AWS Fargate Reviews

We process data mostly by scraping from retail chains on behalf of our customers, and then we homologate and clean that data for our customers to use in analytics displays and decision-making tools. The original architecture was very basic as we used applications such as Pentaho for all ETL workloads running on just fixed VMs from EC2, and then we moved these workloads into AWS Fargate. We didn't use any sophisticated Kubernetes clustering integration, so it was very basic in that case.

Currently, we are deploying workloads because this company has been going through a lot of merging and acquisition strategies. The company I am speaking of was a Mexican company that had 100% of the infrastructure over AWS, but as we integrated to manage the other companies we bought, we had to manage a different set of AWS services, such as Redshift and so on.

In our case, the workloads were not oriented to micro-services with AWS Fargate, just servers. The ETL flows we moved into Fargate using Pentaho weren't designed for micro-service architecture. The front end was very monolithic rather than micro-services oriented, and we had some simple API services, but not a formal micro-service architecture, so we didn't use AWS Fargate for that.

One of the best features of AWS Fargate is that it was useful for us because we didn't require to run container workloads and we didn't need to deal with the management of a Kubernetes cluster directly, and the ability to run those workloads just in a scheduled manner is also a great feature. Additionally, we reduced costs because the distribution over time of our workloads was not the whole day, so we had fixed VMs and some capacity that we weren't using.

AWS Fargate has definitely impacted our organization positively because before that, we couldn't accommodate the workload requirements as flexibly as we can with Fargate. We were able to process all the workload in a shorter time as we could increase the number of containers processing data by schedule. We provided operations because, in some cases, they required special workloads processed outside the schedule, and we offered some automations for them to just go to an internal application and configure their schedule and the amount of horsepower they require to increase in AWS Fargate, and it worked very easily. I understand that this could be accomplished with the auto scaling capabilities of Fargate, but as mentioned, the DevOps were just learning to use AWS Fargate and chose a simpler approach they considered less risky.

We are a venture builder company, and if we select AWS for our product. Our design is based on a serverless architecture model. ECS Fargate is the most convenient way in terms of scalability, integration, and cost control.

Thanks to the serverless model and easy integration features, a few customers have been able to onboard easily on our platform. We can handle a high volume of customer load and set up users to automatically raise requests within the platform, which ultimately provides a great experience.

I use AWS to manage all AWS services, including load balancing, scalability, availability, monitoring, and support for all services. I use it to buy minutes, buy a house, or buy a movie, and to make an estimation of the price. It also allows me to make comparisons with different AWS services.

All AWS services allow me to manage a wide range of applications and services. For example, deployment and management during deployment and monitoring are handled without any problems on the platform. 

I can set up my processes and manage my issues efficiently with AWS services. It offers me the responsibility to manage and solve different aspects and includes the time to decide on platform solutions, providing solutions in quizzes as the number one in the world. 

It serves as a guide to facilitating applications without limitation. AWS provides a good solution for cloud requests.

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.

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.

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.

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.