AWS Fargate Reviews

We use Fargate in order to scale data processing for retail data. The company I am working for processes data for retail customers like consumer packaged goods producers that sell through Walmart,  and other retail chains. 

The company I work for processes sales, inventory, and order data from those retail chains. We use Fargate to scale the data processing for those kinds of files.

For microservices, we mostly use a combination of Fargate within Lambda.

Previously, we had this kind of processing in Docker containers deployed on EC2 instances. To scale that, the operation was pretty hard. So, we made a change in the architecture, and instead of deploying those containers on EC2 instances, we deployed them on Fargate. So, the application scales pretty easily. 

The application autoscaling within Fargate simplifies the application scaling process. 

The application is pretty simple, so we're not using any complex or added integration features. We're just using it to deploy the containers. We trigger the processes by directly calling the services already exposed by the container. The only service we integrated with Fargate was Amazon EventBridge to ensure we have both on-demand and scheduled capacities to handle peak hours. That's pretty much it. We do not integrate it with SQS or any other queuing system.

The most valuable feature of Fargate is that it's self-managed. You don't have to configure your own clusters or deploy any Kubernetes clusters. This simplifies the initial deployment and scaling process. 

For example, using Spot Instances with AWS after configuring a Kubernetes cluster might make sense. But Fargate's approach is pretty straightforward. My team, including certified cloud engineers, can deploy containers using ECR and Fargate without any issues.

If there are any options to manage containers, that would be good. That relates more to the cost point.

For example, over the next three months, I'll be making a comparison between solutions like CAST AI and other software-as-a-service platforms that offer Kubernetes management with an emphasis on cost reduction. 

Instead of deploying in private, you can use CAST AI with any Kubernetes provider and any cloud, for example. This may solve scaling problems. So, if it allows you to reduce costs by four percent or more of your processing expenses, that AI-assisted Kubernetes-managed solution is something to consider.

After saving on scaling using containers with a self-managed cloud cluster, I think the next step is to use an additional approach. Cloud providers may help you reduce some costs, but a specialized service focused on optimizing your Kubernetes resources in relation to your container usage could be beneficial.

For example, this kind of solution allows you to not only auto-select the instances for cluster nodes based on the current processing load but also define containers that can be spot instances in terms of fault tolerance.

In those cases, the solution will deploy your containers on spot instances, distribute your spot-tolerant processes across the cluster, and potentially achieve additional cost reductions. 

You cannot do that with something like Fargate. That's the next step for a company that needs to scale its processes to another level. Maybe that's worth considering.

I have been using it for two years. 

We currently do not have any paid support from AWS as adding customer support would increase our monthly costs by about 10%. 

However, due to the strategic alliance with AWS, we enjoy the support our account managers provide. I don't need support for troubleshooting or operational issues, as we haven’t had any. 

But especially when starting to use a new service, we have a cloud engineer or cloud architect available from our account manager to assist us.

So, considering that, I would rate the customer care from AWS for Fargate highly. Although my account is very small, with just eight servers, I'm still treated well as a customer.

I've used EC2, S3, Lambda, Fargate, API Gateway, Step Functions, etc.

For security, particularly with container security, we use Azure Patch Manager and AWS Inspector to inspect all our containers, ensure that all necessary patches are applied, and manage any risks associated with the libraries we are using. But I don’t see that as a security feature of Fargate; rather, it is security that stems from the AWS ecosystem.

We perform a scalable monthly review of all the containers and apply the patches that are recommended by those automated tools.

Because Inspector does not automatically apply the patches, we have to do it manually over the ECR containers.

Initially, we noticed some impact on our billing, but it wasn't significant in our overall infrastructure costs. We spend more on fixed EC2 instances and on databases, as we have a large database cluster for our big data applications.

Our main focus isn't cost; it's about being agile and providing a serverless, scalable solution for data processes like ETL—extraction, transformation, and loading. Thus, cost was not our primary concern.

The maturity you have in deploying serverless capabilities is crucial. For example, if your process takes less than 15 minutes, then you should consider AWS Lambda or other cloud function services. If your process may take longer than that, then Fargate is the way to go, especially when you are starting to deploy. 

Your first goal is to provide scalability to your business, particularly to your commercial areas. Once you achieve scalability, you can then focus on cost efficiency. 

If cost becomes a significant factor as you scale up, you might consider managing a Kubernetes cluster with an auto-scaling service to simplify Kubernetes management. When you need that level of scalability, cloud services like Fargate or even Lambda may not provide the cost efficiency you require. That's my current perspective on this.

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

AWS Fargate is a fully managed service provided by Amazon. When using any application, we have services that we need to manage. Instead of managing it ourselves, AWS takes care of it. We just need to create a cluster, do normal patching, and everything is managed by AWS.

AWS Fargate is a fully managed service, and it's very easy to use compared to other services like Elastic Beanstalk Service (EBS). AWS provides the necessary resources so we don't have to do much ourselves; we just need to create a cluster. This makes patching and management straightforward. 

AWS also offers great integration with other AWS services, like using Aurora Serverless for database management, which eliminates the need to manage a database server. 

Overall, if we, as enterprise customers, are using Fargate for our applications, we should not face any problems.

As I have not worked with Fargate extensively, I do not have any specific improvements.

I have knowledge of Fargate but have not worked with it extensively. I mention having a new project in the pipeline where I plan to use Fargate.

Currently, my organization is using Elastic Beanstalk Service (EBS), however, we plan to switch to AWS Fargate in a new project.

AWS Fargate is costly compared to AWS EBS. However, it is worth the money, especially for enterprise customers.

AWS Fargate is easily manageable. We just need to create a cluster and focus on our infrastructure. Customers do not need to take downtime since everything is managed by AWS with no downtime. 

Overall, I would rate it as nine out of ten.

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.

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.

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.