Galileo leverages powerful containerization technology so that your project can run on any OS, on any friendly machine. It runs your project as a containerized process on a remote machine and sends you back the results.
Galileo is end-to-end encrypted. We cannot see your data. The machine that will run your computation (the “landing zone”), has Read-Only access to the information you send. Thanks to containerization technology, your project remains in a secure silo. No one can run on your machine without your explicit approval, and no one (including us) can read your data. If the landing zone is a machine that you control, Galileo is part of your closed network that is inaccessible to others. If you need external compute resources, we can meet your security needs, up to and including HIIPA compliant machines. Galileo can run on all of the leading Cloud providers (AWS, GCP, Azure, etc.). More info: Galileo Security 101.
A container is fundamentally a standardized unit of software. It makes your work portable by packaging code and dependencies together. Galileo specifically uses Docker containers so that your project can run agnostically in any computing environment. Containerization assures reliability and uniformity by isolating a compute job from the underlying OS environment, which means that your work is always run in a secure silo. Containers are also lightweight and allow for nearly native run speeds. Containerization is now the industry standard deployment format for resolving application portability challenges and improving developer productivity.
What’s actually inside a container? How do you know that a container is secure and running the latest OS?
- Containers are a lightweight tool that allow you to run your job without installing the dependencies, the software, or even the operating system necessary to run the job. Containers can run in nearly any compute environment, which means that Galileo can run your job on a wide variety of machines with no configuration.
- Your project folder and the latest, most secure OS to run your job are inside your container. Finally, there is a very simple “Dockerfile,” which tells Docker which image to use for your job.
- Request a demo
- Create an account. (We will never share any of your information with anyone!)
- Add friends. During your trial, we suggest you use one of our “autofriend” machines.
- Set up your project (or use one of our sample projects!).
- Run remotely, get results.
During Beta (now!), you can use Galileo for free! Request a download. Do you need a custom solution? We’re happy to help! Contact us.
After the marketplace launch, you will be able to search and choose between various compute offers and prices.
What do I need to install on my machine to make it a ``landing zone,” where people can send and run jobs?
To run jobs, you only need to have Galileo and Docker Desktop running on your workstations. You do not need to have other software or dependencies installed to run there.
Yes, absolutely. Just let us know what you need, and we can very likely “containerize” it so it can run quickly and easily on Galileo.
The jobs will run concurrently, which might lead to more optimal usage of the machines you use. If you have many users sharing machines, you will be able to see which machines are currently running jobs, so you can choose a machine that is available.
The results are automatically sent back to your machine upon job completion, and you can designate a destination folder. You can also send them to a shared folder that will sync with your local machine.
We have an API and CLI that are in closed Beta. Click below to request information and access.
We will soon be adding marketplace capabilities to significantly increase your hardware options! You will soon be able to use Galileo to buy and sell compute time in a decentralized, peer-to-peer manner, on a sharing economy model.
- Anyone engaged in scientific and high-performance computing, in industry and/or academia. Some recent examples: hydrology engineers, AI/ML engineers, energy providers, and bioinformatics researchers.
- Works best for:
- Easy access to extra compute without the need to setup or configure
- Connecting your own machines to deploy easily between them
- Farming out projects with long run times to other machines
- Batch processing for jobs that can run in parallel
- Teams running analyses on one large dataset
- Easy access to different, bigger, and better machines, without wasting time and energy on cloud configuration.
- Run faster.
- Irregular workflow? Scale up quickly, right when you need to.
- Run anything. If it can be packaged in a container, you can run it on Galileo.