AWS Fargate Reviews

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.

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.

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.

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.

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.

Fargate is stable because it uses Lambda functions that can be triggered as needed, which adds to its reliability.

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.

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.

Neutral

I am also engaged with Azure Compute Services on a project involving a CI/CD pipeline as a DevOps engineer.

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.

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.

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.

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.

We host our solutions, providing workflow management for companies running on Fargate. We create legal documents for them using expert systems and deliver business intelligence throughout the entire process. 

Additionally, everyone from our company uses Fargate since the deployment process is automated. After configuring the CI/CD process, no one needs to manage, only monitor.

Fargate is awesome for scalability and its serverless nature, managing the scalability automatically when used with ECS. We have workloads with only two instances running, and when needed, we can see services spawning ten new instances while everything continues running. When the workload decreases, the instances are automatically reduced.

Fargate is beneficial for hosting our solutions and providing workflow management, creating legal documents, and delivering business intelligence. All AWS solutions using containers, particularly those for horizontal scaling, are supported by Fargate. Its scalability and serverless nature make it a perfect hosting solution as it manages the scalability automatically when used with ECS, especially with the consistent process for deploying new solutions.

There is a tool named Compose that helps in converting the Docker Compose file into a Kubernetes file. For ECS and Fargate, AWS reads a Dockerfile and helps with conversion. 

However, I am uncertain if it's ready for deployment after conversion. Despite this, manual configurations are very easy, and we manage to get by the process.

I have not faced any blocking challenges in Fargate.

The scalability is seamless, spawning necessary instances automatically with ECS when the workload increases and reducing instances when it decreases.

I have not needed to deal with AWS support directly for Fargate.

Neutral

We also use Azure Container Service, which is similar to AWS ECS. ACS is the same solution with different names due to trademarks, offering a similar experience.

The initial setup is straightforward. We have a well-established process of deploying new solutions using OpenAPI specifications and Elastic Container Registry, making it easy for the infrastructure team.

We have a well-defined deployment process where the backend team delivers a configurable image in the Elastic Container Registry (ECR), and the infrastructure team deploys these images.

Fargate is billed based on the amount of processing and storage required for the solution to run, and the pricing is very fair.

We also evaluated Azure Container Service, which offers a similar experience.

I rate Fargate ten out of ten. 

The most significant advantage is the unified configuration for all containers deployed by ECS, allowing seamless integration with services like OpenAI or Google Gemini and secure handling of access keys and secrets.

I am working with AWS Fargate for a little over two years. I am a developer, and we use it internally to deploy applications within our company.

Fargate handles the scalability for us automatically. When there is high traffic, it creates as many instances as possible to serve the traffic. We don't have to worry about scaling up or down, which saves us cost and time. This automatically adjusts based on our needs without our intervention and focuses on the business logic.

Fargate's integration with other AWS services is really good. For example, we can easily connect it to CloudWatch for monitoring. It's easy to convert Lambda functions to run on Fargate without much effort. This integration capability enhances our workflow and productivity.

Sometimes, Fargate can be really hard to configure. You need a certain level of expertise to work with it, particularly around dynamic scaling. Simplifying configurations around scalability and integration with AWS services would be beneficial.

I have been using AWS Fargate for a little over two years.

I would say the stability is nine out of ten based on my experience. I've never had issues with Fargate; it just runs as expected once configured properly.

I would rate the scalability as eight out of ten. Once you have your strategy defined, AWS handles the scaling efficiently, and you can monitor how well it's functioning.

I've not had to contact technical support for Fargate as it runs smoothly without any issues.

Positive

I did not use any other solution before Fargate, as I joined a team that was already using AWS services.

The initial setup was not as simple as Lambda, due to the complexity of configurations needed. However, using CloudFormation simplifies the process significantly.

Deploying Fargate didn't require a lot of people because once the CI/CD pipeline is set up, it orchestrates the deployment. So, not much manual intervention is needed.

In general, AWS services can be quite pricey. The cost depends on how you configure the services. I would rate the pricing as seven out of ten.

No other solutions were evaluated. My team already used AWS services for everything.

Fargate is ideal for scenarios where Lambda would not suffice, especially for functions with longer runtime requirements. It's well-suited for background jobs and tasks that might take longer time.

I'd rate the solution eight out of ten.

We use AWS Fargate primarily to reduce costs when compared to EC2. Fargate allows us to run services on demand with the benefits of EC2 instances.

Using AWS Fargate helps us consolidate resources. With a discount program, we can run more services at the same price, providing better resource allocation.

The most valuable feature of AWS Fargate is its ability to run on demand without the constant run time of basic resources. It operates with a similar philosophy to Lambda functions, providing the benefits of EC2.

AWS Fargate needs improvement in terms of setup complexity. Currently, it is difficult to configure compared to other services like EC2 instances or Lambda functions.

I have used AWS Fargate a little bit.

The stability of AWS Fargate is very high. It is very stable.

AWS Fargate scales very well, similar to if you configure EC2 properly.

I haven't used AWS customer service for Fargate yet. However, generally, they are very customer-driven and provide exceptional support, especially if you have a premium support plan.

Positive

I needed to get help from other resources since Fargate's deployment was complex for me to handle alone.

I am not familiar with the exact pricing of AWS Fargate since we have special deals as part of a bundle of services.

I'd rate the solution eight out of ten.

We use the solution for source information. Vendors have some tactics on our cloud-native application platform, allowing them to use serverless compute for on-demand requests. With AWS, it will cost very little and might be more affordable for the client. We use this service to reduce costs and increase efficiency for Kubernetes or cloud gateway applications.

By using a server's compute resources, one can observe the resource metrics. With AWS, one can determine when servers will be used based on CloudWatch results. For example, CloudWatch informs the application and service platform when the hit ratio has reached the threshold value. Then the service decides that some nodes should be launched in AWS. For instance, when hosting a media application, the hit ratio can grow when needed and shrink when needed. This allows us to satisfy the customer at the utmost level. For cloud-native microservices applications on AWS, this reduces errors. 

Service computing is not as straightforward compared to other computing services. It requires more effort to use effectively. In comparison to traditional cloud computing services, service computing demands a deeper understanding and a more complex setup. Additionally, integrating it with an existing infrastructure can be challenging. 

I have been using AWS Fargate for approximately one and a half years.

The solution is stable and robust.

I rate the solution’s scalability a ten out of ten.

AWS provide documentation. If you encounter further problems, you can contact the AWS support team.

The initial setup is straightforward. If you use CloudVault with AWS Fargate, it consists of approximately fifty states. For testing, it sometimes takes some time to load and may experience downtime for about an hour.

For example, we have some customers in France who are using a modeling platform for cloud services on AWS. They have increased their capacity by three times. Initially, they had one factory, but after using the service model, they increased the number of factories to three. This expansion significantly boosted their business operations.

AWS is an on-demand service.

For customers who use AWS to organize their application environment, leveraging AWS's computing capabilities can lead to cost optimization. They can use the AWS cloud platform model to access services on demand.

Overall, I rate the solution a ten out of ten.

We deploy our code as container images and use Fargate for autoscaling and managing these containers within the Fargate ecosystem. That's how we utilize it.

We have encountered some issues recently. For example, AWS released a new feature called a better quarter, which greatly helped us. Before that, we faced challenges in vertically scaling our workload. After the release of the new feature, we were able to scale vertically by utilizing sixteen CPU units and a large memory capacity. We also experienced issues with scaling in, as it would abruptly terminate the task. However, AWS introduced a feature called task protection that has been helpful in resolving this issue.

Nevertheless, during this period, we were exploring a move to Spark due to the challenges we encountered, which is why I rated the overall product as an eight out of ten.

We have been using it for three years.

Fargate itself is a stable product. We are quite satisfied with its performance.

I would rate scalability as a nine. Although we haven't thoroughly tested it in all scenarios to determine the breaking point, based on our current testing, I am quite satisfied with its scalability.

We are currently live with our first version, and we expect to see a return on investment with our next version. So, we anticipate an ROI. 

We have obtained a significant discount on the pricing, so I wouldn't consider it as expensive. It's quite reasonable.

On a scale from one to ten, I would rate it around eight. I would recommend using the product based on the specific workloads they are dealing with. For instance, if they have strict sub-second performance requirements, I might not suggest it. The decision depends on their specific requirements, and I would advise accordingly.

AWS Fargate is an Amazon-managed service for Kubernetes.

AWS Fargate is used for anything that's containerized and they are all Kubernetes-oriented. It's a nice out-of-the-box pre-packaged solution for deploying. It has good integration with EKS and container registry. It makes it an easy way to use the AWS Kubernetes service.

The most valuable feature of AWS Fargate is its ease of use.

AWS Fargate could improve the privileged mode containers. We had some problems and they were not able to run.

I have been using AWS Fargate for approximately two years.

AWS Fargate is stable.

We have a number of workloads that are running on Kubernetes and on AWS Fargate that are operating well.

We have a collection of applications and reporting tools that are running in that containerized environment and some of them are public facing. For example, we have the Envirofax Data Warehouse and those receive millions of hits a month. Our data analytics data warehouse team is mostly using the solution.

The initial setup of AWS Fargate is straightforward.

The maintenance is done from AWS, such as patches and updates.

I rate the price of AWS Fargate a four out of five.

I rate AWS Fargate an eight out of ten.

We use this solution to build, host and develop websites for our clients, as well as deploy and manage containers.

We appreciate the simple use of containers within this solution, it makes managing the containers quick and easy.

We would like to see some improvement in the process documents that are provided with this product, particularly for auto-scaling and other configuration tools that are a bit complicated.

We have been using this solution for a year now.

In our experience, this is a stable solution.

We have found this to be a scalable solution.

The initial setup for this solution was a little complex. It is very customizable, but that is not straightforward to carry out. 

We now use templates that make the process much easier.

We would advise that this solution has a slightly-higher price point than others on the market. There is a free plan available for start-ups, but the free and lower range licensing models do not provide the full functionality.

I would rate this solution a seven out of ten.