Amazon EC2 Container Service vs Zookeeper: What are the differences?
What is Amazon EC2 Container Service? 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.
What is Zookeeper? Because coordinating distributed systems is a Zoo. A centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services. All of these kinds of services are used in some form or another by distributed applications.
Amazon EC2 Container Service and Zookeeper are primarily classified as "Containers as a Service" and "Open Source Service Discovery" tools respectively.
"Backed by amazon" is the top reason why over 97 developers like Amazon EC2 Container Service, while over 9 developers mention "High performance ,easy to generate node specific config" as the leading cause for choosing Zookeeper.
According to the StackShare community, Amazon EC2 Container Service has a broader approval, being mentioned in 794 company stacks & 391 developers stacks; compared to Zookeeper, which is listed in 116 company stacks and 48 developer stacks.
What is Amazon EC2 Container Service?
What is Zookeeper?
Need advice about which tool to choose?Ask the StackShare community!
Sign up to add, upvote and see more prosMake informed product decisions
What are the cons of using Amazon EC2 Container Service?
What are the cons of using Zookeeper?
Sign up to get full access to all the companiesMake informed product decisions
Sign up to get full access to all the tool integrationsMake informed product decisions
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.
Initially, Stitch only supported real-time updates and addressed this problem with a MapReduce job named The Restorator that performed the following actions:
- Calculated the expected totals
- Queried Cassandra to get the values it had for each counter
- Calculated the increments needed to apply to fix the counters
- Applied the increments
Meanwhile, to stop the sand shifting under its feet, The Restorator needed to coordinate a locking system between itself and the real-time processors, so that the processors did not try to simultaneously apply increments to the same counter, resulting in a race-condition. It used ZooKeeper for this.
Like many large scale web sites, Pinterest’s infrastructure consists of servers that communicate with backend services composed of a number of individual servers for managing load and fault tolerance. Ideally, we’d like the configuration to reflect only the active hosts, so clients don’t need to deal with bad hosts as often. ZooKeeper provides a well known pattern to solve this problem.
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 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.
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.
I don't like AWS BUT Pagely's VPS-3 makes it work. I still use FireHost for most things
Zookeeper manages our state, and tells each node what version of code it should be running.
Used Zookeeper as the resource management system for Mesos/Marathon services.