Cerebrium

Introduction to Cerebrium

Cerebrium is a cutting-edge serverless AI infrastructure platform designed to simplify the deployment and scaling of machine learning models. By eliminating the complexities of traditional infrastructure setup, Cerebrium enables developers to build, test, and launch AI applications swiftly and efficiently. The platform supports a wide range of machine learning frameworks and offers real-time performance with minimal latency, making it an ideal choice for businesses aiming to integrate AI into their operations seamlessly.

Key Features

• Serverless GPU Infrastructure: Run machine learning models in the cloud scalably and performantly without the need to manage servers.
• Rapid Cold Starts: Achieve cold start times under 5 seconds, ensuring quick responsiveness for real-time applications.
• Extensive GPU Selection: Choose from over 12 GPU types, including NVIDIA H100, A100, and A5000, to match specific workload requirements.
• Automatic Scaling: Scale applications from 1 to over 10,000 concurrent requests automatically, handling traffic spikes without manual intervention.
• Pay-Per-Use Pricing: Only pay for the compute resources used, with charges based on GPU, CPU, and memory usage per second, and persistent storage charged per GB per month.
• Comprehensive Observability: Access real-time logging, monitoring with alerts, and performance profiling tools to track application health and performance.
• Enterprise-Grade Security: The platform is SOC 2 compliant, ensuring high standards of data security and privacy.

How to Use Cerebrium

1. Create an Account: Sign up on the Cerebrium platform to get started.
2. Install the CLI: Use the command pip install cerebrium to install the Cerebrium command-line interface.
3. Initialize a Project: Run cerebrium init my-first-app to create a new project.
4. Write Your Code: Develop your machine learning model and define the inference function in main.py.
5. Deploy the Application: Use cerebrium deploy to deploy your application to the cloud.
6. Access the Endpoint: Once deployed, your application will be accessible via a unique endpoint URL.

Pricing

Cerebrium offers a flexible, usage-based pricing model:

• Free Tier: Ideal for developers getting started, includes 3 user seats, up to 3 deployed apps, and 5 concurrent GPUs.
• Standard Plan: Priced at $100 per month, includes 10 user seats, 10 deployed apps, and 30 concurrent GPUs.
• Enterprise Plan: Custom pricing for teams looking to scale ML apps, includes unlimited deployed apps, unlimited concurrent GPUs, and dedicated support.

Compute resources are charged per second, with GPU, CPU, and memory usage billed accordingly. Persistent storage is charged per GB per month. For detailed pricing information, please refer to the Cerebrium pricing page.

Frequently Asked Questions

• What is Cerebrium? Cerebrium is a serverless AI infrastructure platform that simplifies the deployment and scaling of machine learning models in the cloud.
• How fast are Cerebrium’s cold starts? Cold start times are typically under 5 seconds, ensuring quick responsiveness for real-time applications.
• What GPUs does Cerebrium support? Cerebrium supports over 12 GPU types, including NVIDIA H100, A100, and A5000, to match specific workload requirements.
• Is there a free trial available? Yes, Cerebrium offers a free tier with limited resources for developers to get started.
• How does Cerebrium handle scaling? The platform automatically scales applications from 1 to over 10,000 concurrent requests, handling traffic spikes without manual intervention.
• What are the security standards of Cerebrium? Cerebrium is SOC 2 compliant, ensuring high standards of data security and privacy.