Google Kubernetes Engine vs HPE Ezmeral Container Platform comparison

"Stability-wise, this solution is really good."

"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 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."

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

"I am impressed with the product's output scaling."

"GKE is easier to understand and use than Elastic Kubernetes Service."

"The deployment of the cluster is very easy."

"Google Kubernetes Engine has positively impacted my organization in migration-based projects such as on-prem to GCP and AWS to GCP, as we migrated more than thousands, even 10,000s workload in Google Kubernetes Engine."

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

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

"I would rate the scalability a seven out of ten."

"The solution does not have a visual interface."

"The product could be cheaper."

"The product’s visible allocation feature needs improvement."

"The network configuration has to be simplified."

"The console for this solution could be improved because it is very limited."

"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."

"t is not very stable."

"The modernization in Ezmeral could be improved."

"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 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."

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

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

"I would rate the solution's pricing a nine out of ten. The tool costs around 3000 dollars per month. There are no additional costs apart from these."

"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."

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

"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."

"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."