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Modal

Modal

Code execution in the cloud made easy.

cloud computingcontainerizationserverless compute
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Introduction

Modal helps people run code in the cloud. We think it's the easiest way for developers to get access to containerized, serverless compute without the hassle of managing their own infrastructure.

Key Features

Express container images and hardware specifications entirely in code, no need for Dockerfiles or YAML.

Provision network volumes, key-value stores, and queues with ease using powerful cloud primitives that feel like regular Python.

Turn functions into cron jobs with a single line of code.

Serve any function as an HTTPS endpoint and ship to custom domains.

Monitor executions, logs, and metrics in real-time, and debug interactively with modal shell.

Secure workloads with the gVisor runtime and industry-standard SOC 2 compliance.

Frequently Asked Questions

What is Modal?

Modal helps people run code in the cloud. We think it's the easiest way for developers to get access to containerized, serverless compute without the hassle of managing their own infrastructure.

How to use Modal?

To use Modal, developers can run generative AI models, large-scale batch jobs, job queues, and more. They can bring their own code and Modal takes care of running the infrastructure. The installation process involves running 'pip install modal' followed by 'python3 -m modal setup'.

What is Modal?

Modal is a platform that helps developers run code in the cloud without managing their own infrastructure.

How does Modal work?

Modal allows developers to bring their own code, which is then executed in containerized, serverless compute environments. It provides features for storage, job scheduling, web endpoints, observability, and security.

What are the pricing options for Modal?

Modal offers flexible pricing based on compute usage. The cost varies depending on the type of compute resources used, including CPU cores, GPU models, and memory.

What are some use cases for Modal?

Modal is used for running data-intensive applications, large-scale workloads, generative AI models, batch jobs, job queues, and more. It can also be used for scheduling cron jobs and serving functions as HTTPS endpoints.

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Use Cases

  • Running data-intensive applications
  • Running large-scale workloads
  • Running generative AI models
  • Running batch jobs
  • Running job queues
  • Scheduling cron jobs
  • Serving functions as HTTPS endpoints

How to Use

To use Modal, developers can run generative AI models, large-scale batch jobs, job queues, and more. They can bring their own code and Modal takes care of running the infrastructure. The installation process involves running 'pip install modal' followed by 'python3 -m modal setup'.