Terraform vs Zookeeper: What are the differences?
Developers describe Terraform as "Describe your complete infrastructure as code and build resources across providers". With Terraform, you describe your complete infrastructure as code, even as it spans multiple service providers. Your servers may come from AWS, your DNS may come from CloudFlare, and your database may come from Heroku. Terraform will build all these resources across all these providers in parallel. On the other hand, Zookeeper is detailed as "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.
Terraform and Zookeeper are primarily classified as "Infrastructure Build" and "Open Source Service Discovery" tools respectively.
"Infrastructure as code" is the primary reason why developers consider Terraform over the competitors, whereas "High performance ,easy to generate node specific config" was stated as the key factor in picking Zookeeper.
Terraform is an open source tool with 17.7K GitHub stars and 4.83K GitHub forks. Here's a link to Terraform's open source repository on GitHub.
According to the StackShare community, Terraform has a broader approval, being mentioned in 510 company stacks & 313 developers stacks; compared to Zookeeper, which is listed in 116 company stacks and 48 developer stacks.
What is Terraform?
What is Zookeeper?
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What are the cons of using Terraform?
What are the cons of using Zookeeper?
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LaunchDarkly is almost a five year old company, and our methodology for deploying was state of the art... for 2014. We recently undertook a project to modernize the way we #deploy our software, moving from Ansible-based deploy scripts that executed on our local machines, to using Spinnaker (along with Terraform and Packer) as the basis of our deployment system. We've been using Armory's enterprise Spinnaker offering to make this project a reality.
We use Terraform because we needed a way to automate the process of building and deploying feature branches. We wanted to hide the complexity such that when a dev creates a PR, it triggers a build and deployment without the dev having to worry about any of the 'plumbing' going on behind the scenes. Terraform allows us to automate the process of provisioning DNS records, Amazon S3 buckets, Amazon EC2 instances and AWS Elastic Load Balancing (ELB)'s. It also makes it easy to tear it all down when finished. We also like that it supports multiple clouds, which is why we chose to use it over AWS CloudFormation.
I use Terraform because it hits the level of abstraction pocket of being high-level and flexible, and is agnostic to cloud platforms. Creating complex infrastructure components for a solution with a UI console is tedious to repeat. Using low-level APIs are usually specific to cloud platforms, and you still have to build your own tooling for deploying, state management, and destroying infrastructure.
However, Terraform is usually slower to implement new services compared to cloud-specific APIs. It's worth the trade-off though, especially if you're multi-cloud. I heard someone say, "We want to preference a cloud, not lock in to one." Terraform builds on that claim.
Terraform Google Cloud Deployment Manager AWS CloudFormation
Our base infrastructure is composed of Debian based servers running in Amazon EC2 , asset storage with Amazon S3 , and Amazon RDS for Aurora and Redis under Amazon ElastiCache for data storage.
We are starting to work in automated provisioning and management with Terraform , Packer , and Ansible .
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.
Terraform makes it so easy to deploy AWS and Google Cloud services, with the declarative approach avoiding so many headaches of manual work and possible mistakes.
- Infrastructure as Code.
- Central tool to deploy all infratructure: AWS, CloudFlare, StatusCake
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.
The entire AWS environments is described and setup using Terraform.