Codefresh vs Terraform: What are the differences?
Codefresh: CI/CD Tailor-Made For Docker. Automate and parallelize testing. Codefresh allows teams to spin up on-demand compositions to run unit and integration tests as part of the continuous integration process. Jenkins integration allows more complex pipelines; Terraform: 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.
Codefresh belongs to "Container Tools" category of the tech stack, while Terraform can be primarily classified under "Infrastructure Build Tools".
Some of the features offered by Codefresh are:
- Instant Dev, test and feature preview environments: Enables all team members to run any image as a standalone or composition for feature preview, manual testing, bug reproduction and more. Collaborate on features before pushing them into staging and production.
- Testing with every step: Configure your pipeline to run integration and unit tests with every step
- Instantly test all code changes in the Codefresh build system before pushing to staging & production. Run integration, unit tests in parallel.
On the other hand, Terraform provides the following key features:
- Infrastructure as Code: Infrastructure is described using a high-level configuration syntax. This allows a blueprint of your datacenter to be versioned and treated as you would any other code. Additionally, infrastructure can be shared and re-used.
- Execution Plans: Terraform has a "planning" step where it generates an execution plan. The execution plan shows what Terraform will do when you call apply. This lets you avoid any surprises when Terraform manipulates infrastructure.
- Resource Graph: Terraform builds a graph of all your resources, and parallelizes the creation and modification of any non-dependent resources. Because of this, Terraform builds infrastructure as efficiently as possible, and operators get insight into dependencies in their infrastructure.
"Fastest and easiest way to work with Docker" is the primary reason why developers consider Codefresh over the competitors, whereas "Infrastructure as code" was stated as the key factor in picking Terraform.
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.
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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 .
Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.
Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!
Check Out My Architecture: CLICK ME
Check out the GitHub repo attached
We went looking for one thing "CI/CD with on-demand environment creation".
Within only a few hours with Codefresh and their amazing on-boarding support we had that and so much more!
Codefresh immediately brought our build time down 50%; gave us the same consistent unit and integration testing from Development workstations to our CI environment; and allowed our Developers to create an environment from any Docker Image built within Codefresh using simple yaml files for every Pull Request they created and send those links along to our QA/Design Teams.
This greatly increased the velocity of the Development lifecycle. The Developers had environments running their code with yesterday's data from our MySQL databases in our upper tier environments in 1-2 minutes.
QA/Design Team members were given links in the Pull Requests to review and approve these changes before they were being pushed back into our default branch.
The free-style steps are very powerful and allow you the opportunity to run scripts against other APIs during builds.
We've recently used Codefresh variables and have begun integrating the builds into our Rally/CA Project Management tool to identify when test cases are ran in Codefresh and marking the test cases back in Rally with the results.
I work in a place where I'm behind a strict firewall and where I cannot install software on my computer. At home, I'm building my startup, SimpleWP. We're using Docker for our core feature.
Codefresh made me able to work with my docker images in a super easy and efficient way. I can modify the Dockerfile on Butbucket, the build is automatically triggered in Codefresh and I have my service up and running. If there is something wrong, I can see the logs instantly, make my modifications and it rebuilds automatically. Not only I see the logs of course. I can use test scripts to check if everything was OK. I'm lazy, many times I don't write tests, but this feature made me able to reliably test the results of my build without logging into the containers, which would be really difficult from my workplace.
With Codefresh, my development workflow is amazingly simple, completely online and I can work really fast. I'm not using all their features so don't take it as a detailed review. But what I use, I love.
I have to mention that I also have good experience with their support. They were quick to answer and they helped when I had a problem. For me it's super important.
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
The entire AWS environments is described and setup using Terraform.