What is our primary use case?
AWS Fargate is a serverless compute engine for containers that works with Elastic Container Service (ECS) and Elastic Kubernetes Service (EKS). We use it for running containers without managing the server or cluster of Amazon Web Services EC2 instances. It allows us to focus on applications instead of managing infrastructure.
How has it helped my organization?
Fargate allows horizontal or vertical auto-scaling which affects businesses by enabling easy scaling up and down of applications in response to changes in demand. This capability becomes particularly beneficial when there is increased traffic, as it utilizes auto-scaling and allows setting maximum and minimum limits for instances, improving efficiency. Additionally, it offers cost savings through its serverless model by optimizing AWS serverless costs, especially when using Lambda functions.
What is most valuable?
Fargate is better if you need more flexibility or are on a budget. It allows for focusing on applications instead of managing infrastructure. We can also store images inside ECS or create a container using that image. It lets us integrate with load balancing, unifying storage volumes to improve instances' launch time, making it highly beneficial for various projects.
What needs improvement?
I would like to see enhanced faster application scaling and better integration with the elastic file system to unify storage volumes and improve the launch time of instances.
It requires enhancements to orchestrate containers more effectively and handle resource limits like CPU and memory constraints, particularly when load balancing, as it affects the auto-scaling configurations.
For how long have I used the solution?
I have been working with the AWS platform, including Fargate, for one year while exploring new features. I am also blogging about it and creating short videos.
What do I think about the stability of the solution?
Fargate is stable because it uses Lambda functions that can be triggered as needed, which adds to its reliability.
What do I think about the scalability of the solution?
Fargate is scalable. It works with auto-scaling, allowing applications to scale up and down based on demand changes, making it versatile for various business operations.
How are customer service and support?
I have interacted with technical support through emails and ticket management systems like Jira. That said, there is room for improvement. I would appreciate better direct contact with clients regarding pre-requisites and specific uses of resources.
How would you rate customer service and support?
Which solution did I use previously and why did I switch?
I am also engaged with Azure Compute Services on a project involving a CI/CD pipeline as a DevOps engineer.
How was the initial setup?
The initial setup involved defining CPU, memory, volumes, and images required for Fargate. It requires familiarity with CPU architecture, subnets, DNS, contained images, and resource definitions.
What about the implementation team?
Currently, three to four people in my team are working as cloud engineers with me, and within the larger organization, there are about 11 to 20 employees working on it.
Which other solutions did I evaluate?
I have worked with Azure Compute Services for managing an e-commerce website project with front-end, back-end, and database management using CI/CD pipelines and microservices.
What other advice do I have?
I recommend using AWS Fargate as it offers serverless computing capabilities with integration into load balancing, making it a good and beneficial solution.
I'd rate the solution six out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Disclosure: I am a real user, and this review is based on my own experience and opinions.