Should I host my model on AWS or use a managed inference platform?

It depends on how much control vs. how much convenience you want.

Use AWS directly if you want:

• Maximum control over networking, autoscaling, instance choice, IAM, logging, and security
• Lower unit cost at scale if you’re willing to operate it yourself
• Custom serving stacks (vLLM, TGI, Triton, Ray, custom CUDA builds, etc.)
• Enterprise/VPC requirements or stricter compliance needs
• Predictable, high, or spiky traffic where you can optimize infra carefully

Tradeoff: you’ll spend more time on ops:

• deployment pipelines
• capacity planning
• scaling policies
• rolling updates
• observability
• GPU utilization tuning
• incident handling

Use a managed inference platform if you want:

• Fastest path to production
• Less DevOps/MLOps burden
• Easy autoscaling and deployments
• Built-in observability, versioning, rollbacks, A/B testing
• Simple API-based usage
• Good defaults without having to manage servers

Tradeoff: usually:

• higher cost per request
• less control
• possible vendor lock-in
• limited support for custom runtimes or niche GPU configs

A practical rule of thumb

Choose managed inference if:

• you’re an early-stage team
• you need to launch quickly
• your workload is moderate
• you don’t have dedicated infra engineers
• your model serving needs are standard

Choose AWS directly if:

• inference is a major cost center
• you have production scale
• latency and throughput matter a lot
• you need custom serving or networking
• you have strong infra/ML platform expertise

Cost perspective

• Managed platforms often win on engineering time
• AWS often wins on raw infrastructure cost once you’re at scale and can keep GPUs busy

A good mental model:

• If your team cost matters more than infra cost: managed
• If infra cost and performance matter more than team simplicity: AWS

Common hybrid approach

Many teams do this:

1. Start on a managed platform
2. Validate the model, latency, and traffic patterns
3. Move to AWS when usage grows or costs become important

That’s often the best balance.

My recommendation

• If you’re unsure or need to ship quickly: use a managed inference platform
• If you already know you need tight control or low-cost scale: host on AWS

If you want, I can help you choose based on your:

• model type
• expected traffic
• latency target
• budget
• team size
• compliance needs