Need advice about which tool to choose?Ask the StackShare community!
GeoEngineer vs Terraform: What are the differences?
What is GeoEngineer? Ruby DSL and DSL (geo) to codify then plan and execute changes to cloud resources, by Coinbase. GeoEngineer uses Terraform to plan and execute changes, so the DSL to describe resources is similar to Terraform's. GeoEngineer's DSL also provides programming and object oriented features like inheritance, abstraction, branching and looping.
What is 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.
GeoEngineer and Terraform can be primarily classified as "Infrastructure Build" tools.
GeoEngineer and Terraform are both open source tools. Terraform with 17.7K GitHub stars and 4.83K forks on GitHub appears to be more popular than GeoEngineer with 397 GitHub stars and 49 GitHub forks.
We are an application development firm helping our customers develop web & mobile application. We are currently using GitLab for CI/CT/CD. However, we are looking for something more modern, advance & futuristic that will still be in use even after 10 years of supporting the latest technologies/servers of the time. Someone mentioned about Terraform. Any thoughts about which one would be right one to adopt or just continue with Gitlab?
Stick to gitlab you can still use all the other tooling along with it. Terraform is for infrastructure a d they are different things. I use a combination of gitlab, terraform among other tooling.
If you're self-hosting GitLab, then check you're on the latest version since you mentioned it not being modern (in what ways is it not modern?). GitLab is updated very regularly and IMO is definitely a candidate for the best due to it's all-in-one (low cost of integration) design.
I have experience with many CI/CD tools (going right back to CruiseControl!), but not much experience on some of the newer ones (e.g. Spinnaker / Concourse). Recently I came across Tekton, which a lot of good people are rating, so that might be worth a look if you're doing hybrid/multi-cloud with Kubernetes, but I wouldn't replace GitLab unless you're facing some constraining factor that the GitLab team can't help you with - their feature delivery is pretty quick in my experience.
Hello, we have a bunch of local hosts (Linux and Windows) where Docker containers are running with bamboo agents on them. Currently, each container is installed as a system service. Each host is set up manually. I want to improve the system by adding some sort of orchestration software that should install, update and check for consistency in my docker containers. I don't need any clouds, all hosts are local. I'd prefer simple solutions. What orchestration system should I choose?

If you just want the basic orchestration between a set of defined hosts, go with Docker Swarm. If you want more advanced orchestration + flexibility in terms of resource management and load balancing go with Kubernetes. In both cases, you can make it even more complex while making the whole architecture more understandable and replicable by using Terraform.
Ok, so first - AWS Copilot is CloudFormation under the hood, but the way it works results in you not thinking about CFN anymore. AWS found the right balance with Copilot - it's insanely simple to setup production-ready multi-account environment with many services inside, with CI/CD out of the box etc etc. It's pretty new, but even now it was enough to launch Transcripto, which uses may be a dozen of different AWS services, all bound together by Copilot.
Because Pulumi uses real programming languages, you can actually write abstractions for your infrastructure code, which is incredibly empowering. You still 'describe' your desired state, but by having a programming language at your fingers, you can factor out patterns, and package it up for easier consumption.
We use Terraform to manage AWS cloud environment for the project. It is pretty complex, largely static, security-focused, and constantly evolving.
Terraform provides descriptive (declarative) way of defining the target configuration, where it can work out the dependencies between configuration elements and apply differences without re-provisioning the entire cloud stack.
AdvantagesTerraform is vendor-neutral in a way that it is using a common configuration language (HCL) with plugins (providers) for multiple cloud and service providers.
Terraform keeps track of the previous state of the deployment and applies incremental changes, resulting in faster deployment times.
Terraform allows us to share reusable modules between projects. We have built an impressive library of modules internally, which makes it very easy to assemble a new project from pre-fabricated building blocks.
DisadvantagesSoftware is imperfect, and Terraform is no exception. Occasionally we hit annoying bugs that we have to work around. The interaction with any underlying APIs is encapsulated inside 3rd party Terraform providers, and any bug fixes or new features require a provider release. Some providers have very poor coverage of the underlying APIs.
Terraform is not great for managing highly dynamic parts of cloud environments. That part is better delegated to other tools or scripts.
Terraform state may go out of sync with the target environment or with the source configuration, which often results in painful reconciliation.
I personally am not a huge fan of vendor lock in for multiple reasons:
- I've seen cost saving moves to the cloud end up costing a fortune and trapping companies due to over utilization of cloud specific features.
- I've seen S3 failures nearly take down half the internet.
- I've seen companies get stuck in the cloud because they aren't built cloud agnostic.
I choose to use terraform for my cloud provisioning for these reasons:
- It's cloud agnostic so I can use it no matter where I am.
- It isn't difficult to use and uses a relatively easy to read language.
- It tests infrastructure before running it, and enables me to see and keep changes up to date.
- It runs from the same CLI I do most of my CM work from.
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
Pros of GeoEngineer
Pros of Terraform
- Infrastructure as code119
- Declarative syntax73
- Planning44
- Simple28
- Parallelism24
- Cloud agnostic8
- Well-documented8
- Immutable infrastructure6
- It's like coding your infrastructure in simple English6
- Platform agnostic5
- Portability4
- Extendable4
- Automation4
- Automates infrastructure deployments4
- Scales to hundreds of hosts2
- Lightweight2
Sign up to add or upvote prosMake informed product decisions
Cons of GeoEngineer
Cons of Terraform
- Doesn't have full support to GKE1