Overview
Gitpod is a developer platform that provides on-demand, pre-configured cloud development environments (CDEs) that automatically integrate into any tool, library, or dependency required for creating software.
Gitpod CDEs are best for organizations that are looking to drastically cut onboarding time for developers, increase the productivity of their teams or secure their development supply chains.
Gitpod Enterprise is hosted within your VPC and managed by Gitpod, enabling maximum security with minimal overhead.
Highlights
- Configured to your specs: Pre-configured environments, out-of-the-box, eliminate the need to setup any dev environments: local, VDI or homegrown. CDEs can also be customized to the needs of your organization and are powerful enough to handle any size application without draining your resources.
- Maximise developer efficiency: Eliminate environment troubleshooting, streamline collaboration and slash onboarding time from weeks to hours, through shareable configurations and environments.
- Security & control: Isolated, single-tenant installations ensure source code, dependencies and dev environments are private and protected. All within the cloud region of your choice. Gitpod Enterprise also runs within your VPC enabling secure access to private resources
Details
Features and programs
Financing for AWS Marketplace purchases
Pricing
Dimension | Description | Cost/12 months |
---|---|---|
Annual Commit | Gitpod Enterprise | $60,000.00 |
Vendor refund policy
All fees are non-cancellable and non-refundable except as required by law
Custom pricing options
Legal
Vendor terms and conditions
Content disclaimer
Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Support
Vendor support
https://www.gitpod.io/support support@gitpod.io Gitpod provides custom pricing for customers via Private Offer. Please contact sales@gitpod.io for a better understanding of our pricing model and delivery options. For support inquiries please visit
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Customer reviews
Great platform for faster and reliable codespaces.
Elevate Your Development Workflow with Gitpod: A Game-Changer for Efficiency and Collaboration
The initial dedicated SAAS setup, was up and running in no time. And the support we receive troughout the process has been tremendous.
- No Data access for BYOD
- Inconsistent development environments
Cloud IDEs: fast onboarding and isolated reproducible environments
* One unexpected benefit was that the environments are not only reproducible, they're also isolated: you can work on 2 branches at the same time by spinning up 2 gitpod workspaces.
* Prebuilds ease the pain of waiting for workspace boot.
* We could shut down our previous notebook solution thanks to gitpod using a vscode notebook plugin.
Easy to set up, happy engineers and excellent support
As an internal developer platform team, it allows us to onboard new engineers much faster than before. Where in the past people had to go through 20 documentation pages with all the tools that needed to be installed, this can now be provided by the platform team as a script in the .gitpod.yml configuration file.
- Secure connectivty to data systems (data doens't have to be on personal laptops anymore)
- Onboarding people instantly without losing time
- Helping to bridge the disconnect between the "experimentation" and "industrialization" phases of the data product lifecycle. People can now run Jupyter notebooks right next to their code in an IDE. This promotes better writing of functions and prevents copy pasting code after the machine learning model experiments are done. In the past, when people finished developed a machine learning model in a notebook, they had to go to the next step, which is industrializing the code and making sure the predictions are run everyday or in real-time. People often had to copy paste code from a notebook to an IDE.
Avoid, use one of the larger players
- Doubled prices (more than doubled for most use cases, in fact)
- Support has gone down the drain. We sent in our most recent tech question 9 days ago, still have not gotten an answer (and I can provide screenshots if needed)
- Dropped their open source. We use their SaaS product, but this leaves a horrible taste in our mouths. For years and years, they got lots of help/support/feedback from the community, precisely because they maintained an open source product that could be used by nonprofits, academics, etc. who might not have the funds to pay for SaaS. In one fell swoop, they dropped all of those folks. Now they're purely profiting off the backs of all that help the got from the community
We wish we had gone with a different company, and as soon as we can get the time to migrate, we will.