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Lightweight compute platform for Python people, enabling scalable data science and engineering workflows in the cloud without Kubernetes or Docker.

Coiled is a cloud computing platform optimized for Python-based data science and engineering. It simplifies scaling workloads by abstracting away the complexities of infrastructure management like Kubernetes and Docker. Users can define and spin up clusters using Python code, automatically distributing their code and environment across cloud machines. Coiled integrates seamlessly with existing Python workflows and tools like Dask, Xarray, and Prefect. Use cases include processing large tabular datasets, training machine learning models, performing geospatial analysis, and running production ETL pipelines. It supports various cloud providers (AWS, GCP, Azure) and offers features like custom networking, private PyPI, spot instances, and integration with custom AMIs. Coiled's architecture emphasizes ephemeral infrastructure, ensuring that users only pay for active compute time.
Coiled is a cloud computing platform optimized for Python-based data science and engineering.
Explore all tools that specialize in batch processing. This domain focus ensures Coiled delivers optimized results for this specific requirement.
Explore all tools that specialize in orchestrate data workflows. This domain focus ensures Coiled delivers optimized results for this specific requirement.
Explore all tools that specialize in manipulate dataframes. This domain focus ensures Coiled delivers optimized results for this specific requirement.
Enables users to configure private networks for their Coiled clusters, enhancing security and compliance by isolating compute resources.
Allows users to host private Python package repositories, ensuring that sensitive code and dependencies are not exposed to the public internet.
Leverages spot instances from cloud providers to reduce compute costs. Coiled automatically manages instance interruptions and rescheduling.
Supports the use of custom Amazon Machine Images (AMIs), enabling users to preconfigure their compute environments with specific software and dependencies.
Integrates with Single Sign-On (SSO) providers, simplifying user authentication and access management.
Install Coiled: `pip install coiled`
Authenticate with your cloud provider (AWS, GCP, or Azure)
Create a Coiled account and link it to your cloud provider
Define your cluster configuration using Python, specifying the number of workers, region, and VM types.
Start your cluster: `cluster = coiled.Cluster(n_workers=10, region='us-west-2', vm_type='m5.xlarge')`
Connect to the Dask cluster: `client = dask.distributed.Client(cluster)`
Submit your Python code to the cluster for distributed execution
Monitor your job's progress using the Coiled Web UI or API
Scale your cluster up or down as needed to optimize performance and cost
Tear down your cluster when finished to avoid idle costs
All Set
Ready to go
Verified feedback from other users.
"Coiled is highly praised for its ease of use, scalability, and excellent support, making it a preferred choice for data scientists and engineers working with large datasets."
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