“The post Database maker ClickHouse raises $400M, acquires AI observability startup Langfuse appeared on SiliconANGLE.”

“Function Summary: Time taken for a turn (a single interaction between the user and Claude)...”

“Integrating AI into code review workflows allows engineering leaders to detect systemic risks that often evade human detection at scale.”

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“LLMアプリ開発は「動くものを作る」だけなら驚くほど簡単だ。OpenAIのAPIキーを取得し、数行のPythonコードを書けば、誰でもチャットボットを作ることができる。”

“The paper derives sufficient conditions on a compact self adjoint perturbation to guarantee that the perturbed system stays exactly observable.”

“The paper proposes an auxiliary task learning (ATL) method for reconstructing missing PMU data.”

“最近は、Windows の GPU でローカル LLM なんていうこともやることが多くなってきていると思うので、GPU が燃え尽きないように監視も大切ということで、監視させてみたいと思います。”

“The article doesn't contain a direct quote.”

“What types of failures do you encounter most often in your training workflows? What information do you currently collect to debug these? What's missing? What do you wish you could see when things break?”

“「New Relic Advent Calendar 2025 」シリーズ4・25日目の記事になります。”

“The study utilizes observable mempools to determine transaction timing and fee.”

“The paper demonstrates the existence of almost dissipationless oscillating modes at low temperatures, realizing prethermal time-crystal behavior.”

“"TOKIUM AI 出張手配は、自然言語で出張内容を伝えるだけで、新幹線・ホテル・飛行機などの提案をAIエージェントが代行してくれるプロダクトです。"”

“Langfuse を Docker Compose でローカル起動し、LangChain/OpenAI SDK を使った Python コードでトレースを OTLP (OpenTelemetry Protocol) 送信するまでをまとめた記事です。”

“The paper likely discusses methods or metrics for assessing how easily an AI system can be observed and understood.”

“Focus on provable observability and lightweight audit agents.”

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“The article quotes the creator's experience with debugging agents in production and the desire for granular control and easy observability.”

“The article likely discusses the benefits of using OpenTelemetry for monitoring LLM performance and debugging issues.”

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“Nexus is an open-source AI router.”

“We explore their use of cloud-based infrastructure—in this case on AWS—to provide a foundation upon which they then layer open-source and proprietary services and tools.”

“Vocera (YC F24) - Testing and Observability for Voice AI”

“Sunil describes their system's agent-based design, focusing on clear roles and boundaries to ensure reliability.”

“The key difference is that we tie text analytics directly to execution traces. Rich text data makes LLM traces unique, so we let you track “semantic metrics” (like what your AI agent is actually saying) and connect those metrics to where they happen in the trace.”

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“OpenLIT is an open-source tool designed to make monitoring your Large Language Model (LLM) applications straightforward. It’s built on OpenTelemetry, aiming to reduce the complexities that come with observing the behavior and usage of your LLM stack.”

“The article quotes the founder explaining the product and the problem it solves: the limitations of low-code tools and the complexity of building integrations.”

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“The article highlights the benefits of OpenLLMetry, including the ability to trace the entire system execution and connect to any monitoring platform.”

“Gentrace makes pre-production testing of generative pipelines continuous and nearly instantaneous.”

“Helicone's one-line integration logs the prompts, completions, latencies, and costs of your OpenAI requests.”

“We’re building Vellum, a developer platform for building on LLMs like OpenAI’s GPT-3 and Anthropic’s Claude. We provide tools for efficient prompt engineering, semantic search, performance monitoring, and fine-tuning, helping you bring LLM-powered features from prototype to production.”

“UpTrain is an open-source ML observability and refinement tool.”