Graphsignal

Inference Profiler

[Graphsignal @GraphsignalAI]

autodebug: an autonomous loop that deploys an inference service, benchmarks it, reads profiling telemetry, and redeploys with a better config. Then repeats.

Uses @GraphsignalAI for inference profiling, @dstackai for GPU provisioning, Claude Code as the agent.

https://t.co/HHdHa6TcaM https://t.co/IsIBt9hbel

[dstack @dstackai]

@GraphsignalAI More on how Graphsignal uses dstack across on-prem and GPU cloud for development and inference: https://t.co/ssFzsc38o2

[dstack @dstackai]

New: a case study on how @GraphsignalAI uses dstack for development and inference benchmarking.

Graphsignal builds tooling to profile model inference, and uses dstack across a fleet of @nvidia DGX Spark devices and @verdacloud to keep the workflow consistent across on-prem and cloud:
https://t.co/fDZSrXV0wW

[Graphsignal @GraphsignalAI]

@dstackai And we also rely on @dstackai for development and testing of our SDK: https://t.co/aSw2gnjEln. Can’t wait to share more in another post!

[dstack @dstackai]

autodebug by @GraphsignalAI is a closed-loop system for inference optimization.

It uses @dstackai to provision GPUs and redeploy services on each pass through the loop:

benchmark → read profiling telemetry → tweak config → redeploy → repeat.

What's interesting here is the combination of agentic optimization and heterogeneous hardware: the system is not tuning a fixed deployment, it is continuously searching across infrastructure and configuration.

There's no manual step between iterations.

@dmitrimelikyan's writeup: https://t.co/uvSBN2maMJ

[Graphsignal @GraphsignalAI]

@dstackai and here is the repo https://t.co/zcxItMwYFg, inspired by @karpathy authoresearch

[Graphsignal @GraphsignalAI]

autodebug: an autonomous loop that deploys an inference service, benchmarks it, reads profiling telemetry, and redeploys with a better config. Then repeats.

Uses @GraphsignalAI for inference profiling, @dstackai for GPU provisioning, Claude Code as the agent.

https://t.co/HHdHa6TcaM https://t.co/IsIBt9hbel

[Andrey Cheptsov @andrey_cheptsov]

Config tuning is just the start. The same loop can optimize inference code and even custom CUDA kernels. It all depends on what tools the agent can use.

[dstack @dstackai]

Agent orchestration is evolving fast!

Agents + orchestration + telemetry → closed-loop systems.

Our friends at GraphSignal show how this unlocks continuous inference optimization in production — across heterogeneous hardware.

This is where things get interesting.

[dstack @dstackai]

Now @GraphsignalAI integrates with dstack — add @sgl_project profiling, tracing, and GPU metrics to your inference services.

pip install 'graphsignal[cu12]' + wrap with graphsignal-run. That's it.

https://t.co/TEFptiG1ak

[Graphsignal @GraphsignalAI]

New post: AI Debugging and Optimization For Production Inference https://t.co/VbZKQnTy2R

Use Claude Code to debug and optimize AI systems with rich production context from Graphsignal

[Graphsignal @GraphsignalAI]

New post: Traditional Observability Is Blind to Inference
https://t.co/Y2zS4twlBs

[Graphsignal @GraphsignalAI]

New post: vLLM production observability - from model to hardware.

https://t.co/Jjun3ahbia

[Graphsignal @GraphsignalAI]

@dstackai @nvidia Thank you for the mention! We’re big fans of @dstackai

[Graphsignal @GraphsignalAI]

Fresh dev setup on #dgx_spark running as a @dstackai fleet⚡️

[Graphsignal @GraphsignalAI]

LLM API Latency Optimization Explained https://t.co/Fi7o5DB3R5

[Nathan Benaich @nathanbenaich]

berlin done, munich next!

good crew coming too:

[Graphsignal @GraphsignalAI]

YES, you need to see the prompts! Great article by @HamelHusain https://t.co/v2pXVzfc40

[Graphsignal @GraphsignalAI]

Learn how to measure and analyze LLM streaming performance using time-to-first-token metrics and traces

➡️ https://t.co/Q8drhdw6GZ

[Graphsignal @GraphsignalAI]

#AI observability is evolving. Today's tools not only monitor AI performance but also unravel complex model behaviors, enhancing transparency and reliability.

[Victor M @victormustar]

Free ChatGPT users - what's stopping you from switching to HuggingChat?