Google Kubernetes Engine and Amazon Elastic Container Service are competing in the container management space. Google Kubernetes Engine shows advantages in multi-cloud environments and ease of deployment for specific tasks like machine learning, while Amazon Elastic Container Service benefits users deeply integrated with AWS through ease of AWS service integration and cost-effectiveness.
Features: Google Kubernetes Engine offers robust autoscaling, global multi-cloud integration, and ease in application deployment. It efficiently manages the control plane with strong integration within the Google ecosystem, making it highly suitable for machine learning tasks. Amazon Elastic Container Service emphasizes seamless integration with AWS services, task definitions for applications deployment, and strong integration with AWS CloudWatch for metric-based scaling, offering ease of use for those familiar with AWS infrastructure.
Room for Improvement: Google Kubernetes Engine users encounter challenges with IAM roles and Terraform usage, coupled with a need for better documentation and third-party integration. Amazon Elastic Container Service users comment on its complex management and look for better pricing models. Additionally, its user interface can be cumbersome, and improved cross-platform integrations are needed.
Ease of Deployment and Customer Service: Google Kubernetes Engine is praised for its deployment capability across diverse cloud environments, including hybrid and multi-cloud settings, yet complexity in support is noted. Amazon Elastic Container Service is reported to be easier within AWS infrastructure, but users find responsiveness in Amazon's support advantageous for quick problem resolution.
Pricing and ROI: Amazon Elastic Container Service presents a pay-as-you-go model, viewed as beneficial within AWS resources but costly with extensive scaling. Google Kubernetes Engine may have higher initial costs due to integration capabilities, justifying ROI through its operational efficiency and flexibility. While Amazon offers cost benefits for users in its ecosystem, Google provides integration value for varied cases.
This saving is achieved since, with EC2, the entire virtual machine must be running regardless of workload, whereas Fargate eliminates this cost.
By migrating from AWS to Google Cloud Platform, we have saved a lot of time and money.
We do not rely heavily on technical support from AWS as we have our own teams managing the infrastructure.
Small REST APIs, containerized databases, and simple front-end solutions are possible, but larger applications requiring more resources are not feasible.
Scalability becomes an inherent capability in the cloud context, and this service does well in that regard.
Amazon Elastic Container Service has a scalability rating of ten out of ten.
The autoscaling capabilities of Google Kubernetes Engine have significantly impacted our operations.
The stability of Amazon Elastic Container Service is excellent.
Amazon Elastic Container Service is mostly very stable.
A suitable option would be N2D or beyond, which can onboard all the workloads quickly.
When it comes to new-age services around AI, particularly in the areas of LLMs and genomics, these services are not fully available in our region's availability domain.
Currently, when scaling with Amazon Elastic Container Service, I have to choose between monitoring CPU or memory usage to scale up or scale out; there is no option to monitor both simultaneously.
When looking at the web interface, it feels kind of slow due to the many features involved.
Log observability could be made easier so someone from high school can use it without having technological expertise.
It would be helpful if I could easily find log information in a particular namespace without needing to write certain labels.
Amazon Elastic Container Service is quite cheap compared to Google, particularly for hosting databases.
Our customers often do a trade-off between requiring services at particular SLA levels and being willing to pay a premium price to us as partners.
Instead, we only pay for the hardware we use, which results in cost-cutting.
Google is considered cheaper compared to AWS, making it suitable for smaller to medium companies concerning cost.
The on-demand nodes are quite expensive.
It inherently offers scalability by default, without our IT teams needing to take the extra load to make the services available for our end users.
Amazon Elastic Container Service allows the opportunity for low cost, as it is less expensive than EC2, to get used to all these concepts, paradigms, and techniques.
Additionally, it provides excellent horizontal scalability.
The most valuable aspect of Google Kubernetes Engine (GKE) is its managed nature, which significantly reduces the burden on our platform team.
GKE is easier to understand and use than Elastic Kubernetes Service.
What I find most valuable is the ability to focus solely on my product without worrying about the Kubernetes infrastructure itself.
Amazon Elastic Container Service (Amazon ECS) is a highly scalable, high-performance container orchestration service that supports Docker containers and allows you to easily run and scale containerized applications on AWS. Amazon ECS eliminates the need for you to install and operate your own container orchestration software, manage and scale a cluster of virtual machines, or schedule containers on those virtual machines.
Kubernetes Engine is a managed, production-ready environment for deploying containerized applications. It brings our latest innovations in developer productivity, resource efficiency, automated operations, and open source flexibility to accelerate your time to market.
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