My main use case for Amazon Linux is deploying Django websites, apps, and APIs with Next.js. I handle deployment using Nginx and manage the complete setup for deploying full projects. A specific example is the Django API backend with a Next.js frontend for the web dashboard at 71lbs.com, where users must log in. The entire project is deployed on Amazon Linux. I manage the integration of new deployments and created a setup using Nginx and the supervisor provided by Amazon Linux.
I currently use Amazon Linux for a web application deployed on AWS on EC2. The web application is built on Amazon EC2, which is the virtual machine infrastructure as a code service, and Amazon Linux is Amazon's Linux distribution built for increased efficiency with use on EC2. I have built my web application on EC2 instances in a managed instance group and Amazon Linux is the distribution that I use due to it being hosted on AWS.
Senior Software Engineer at a financial services firm with 10,001+ employees
Real User
Top 20
Jan 13, 2026
We run EC2 instances on Amazon Linux, and we use Amazon Linux-based Docker images as well, which serve as a container for our data science users. On top of Amazon Linux, we have installed all data science-supported software that they use, including Jupyter Notebook and R. We also run APIs on top of Amazon Linux. We run Fargate containers which are again based on Amazon Linux. We run FastAPI, and then we host our APIs on top of it, allowing our UIs to connect to this API in the backend. There are multiple use cases for Amazon Linux. The first thing is installing R and R packages. It is not easy because for R to be installed, you need to solve many dependencies. Most of those dependencies are already available in Amazon Linux. Our organization also does a lot of security settings, given that it is a banking domain, and all those settings are straightforward. There is nothing we cannot do on Amazon Linux. It is easily customizable, and there are many packages available that can be installed on it. The very good thing is the AWS support we get; if there are any issues, we can reach out to the support team, and they will troubleshoot and help us, through which we learn and can resolve issues ourselves next time.
The use cases for this in our company is that we have a customer that internally uses it for several applications, and they are a telecommunications company that has virtual machines and Linux machines for several purposes.
Software Engineer at a tech services company with 501-1,000 employees
Real User
Top 10
Nov 28, 2025
I switched to a different organization where I am using AWS. We are dealing with EKS and ECS. I work with API Gateways, Amazon Linux, Lambda functions, and S3 storage buckets, among other services. Currently, I am building my own product, which is deployed in AWS services using ECS.
My primary use case for Amazon Linux is hosting production-grade applications and microservices running on EC2, EKS, and container-based architectures such as Docker and Kubernetes. Amazon Linux provides continuous security and maintenance updates, including rapid vulnerability patches, which helps keep workloads secure with minimal manual effort. Its security hardening features and minimal footprint reduce the attack surface, offering better protection against common threats. In my previous organization, almost all our servers ran on Amazon Linux, and I worked with it extensively for about five years. In my current role, we continue to use Amazon Linux primarily for cloud migration projects and for running microservices that require a lightweight, AWS-optimized Linux environment. In my current role at Quantum Integrators, I am involved in migrating SAP workloads and other applications from a private cloud to AWS, and Amazon Linux has been a core part of this process due to its consistent performance, seamless integration with AWS services, and minimal configuration effort during migration.
Cloud Architect at a manufacturing company with 10,001+ employees
Real User
Top 20
Nov 5, 2025
With AWS, I work with products involving networking, migration, and other services. Currently, I work in an industry where I use Amazon Linux for various use cases.
I work with Kubernetes tools. My job is L3 support and I troubleshoot Red Hat-based systems and Kubernetes. Those are my two areas and that is all I do. When a client's system breaks down, it is my job to fix it as much as possible. In the last 12 months, I have been troubleshooting systems and training in Kubernetes. I deploy applications atop it. I mostly use it as a server for various DevOps concerns. For example, I have a Kubernetes server running on Red Hat Enterprise Linux and Ansible server running on Red Hat Enterprise Linux. It is a DevOps pipeline that is fed by these separate servers. I just duplicate installations of my clients' machines in order to troubleshoot. The idea is that I am presented with a problem, a broken system. If I can clone it, I do and then I try to fix it locally on my own machine before I present the solution back to the client. It varies slightly, depending on what the clients are using it for. In my very last case, about 2 or 3 weeks ago, there were etcd clusters running on an Ubuntu machine managing a Patroni installation. I tried to set that up on my own systems and started troubleshooting from there.
Amazon Linux is a secure and stable distribution for cloud environments, optimized for AWS performance. It is widely adopted by developers seeking minimal disruption in deployment and management, offering a seamless operational experience.Developed by Amazon Web Services, Amazon Linux provides an environment streamlined for performance on AWS infrastructure. By offering long-term support and regular security updates, it ensures crucial security and reliability. It is tailored to enhance...
My main use case for Amazon Linux is deploying Django websites, apps, and APIs with Next.js. I handle deployment using Nginx and manage the complete setup for deploying full projects. A specific example is the Django API backend with a Next.js frontend for the web dashboard at 71lbs.com, where users must log in. The entire project is deployed on Amazon Linux. I manage the integration of new deployments and created a setup using Nginx and the supervisor provided by Amazon Linux.
I currently use Amazon Linux for a web application deployed on AWS on EC2. The web application is built on Amazon EC2, which is the virtual machine infrastructure as a code service, and Amazon Linux is Amazon's Linux distribution built for increased efficiency with use on EC2. I have built my web application on EC2 instances in a managed instance group and Amazon Linux is the distribution that I use due to it being hosted on AWS.
We run EC2 instances on Amazon Linux, and we use Amazon Linux-based Docker images as well, which serve as a container for our data science users. On top of Amazon Linux, we have installed all data science-supported software that they use, including Jupyter Notebook and R. We also run APIs on top of Amazon Linux. We run Fargate containers which are again based on Amazon Linux. We run FastAPI, and then we host our APIs on top of it, allowing our UIs to connect to this API in the backend. There are multiple use cases for Amazon Linux. The first thing is installing R and R packages. It is not easy because for R to be installed, you need to solve many dependencies. Most of those dependencies are already available in Amazon Linux. Our organization also does a lot of security settings, given that it is a banking domain, and all those settings are straightforward. There is nothing we cannot do on Amazon Linux. It is easily customizable, and there are many packages available that can be installed on it. The very good thing is the AWS support we get; if there are any issues, we can reach out to the support team, and they will troubleshoot and help us, through which we learn and can resolve issues ourselves next time.
The use cases for this in our company is that we have a customer that internally uses it for several applications, and they are a telecommunications company that has virtual machines and Linux machines for several purposes.
I switched to a different organization where I am using AWS. We are dealing with EKS and ECS. I work with API Gateways, Amazon Linux, Lambda functions, and S3 storage buckets, among other services. Currently, I am building my own product, which is deployed in AWS services using ECS.
My primary use case for Amazon Linux is hosting production-grade applications and microservices running on EC2, EKS, and container-based architectures such as Docker and Kubernetes. Amazon Linux provides continuous security and maintenance updates, including rapid vulnerability patches, which helps keep workloads secure with minimal manual effort. Its security hardening features and minimal footprint reduce the attack surface, offering better protection against common threats. In my previous organization, almost all our servers ran on Amazon Linux, and I worked with it extensively for about five years. In my current role, we continue to use Amazon Linux primarily for cloud migration projects and for running microservices that require a lightweight, AWS-optimized Linux environment. In my current role at Quantum Integrators, I am involved in migrating SAP workloads and other applications from a private cloud to AWS, and Amazon Linux has been a core part of this process due to its consistent performance, seamless integration with AWS services, and minimal configuration effort during migration.
With AWS, I work with products involving networking, migration, and other services. Currently, I work in an industry where I use Amazon Linux for various use cases.
My use case for Amazon Linux is mostly for running containers. I am using SELinux for enhanced security in Amazon Linux, and it is helpful for me.
I work with Kubernetes tools. My job is L3 support and I troubleshoot Red Hat-based systems and Kubernetes. Those are my two areas and that is all I do. When a client's system breaks down, it is my job to fix it as much as possible. In the last 12 months, I have been troubleshooting systems and training in Kubernetes. I deploy applications atop it. I mostly use it as a server for various DevOps concerns. For example, I have a Kubernetes server running on Red Hat Enterprise Linux and Ansible server running on Red Hat Enterprise Linux. It is a DevOps pipeline that is fed by these separate servers. I just duplicate installations of my clients' machines in order to troubleshoot. The idea is that I am presented with a problem, a broken system. If I can clone it, I do and then I try to fix it locally on my own machine before I present the solution back to the client. It varies slightly, depending on what the clients are using it for. In my very last case, about 2 or 3 weeks ago, there were etcd clusters running on an Ubuntu machine managing a Patroni installation. I tried to set that up on my own systems and started troubleshooting from there.