惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

B
Blog
Microsoft Security Blog
Microsoft Security Blog
Jina AI
Jina AI
博客园 - 叶小钗
J
Java Code Geeks
博客园 - 聂微东
博客园 - 司徒正美
大猫的无限游戏
大猫的无限游戏
阮一峰的网络日志
阮一峰的网络日志
V
V2EX
美团技术团队
WordPress大学
WordPress大学
M
MIT News - Artificial intelligence
雷峰网
雷峰网
酷 壳 – CoolShell
酷 壳 – CoolShell
GbyAI
GbyAI
罗磊的独立博客
T
The Blog of Author Tim Ferriss
aimingoo的专栏
aimingoo的专栏
T
Tailwind CSS Blog
The Cloudflare Blog
Stack Overflow Blog
Stack Overflow Blog
N
Netflix TechBlog - Medium
小众软件
小众软件

Hugging Face - Blog

Waypoint-1.5: Higher-Fidelity Interactive Worlds for Everyday GPUs ALTK‑Evolve: On‑the‑Job Learning for AI Agents Safetensors is Joining the PyTorch Foundation Holo3: Breaking the Computer Use Frontier Any Custom Frontend with Gradio's Backend A New Framework for Evaluating Voice Agents (EVA) Bringing Robotics AI to Embedded Platforms: Dataset Recording, VLA Fine‑Tuning, and On‑Device Optimizations One-Shot Any Web App with Gradio's gr.HTML CUGA on Hugging Face: Democratizing Configurable AI Agents New in llama.cpp: Model Management Building Deep Research: How we Achieved State of the Art OVHcloud on Hugging Face Inference Providers 🔥 20x Faster TRL Fine-tuning with RapidFire AI Building for an Open Future - our new partnership with Google Cloud Aligning to What? Rethinking Agent Generalization in MiniMax M2 Building a Healthcare Robot from Simulation to Deployment with NVIDIA Isaac Sentence Transformers is joining Hugging Face! Unlock the power of images with AI Sheets Supercharge your OCR Pipelines with Open Models Google Cloud C4 Brings a 70% TCO improvement on GPT OSS with Intel and Hugging Face Get your VLM running in 3 simple steps on Intel CPUs Nemotron-Personas-India: Synthesized Data for Sovereign AI Introducing RTEB: A New Standard for Retrieval Evaluation Accelerating Qwen3-8B Agent on Intel® Core™ Ultra with Depth-Pruned Draft Models VibeGame: Exploring Vibe Coding Games Nemotron-Personas-Japan: ソブリン AI のための合成データセット Swift Transformers Reaches 1.0 – and Looks to the Future Smol2Operator: Post-Training GUI Agents for Computer Use SyGra: The One-Stop Framework for Building Data for LLMs and SLMs Gaia2 and ARE: Empowering the community to study agents
The New and Fresh analytics in Inference Endpoints
Erik Kaunismäki, Thibault Goehringer, Remy, Corentin Regal, Mich · 2025-03-21 · via Hugging Face - Blog

Back to Articles

Analytics is important

Analytics and metrics are the cornerstone of understanding what's happening with your deployment. Are your Inference Endpoints overloaded? How many requests are they handling? Having well-visualized, relevant metrics displayed in real-time is crucial for monitoring and debugging.

We realized that our analytics dashboard needed a refresh. Since we debug a lot of endpoints ourselves, we’ve felt the same pain as our users. That’s why we sat down to plan and make several improvements to provide a better experience for you.

What’s New?

⏰ Real-Time Metrics: Data now updates in real-time, ensuring you get an accurate and up-to-the-second view of your endpoint’s performance. Whether you’re monitoring request latency, response times, or error rates, you can now see the events as they happen. We’ve also reworked the backend of our analytics dashboard to ensure that data loads swiftly, especially for high-traffic endpoints. No more waiting around for metrics to populate. Just open the dashboard and get instant insights.

🔬 Customizable Time Ranges & Auto-Refresh: We know that different users need different views, so we’ve made it easier to zoom in on a specific time range or track long-term trends. You can also enable auto-refresh, ensuring that your dashboard stays up to date without needing to manually reload.

🔄 Replica Lifecycle View: Understanding what’s happening with your replicas is crucial, so we’ve introduced a detailed view of each replica’s lifecycle. You can now track replicas from initialization to termination, observing every state transition in between. This helps understand what's going on with your endpoint even if you have several moving parts.


Even though we’ve rolled out these updates, we’re actively iterating on them. Things will continue to improve, and we welcome all feedback.

Let us know what works, what doesn’t, and what you’d like to see next! 🙌

Head to Inference Endpoints to check out the changes!