We performed a comparison between Amazon Elastic Container Service and Google Kubernetes Engine based on real PeerSpot user reviews.
Find out in this report how the two Container Management solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."We use the product for website and email database hosting."
"ECS is flexible and easy to use."
"The product's initial setup was very straightforward and not complex."
"The most valuable feature is the volume size they offer."
"The most valuable feature of the solution is its scalability."
"I like Amazon EC2 Container Service's elasticity."
"The cloud services are readily available."
"The solution is simple to access."
"The product has no downtime."
"The initial setup is very easy. We can create our cluster using the command line, or using our console."
"The main advantage of GKE is that it is a managed service. This means that Google is responsible for managing the master node in the Kubernetes cluster system. As a result, we can focus on deploying applications to the slaves, while Google handles any updates and security patches. The fact that GKE is fully integrated into the Google ecosystem, including solutions such as BigQuery and VertexAI. This makes it easier for us to integrate these tools into our process. This integration ultimately speeds up our time to market and reduces the time and effort spent on managing infrastructure. The managed aspect of GKE allows us to simply deploy and utilize it without having to worry about the technicalities of infrastructure management."
"I am satisfied with the stability offered by the solution."
"We hardly have a breakdown. It's been very stable."
"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 logs are important for detecting problems in our clusters."
"Stability is perfect for me."
"The solution needs to be more usable."
"Sometimes, the instances fail under the ECS container cluster, and we have to manually go and find out the black sheep in the ECS container instance. We had an issue earlier where one of the instances under the ECS container cluster went down, and we were not able to identify that instance. The instance got terminated, but a new instance did not come up. Therefore, I had to manually get that instance up. It could be optimized better. In production, we normally cannot sustain such things. It can be optimized in terms of instances, durability, and serving the requests of customers."
"For Amazon EC2 Container Service, providing the ability for users to select specific processor, memory, disk, and interface types might be an ideal feature. But, the practicality of offering all possible physical combinations is nearly impossible due to the underlying physical machines. AWS and Azure organize options into groups based on essential components like powerful processors or critical interfaces, considering physical restrictions. While expanding these choices is conceivable, it may not be feasible from a financial and practical perspective. Customers generally comprehend this limitation, as even in their own data centers, exact physical machine requirements are often a result of a combination of factors such as price, availability, and new machine generations."
"There is room for improvement in the licensing costs. There can be better licensing costs."
"Amazon Elastic Container Service’s initial setup is a bit difficult."
"The solution's stability is an area of concern where improvements are required."
"In the next release, they could add some customization options for high computer workloads."
"The solution is expensive compared to other alternatives like Azure."
"The notifications are not informative."
"The solution does not have a visual interface."
"The monitoring part requires some serious improvements in Google Kubernetes Engine, as it does not have very good monitoring consoles."
"The pricing could be more competitive. It should be cheaper."
"Our critique is that we have to do too much work to get the cluster production-ready."
"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 think that security is an important point, and there should be additional features for the evaluation of data in containers that will create a more secure environment for usage in multi-parent models."
"There are some security issues, but it might just be because we are not up to speed yet as much as we should be and so we haven't found it in the documentation yet. That's why I don't want to confuse this. Still, it could be a little bit easier to understand and implement."
More Amazon Elastic Container Service Pricing and Cost Advice →
Amazon Elastic Container Service is ranked 8th in Container Management with 46 reviews while Google Kubernetes Engine is ranked 9th in Container Management with 32 reviews. Amazon Elastic Container Service is rated 8.4, while Google Kubernetes Engine is rated 8.0. The top reviewer of Amazon Elastic Container Service writes "An easy to compute solution that can be used to take complete workloads to the cloud". On the other hand, the top reviewer of Google Kubernetes Engine writes "The auto-scaling feature helps during peak hours, but the support is not great". Amazon Elastic Container Service is most compared with Red Hat OpenShift Container Platform, Microsoft Azure Container Service, VMware Tanzu Mission Control and Linode, whereas Google Kubernetes Engine is most compared with Linode, Kubernetes, Rancher Labs, Red Hat OpenShift Container Platform and Trend Micro Deep Security. See our Amazon Elastic Container Service vs. Google Kubernetes Engine report.
See our list of best Container Management vendors.
We monitor all Container Management reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
