Research Firm Deploys AWS Fargate to Accelerate Innovation

A research and development arm of a global business, this organization is responsible for forging innovations that will drive the company’s future. As the business continues to expand, it has relentlessly pursued DevOps automation as a means to reach its business objectives faster and at scale. With automation set across other areas of its cloud infrastructure, the R&D firm sought to streamline its container processes. While it originally chose to use Amazon ECS for its ability to easily containerize applications, the firm elected to move to AWS Fargate on its introduction as it allows engineers to run containers without having to manage servers or clusters.

The AWS Fargate Solution 

To mitigate infrastructure management overhead and help developers focus on strategic infrastructure initiatives, we recommended AWS Fargate. According to Amazon, AWS Fargate is “a compute engine for Amazon ECS that allows you to run containers without having to manage servers or clusters.” AWS Fargate is a good fit as it completely manages task execution; only tasks are run and you only pay for those tasks you run.

With AWS Fargate, the R&D team avoids the need to manage EC2 instances as ECS takes the containers provisioned by Fargate and automatically scales, load balances, and manages their scheduling. This makes it much easier for the team to build and manage containerized applications.  

Because Fargate separates the task of running containers from managing the underlying infrastructure, developers can specify the resources that each container requires, and AWS Fargate handles the rest. 

HashiCorp Terraform Fargate Cluster Creation

Using a HashiCorp Terraform module, the team creates a Fargate Cluster, enabling required tasks to run in it. The Terraform file contains all task-related configurations, which clusters to create and more. The first application to use the Fargate solution is Netbox, an open-source web application that the firm uses to help manage and document its network. For it, a Terraform module is created that in turn creates a Fargate cluster with the required tasks and services for running the Netbox application. 

Grow Automation and Productivity 

Prior to AWS Fargate-enabled automation, engineers spent a great deal of time on Amazon EC2 instance with tedious manual configuration and monitoring to manage the lifecycle and placement of both tasks and running containers.  Now, with the AWS Fargate solution, the R&D team is able to increase the productivity of its developers, giving them more time to spend on strategic infrastructure initiatives. In addition, the engineering team saves time as AWS Fargate is easy to get up and running, saving on training. With more development resources, the organization is able to develop solutions faster that enable scientists to focus on building groundbreaking, customer-impacting technologies.

What’s Next

The new AWS Fargate solution is easily scalable, allowing the team to easily add new applications beyond the Netbox deployment. They are able to do so securely with immutable container technology. All of which sets the team up for ongoing success with automation that supports the spirit of continuous process and quality improvements facilitated by DevOps automation. 

For additional reading on enhanced automation with container technology:

• Enterprise media company balances improvements in efficiency and builds innovative digital experiences with a Docker and Kubernetes architecture.
• A major US airline paired KOPS, AWS Kubernetes clusters, and Ubuntu CIS benchmarked images to give it a secure cloud foundation that allows airline teams to effectively, efficiently and securely deploy services without slowing down development.
• A gaming developer wanted a no-downtime migration to a best-in-class AWS Kubernetes solution with full CI/CD. Containerizing the developer’s systems using Docker and Kubernetes, we completed an AWS migration of the firm’s highest volume services to Kubernetes without downtime or interruption to the customer. 
• For an application modernization project at an enterprise media organization, we created a Kubernetes factory for two deployment pipelines, allowing the customer to go to a self-service portal and create production-ready Kubernetes clusters. The result is a 14-28x increase in the firm’s release frequency.