Amazon EC2 Container Service vs Ansible: What are the differences?
Developers describe Amazon EC2 Container Service as "Container management service that supports Docker containers". Amazon EC2 Container Service lets you launch and stop container-enabled applications with simple API calls, allows you to query the state of your cluster from a centralized service, and gives you access to many familiar Amazon EC2 features like security groups, EBS volumes and IAM roles. On the other hand, Ansible is detailed as "Radically simple configuration-management, application deployment, task-execution, and multi-node orchestration engine". Ansible is an IT automation tool. It can configure systems, deploy software, and orchestrate more advanced IT tasks such as continuous deployments or zero downtime rolling updates. Ansible’s goals are foremost those of simplicity and maximum ease of use.
Amazon EC2 Container Service and Ansible are primarily classified as "Containers as a Service" and "Server Configuration and Automation" tools respectively.
Some of the features offered by Amazon EC2 Container Service are:
- Docker Compatibility
- Managed Clusters
- Programmatic Control
On the other hand, Ansible provides the following key features:
- Ansible's natural automation language allows sysadmins, developers, and IT managers to complete automation projects in hours, not weeks.
- Ansible uses SSH by default instead of requiring agents everywhere. Avoid extra open ports, improve security, eliminate "managing the management", and reclaim CPU cycles.
- Ansible automates app deployment, configuration management, workflow orchestration, and even cloud provisioning all from one system.
"Backed by amazon", "Familiar to ec2" and "Cluster based" are the key factors why developers consider Amazon EC2 Container Service; whereas "Agentless", "Great configuration " and "Simple" are the primary reasons why Ansible is favored.
Ansible is an open source tool with 38.2K GitHub stars and 16K GitHub forks. Here's a link to Ansible's open source repository on GitHub.
According to the StackShare community, Ansible has a broader approval, being mentioned in 960 company stacks & 587 developers stacks; compared to Amazon EC2 Container Service, which is listed in 794 company stacks and 391 developer stacks.
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By 2014, the DevOps team at Lyft decided to port their infrastructure code from Puppet to Salt. At that point, the Puppet code based included around "10,000 lines of spaghetti-code,” which was unfamiliar and challenging to the relatively new members of the DevOps team.
“The DevOps team felt that the Puppet infrastructure was too difficult to pick up quickly and would be impossible to introduce to [their] developers as the tool they’d use to manage their own services.”
To determine a path forward, the team assessed both Ansible and Salt, exploring four key areas: simplicity/ease of use, maturity, performance, and community.
They found that “Salt’s execution and state module support is more mature than Ansible’s, overall,” and that “Salt was faster than Ansible for state/playbook runs.” And while both have high levels of community support, Salt exceeded expectations in terms of friendless and responsiveness to opened issues.
Since #ATComputing is a vendor independent Linux and open source specialist, we do not have a favorite Linux distribution. We mainly use Ubuntu , Centos Debian , Red Hat Enterprise Linux and Fedora during our daily work. These are also the distributions we see most often used in our customers environments.
For our #ci/cd training, we use an open source pipeline that is build around Visual Studio Code , Jenkins , VirtualBox , GitHub , Docker Kubernetes and Google Compute Engine.
For #ServerConfigurationAndAutomation, we have embraced and contributed to Ansible mainly because it is not only flexible and powerful, but also straightforward and easier to learn than some other (open source) solutions. On the other hand: we are not affraid of Puppet Labs and Chef either.
Currently, our most popular #programming #Language course is Python . The reason Python is so popular has to do with it's versatility, but also with its low complexity. This helps sysadmins to write scripts or simple programs to make their job less repetitive and automating things more fun. Python is also widely used to communicate with (REST) API's and for data analysis.
We began our hosting journey, as many do, on Heroku because they make it easy to deploy your application and automate some of the routine tasks associated with deployments, etc. However, as our team grew and our product matured, our needs have outgrown Heroku. I will dive into the history and reasons for this in a future blog post.
We decided to migrate our infrastructure to Kubernetes running on Amazon EKS. Although Google Kubernetes Engine has a slightly more mature Kubernetes offering and is more user-friendly; we decided to go with EKS because we already using other AWS services (including a previous migration from Heroku Postgres to AWS RDS). We are still in the process of moving our main website workloads to EKS, however we have successfully migrate all our staging and testing PR apps to run in a staging cluster. We developed a Slack chatops application (also running in the cluster) which automates all the common tasks of spinning up and managing a production-like cluster for a pull request. This allows our engineering team to iterate quickly and safely test code in a full production environment. Helm plays a central role when deploying our staging apps into the cluster. We use CircleCI to build docker containers for each PR push, which are then published to Amazon EC2 Container Service (ECR). An
upgrade-operator process watches the ECR repository for new containers and then uses Helm to rollout updates to the staging environments. All this happens automatically and makes it really easy for developers to get code onto servers quickly. The immutable and isolated nature of our staging environments means that we can do anything we want in that environment and quickly re-create or restore the environment to start over.
The next step in our journey is to migrate our production workloads to an EKS cluster and build out the CD workflows to get our containers promoted to that cluster after our QA testing is complete in our staging environments.
Ansible is the deployment tool for people who don't like deployment tools. It's close to scripting, doesn't pollute your servers with agents or centralized servers, and just makes immediate sense. The entire stack at Cloudcraft.co is orchestrated by Ansible. What does that mean? Beyond the obvious of installing packages and configuring services, Ansible coordinates all the machines into a working deployment: It adds API servers to the loadbancer pool, opens ports on the DB server for the backend servers to connect, gracefully upgrades services in a rolling fashion for zero-downtime deployments etc. And it's so easy to use, it's easier to use than doing things by hand, meaning it's a deployment tool you'll actually use every time!
We use the container service so that we can deploy our application services with Dockerfiles, so that we can test locally and deploy to AWS simply.
Additionally, the ability to scale containers and have them automatically restart in case of failure is very helpful to our operations.
We use Ansible to synchronize the few configuration-options we've taken on our CoreOS-Machines. This makes deployment even easier and the fact that it's Agentless made the decision even easier.
Ansible is used in both the development and production deployment process. A playbook couple with a Vagrantfile, easy deploys a local virtual machine that will mirror the setup in production.
I use Ansible to manage the configuration between all of the different pieces of equipment, and because it's agentless I can even manage things like networking devices all from one repo.
We use the EC2 registry for secure private container registration. When used in combination with I AM roles we can control customer access to repos on and individual basis.
Amazon EC2 is our primary application hosting solution. Most applications are not exposed on the internet and use a virtually private cloud to interact with each other.
- Configuration management:
- deploy/install all web/app environments
- simple with Galaxy and playbooks.
- No need any pre-installed agent on remote servers.
With a little forethought, ECS can handle a good portion of my development stack as though it were production. 12 Factor configuration makes this a breeze.