By CometAPI
I’m building an AI-powered app hosted on a DigitalOcean Droplet. The app needs to call multiple providers — OpenAI for LLMs, Midjourney for image generation, and some video generation models like Kling and Veo 3.
Managing separate API keys, rate limits, and billing across all of them is getting messy. I’ve been looking at API aggregator platforms that unify everything under one endpoint.
Has anyone used an aggregator like this in production on DigitalOcean? Curious about:
- Latency impact vs calling providers directly
- How you handle failover if the aggregator goes down
- Whether the cost savings actually hold up at scale
Any experience or alternative approaches welcome.
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This comment has been deleted
Hi there,
Before reaching for a third party aggregator, it is worth knowing that DigitalOcean has its own AI platform with access to a growing list of models directly from the control panel, including models from Anthropic, Meta, and others. If some of your needs are covered there, it simplifies the stack considerably and keeps everything in one place. Worth checking what is available: https://www.digitalocean.com/products/ai-ml
For providers not covered, managing multiple API keys is mostly an env var and config management problem. A simple abstraction layer in your FastAPI app that routes requests to the right provider based on model type works well and keeps you in control. Libraries like LiteLLM are worth looking at since they provide a unified OpenAI-compatible interface across most major providers without introducing a third party dependency you cannot control.
On the aggregator question generally: latency impact is real since you are adding a hop, and if the aggregator goes down you lose access to everything at once rather than having isolated failures per provider. For production use, that single point of failure is the main concern.
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