmeral Container Platform is good, and I rate it an eight out of ten."

"I use the Firebase tool with GKE and it would be helpful if the solution can give notifications when we reach the budget limit."

"The pricing could be more competitive. It should be cheaper."

"The management UI could be improved. When looking at the web interface, it feels kind of slow due to the many features involved."

"The network configuration has to be simplified."

"t is not very stable."

"I would like to see the ability to create multiple notebook configurations."

"An area in which Google Kubernetes Engine could improve is configuration."

"The support is not that great. I rate the support a three or four out of ten."

"HPE Ezmeral Container Platform is not user-friendly and has many parts that are more difficult than Cloudera. It is also a complex solution and has low features for data management."

"The modernization in Ezmeral could be improved."

"If a customer is focused on process automation or API usage, I would not recommend this solution, but it is good to use for Data Science."

"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."

"The tool's licensing costs are yearly."

"The pricing for GKE is dependent on the type of machine or virtual machine (VM) that is selected for the nodes in the cluster. There is a degree of flexibility in choosing the specifications of the machine, such as the number of CPUs, GPUs, and so on. Google provides a variety of options, allowing the user to create the desired cluster composition. However, the cost can be quite steep when it comes to regional clusters, which are necessary for high availability and failover. This redundancy is crucial for businesses and is required to handle an increase in requests in case of any issues in one region, such as jumping to a different region in case of a failure in the Toronto region. While it may be tempting to choose the cheapest type of machines, this may result in a limited capacity and user numbers, requiring over-provisioning to handle additional requests, such as those for a web application."

"We are planning to use external support, and hire a commercial partner for it."

"The price for Google Kubernetes Engine could be lower - I'd rate its pricing at three out of five."

"The product is a little bit expensive."

"This is an open source solution, so there is no pricing or licensing."

"Currently, it costs around $1000 per month which sorted our deployment. So once we get more clients, having a huge suffix, costs can go up."