Cerebrium: Serverless AI Infrastructure

Key Features

• Sub-second cold starts

  Uses memory and GPU snapshotting to launch containers quickly, which helps maintain responsiveness during traffic spikes.

• Instant autoscaling

  Scales CPU and GPU workloads based on demand to help avoid paying for idle capacity.

• Multi-cloud GPU access

  Provides access to NVIDIA and AMD GPUs across different global regions without requiring long-term capacity reservations.

• Dockerfile deployment

  Supports deploying applications by pointing to an entry point or Dockerfile, allowing code to run without custom SDKs.

• Infrastructure observability

  Includes logs, metrics, and scaling events with OpenTelemetry integration for monitoring system performance.

• Compliance and Isolation

  Supports SOC 2, HIPAA, GDPR, and ISO standards, using gVisor for container isolation.

Use Cases

• Deploying Large Language Models

  Supporting production deployment of LLMs using frameworks like vLLM, SGLang, or TensorRT.

• Voice Agents

  Deploying low-latency voice bots, such as those built with Pipecat or LiveKit.

• Generative AI for Image and Video

  Running image generation models like SDXL or video generative AI workloads.

• Embedding Servers

  Serving text-embeddings and reranking models via REST APIs.

• Batch AI Processing

  Running large-scale batch jobs, such as transcribing audio podcasts.

Integrations

• Grafana Cloud
• Datadog
• Prometheus
• New Relic
• Honeycomb
• Lightstep

FAQ

How does Cerebrium pricing work?

Cerebrium uses a usage-based model where you pay for actual compute time measured in seconds. There are three tiers: a free Hobby plan, a Standard plan at $100/month plus compute, and a custom Enterprise plan.

Does Cerebrium support data privacy regulations?

Yes, the platform supports SOC 2, HIPAA, GDPR, and ISO compliance, and it offers data residency options to keep data in specific regions.

What is a 'cold start' in Cerebrium?

A cold start is the time it takes to launch a container. Cerebrium uses memory and GPU snapshotting to support sub-second cold starts for faster application restores.

Do I need to rewrite my code to use Cerebrium?

No, the platform supports deployment by specifying an entry point or using a Dockerfile, which may allow you to run your application without custom SDKs.