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Koding vs Terraform: What are the differences?
What is Koding? A new way for developers to work. Koding is a feature rich cloud-based development environment complete with free VMs, an attractive IDE & sudo level terminal access!.
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.
Koding belongs to "Cloud IDE" category of the tech stack, while Terraform can be primarily classified under "Infrastructure Build Tools".
Some of the features offered by Koding are:
- Free virtual machine (VM) with Ubuntu, root access, apt-get, and many commonly used tools
- Built-in Terminal with 256-color support
- All languages, databases, and command-line tools are supported
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.
"Free" is the top reason why over 35 developers like Koding, while over 80 developers mention "Infrastructure as code" as the leading cause for choosing Terraform.
Terraform is an open source tool with 17.4K GitHub stars and 4.77K GitHub forks. Here's a link to Terraform's open source repository on GitHub.
I am going to learn machine learning and self host an online IDE, the tool that i may use is Python, Anaconda, various python library and etc. which tools should i go for? this may include Java development, web development. Now i have 1 more candidate which are visual studio code online (code server). i will host on google cloud
The main contenders here are VS code and Eclipse, because Koding is meant to be used by large companies and by devs who know what they are doing. Both VS code and Eclipse have pros and cons, but for someone who wants to learn, VS Code is a much better choice as it has a very simple UI and plugins are easier to find and download.
Eclipse isn't meant for learning purposes and was designed with the intent to be used by professionals. Also it is an amazing IDE for java, but isn't so good in other languages, while VS code is much more efficient in a vast number of languages.
The only likely issue you might be facing with vs code is that, at times, it can be a resource hog, and in extreme cases it is possible to crash. But it is very rare and I recommend you have at least 8GB ram and at least a dual 1.6 GHz CPU.
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 Koding
- Free36
- Built in terminal for vm31
- Free vm with ssh access30
- Apps15
- Real time code collaboration with infinite # of people14
- Built in social network with developers from all over13
- Good ui12
- Active community12
- 1gb ram on the free plan12
- Strong alternative of localhosts10
- Free public ip6
- Best online ide3
- Easy and reliable2
- Koding University1
- Koding Package Manager1
- Automated development environment setup system1
- No free VM anymore1
Pros of Terraform
- Infrastructure as code121
- Declarative syntax73
- Planning45
- Simple28
- Parallelism24
- Well-documented8
- Cloud agnostic8
- It's like coding your infrastructure in simple English6
- Immutable infrastructure6
- Platform agnostic5
- Extendable4
- Automation4
- Automates infrastructure deployments4
- Portability4
- Lightweight2
- Scales to hundreds of hosts2
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Cons of Koding
Cons of Terraform
- Doesn't have full support to GKE1