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News FAUN.dev() Team Trending
@devopslinks shared an update, 1 week ago
FAUN.dev()

AWS Unveils Graviton5: A 192-Core Leap in Cloud Performance and Efficiency

Amazon EC2 Amazon Web Services

AWS introduces Graviton5-based EC2 M9g instances, boosting performance by 25% and enhancing scalability while reducing costs.

AWS Unveils Graviton5: A 192-Core Leap in Cloud Performance and Efficiency
News FAUN.dev() Team Trending
@varbear shared an update, 1 week ago
FAUN.dev()

Tor Goes Rust: Introducing Arti, a New Foundation for the Future of Tor

Rust Tor Arti

The development of "Arti," a Rust-based Tor implementation funded by Zcash, aims to enhance security and efficiency by addressing the limitations of the current C-based Tor.

Tor Goes Rust: Introducing Arti, a New Foundation for the Future of Tor
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@varbear added a new tool Arti , 1 week ago.
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@varbear added a new tool Tor , 1 week ago.
News FAUN.dev() Team Trending
@kala shared an update, 1 week ago
FAUN.dev()

Gemini Deep Research Is Now Programmable Through a New API

Gemini 3 Vertex AI

The enhanced Gemini Deep Research agent is now available via API, enabling developers to integrate advanced research capabilities into applications, with the open-sourcing of DeepSearchQA for evaluating complex tasks.

Gemini Deep Research Is Now Programmable Through a New API
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@kala added a new tool Vertex AI , 1 week ago.
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@kala added a new tool Gemini 3 , 1 week ago.
News FAUN.dev() Team Trending
@kala shared an update, 1 week ago
FAUN.dev()

GitHub Copilot Adds GPT-5.2 With Long-Context and UI Generation

GitHub Copilot GPT-5.2

OpenAI unveils GPT-5.2 for GitHub Copilot, enhancing software engineering with improved long-context reasoning and UI generation, integrated with Microsoft Azure and NVIDIA.

GitHub Copilot Adds GPT-5.2 With Long-Context and UI Generation
News FAUN.dev() Team Trending
@kala shared an update, 1 week ago
FAUN.dev()

GPT-5.2 Quietly Beats Human Experts at Knowledge Work

Azure GPT-5.2

OpenAI releases GPT-5.2, enhancing professional tasks with improved speed and cost-effectiveness, now available for paid users in ChatGPT and via API.

OpenAI unveils GPT-5.2, the most advanced frontier model for professional work and long-running agents
 Activity
@kala added a new tool GPT-5.2 , 1 week ago.
Grafana Tempo is a distributed tracing backend built for massive scale and low operational overhead. Unlike traditional tracing systems that depend on complex databases, Tempo uses object storage—such as S3, GCS, or Azure Blob Storage—to store trace data, making it highly cost-effective and resilient. Tempo is part of the Grafana observability stack and integrates natively with Grafana, Prometheus, and Loki, enabling unified visualization and correlation across metrics, logs, and traces.

Technically, Tempo supports ingestion from major tracing protocols including Jaeger, Zipkin, OpenCensus, and OpenTelemetry, ensuring easy interoperability. It features TraceQL, a domain-specific query language for traces inspired by PromQL and LogQL, allowing developers to perform targeted searches and complex trace-based analytics. The newer TraceQL Metrics capability even lets users derive metrics directly from trace data, bridging the gap between tracing and performance analysis.

Tempo’s Traces Drilldown UI further enhances usability by providing intuitive, queryless analysis of latency, errors, and performance bottlenecks. Combined with the tempo-cli and tempo-vulture tools, it delivers a full suite for trace collection, verification, and debugging.

Built in Go and following OpenTelemetry standards, Grafana Tempo is ideal for organizations seeking scalable, vendor-neutral distributed tracing to power observability at cloud scale.