Updates and recent posts about LangChain..

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@laura_garcia shared a post, 1 month, 1 week ago

Software Developer, RELIANOID

🛡️ RELIANOID at Black Hat Europe 2025

📅 December 8–11, 2025 • 📍 London, UK RELIANOID is heading to Black Hat Europe 2025, the premier global event for cutting-edge cybersecurity research and innovation. We’ll be in London showcasing how our high-performance ADCs, intelligent proxy architecture, and automated security capabilities help e..

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@anjali shared a link, 1 month, 1 week ago

Customer Marketing Manager, Last9

OTel Updates: Unroll Processor Now in Collector Contrib

The OTel unroll processor splits bundled log records into individual events. Now in Collector Contrib v0.137.0 for VPC and CloudWatch logs.

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@laura_garcia shared a post, 1 month, 1 week ago

Software Developer, RELIANOID

Tesco’s latest outage is a reminder: uptime IS the customer experience.

Shoppers across the UK faced checkout failures, broken order updates, and Clubcard access issues as Tesco’s digital platforms suffered “intermittent” instability. In modern retail, even brief disruptions damage trust, loyalty, and sales. At RELIANOID, we help retailers stay resilient with intelligen..

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@anjali shared a link, 1 month, 1 week ago

Customer Marketing Manager, Last9

Instrumentation: Getting Signals In

See how instrumentation in OpenTelemetry helps track app issues, know the difference between auto and manual methods, and when to use them.

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@devopslinks added a new tool Syft , 1 month, 1 week ago.

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@kaptain added a new tool KubeLinter , 1 month, 1 week ago.

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@devopslinks added a new tool Grype , 1 month, 1 week ago.

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@kaptain added a new tool Hadolint , 1 month, 1 week ago.

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@varbear added a new tool Bandit , 1 month, 1 week ago.

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@devopslinks added a new tool JFrog Xray , 1 month, 1 week ago.

LangChain is a modular framework designed to help developers build complex, production-grade applications that leverage large language models. It abstracts the underlying complexity of prompt management, context retrieval, and model orchestration into reusable components. At its core, LangChain introduces primitives like Chains, Agents, and Tools, allowing developers to sequence model calls, make decisions dynamically, and integrate real-world data or APIs into LLM workflows.

LangChain supports retrieval-augmented generation (RAG) pipelines through integrations with vector databases, enabling models to access and reason over large external knowledge bases efficiently. It also provides utilities for handling long-term context via memory management and supports multiple backends like OpenAI, Anthropic, and local models.

Technically, LangChain simplifies building LLM-driven architectures such as chatbots, document Q&A systems, and autonomous agents. Its ecosystem includes components for caching, tracing, evaluation, and deployment, allowing seamless movement from prototype to production. It serves as a foundational layer for developers who need tight control over how language models interact with data and external systems.

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