Hey everyone! 👋 I've been diving deep into AWS Bedrock lately for some of our generative AI projects, and I kept hearing about Helicone as a potential layer for logging, cost tracking, and monitoring. The promise of a unified dashboard for all our LLM calls, even across different providers, sounds like a dream for our analytics stack.
So I spun up a trial last week to see if it plays nicely with Bedrock specifically. The short answer is: **yes, it works**, but there's a bit of setup involved compared to just plugging in an OpenAI key. I had to configure the Bedrock integration using their specific provider settings and use the Helicone proxy URL for my requests.
Here’s my quick take on the initial setup and experience:
* **Connection:** Once you add your AWS credentials (access key/secret) in the Helicone dashboard under the Bedrock provider, it establishes the bridge. You then point your Bedrock client to Helicone's endpoint.
* **What works really well:** The logging is fantastic. I can see all my model calls (Claude, Command, etc.), latency, token usage, and costs in one place. The caching feature is a potential game-changer for cost savings.
* **Minor hiccup:** I had to be careful with the request format. Helicone expects a specific structure for Bedrock calls to parse everything correctly. Their docs helped, but it took a tiny bit of trial and error.
Has anyone else run this combo in production? I'm particularly curious about:
* How stable the Bedrock connection has been for you over time.
* Whether you've used the advanced features like custom rate limiting or alerting with Bedrock models.
* Any gotchas with the pricing tracking for Bedrock's complex pricing tiers.
The integration feels powerful, and I'm excited to test it more with A/B testing different models. Would love to hear your stories and compare notes!