Google Cloud Deployment Manager vs. IBM Terraform

Anything that needs to be repeated en masse. Terraform is great at taking a template and have it be repeated across your estate. You can dynamically change the assets they're generating depending on certain variables. Which means though templated assets will all be similar, they're allowed to have unique properties about them. For example flattening JSON into tabular data and ensuring the flattening code is unique to the file's schema.

Incentivized

• Terraform is cloud agnostic. Just select the suitable provider for the cloud and it will do the job.
• Templating is possible to make the Terraform templates reusable.
• Variables can be created to make the templates generic so that it can be reused for different environments or resources.

Incentivized

• The language itself is a bit unusual and this makes it hard for new users to get onboarded into the codebase. While it's improving with later releases, basic concepts like "map an array of options into a set of configurations" or "apply this logic if a variable is specified" are possible but unnecessarily cumbersome.
• The 'Terraform Plan' operation could be substantially more sophisticated. There are many situations where a Terraform file could never work but successfully passes the 'plan' phase only to fail during the 'apply' phase.
• Environment migrations could be smoother. Renaming/refactoring files is a challenge because of the need to use 'Terraform mv' commands, etc.

Incentivized

Still the best provisioning tool out there and good support from the community as well in terms of shared knowledge

Incentivized

The syntax itself is pretty straightforward. The documentation is well-maintained & easy to follow. Most cloud providers, even smaller ones, maintain official provider libraries, making discovery & learning a breeze. Some, like GCP, even provide high-level libraries on top of their own more primitive provider, making building complex infra much more manageable. The language itself is cloud-agnostic, so you can literally manage resources from multiple providers in a single Terraform repo.

Terraform's performance is quite amazing when it comes to deployment of resources in AWS. Of course, the deployment times depend on various parameters like the number of resources to deploy and different regions to deploy. Terraform cannot control that. The only minor drawback probably shows up when a terraform job is terminated mid way. Then in many cases, time-consuming manual cleanup is required.

Incentivized

I have yet to have an opportunity to reach out directly to HashiCorp for support on Terraform. However, I have spent a great deal of time considering their documentation as I use the tool. This opinion is based solely on that. I find the Terraform documentation to have great breadth but lacking in depth in many areas. I appreciate that all of the tool's resources have an entry in the docs but often the examples are lacking. Often, the examples provided are very basic and prompt additional exploration. Also, the links in the documentation often link back to the same page where one might expect to be linked to a different source with additional information.

Incentivized

Implementation is straight forward. Never had issues as the team is already very familiar with Terraform installation from previous projects and roles

Incentivized

Terraform is the solid leader in the space. It allows you to do more then just provisioning within a pre-existing servers. It is more extensible and has more providers available than it competitors. It is also open source and more adopted by the community then some of the other solutions that are available in the market place.

Incentivized

• we are able to deploy our infrastructure in a couple of ours in an automated and repeatable way, before this could take weeks if the work was done manually and was a lot of error prone.
• having the state file, you can see a diff of what things have changed manually out side of Terraform which is a huge plus
• if state file gets corrupted, it is very hard to debug or restore it without an impact or spending hours ..
• writing big scale code can be very challenging and hard to be efficient so it's usable by the whole team