Operations | Monitoring | ITSM | DevOps | Cloud

Agentic RAG on Dell AI Factory with NVIDIA and Elasticsearch Vector Database

We are excited to collaborate with Dell on the white paper,Agentic RAG on Dell AI Factory with NVIDIA. The white paper is a design reference document for developers outlining strategies and solution components to implement agentic retrieval augmented generation (RAG) applications. It’s a design point for organizations across industries, specifically healthcare, for the agentic RAG framework decision-making with AI-driven data retrieval.

Supply Chain and Warehouse Trends in 2024 and Beyond

The COVID-19 pandemic disrupted the supply chain industry and exposed its vulnerabilities. Adding to the pressure, even more complicated challenges have emerged, including extreme weather events, complicated geopolitical climates and the complex evolution of AI. A survey by Ivanti reveals the state of the industry, key insights from insiders and trends to watch. The survey collected insights from management and employees across a range of supply chain roles.

Adding AI to Observability 2.0 for Dynamic Observability

The original premise of observability was to ensure system health, identify issues, and resolve those issues efficiently. As I recently outlined, the legacy approach (sometimes called Observability 1.0 now) relied heavily on metrics and tracing because logs were seen as too noisy or challenging. But, as most forward thinkers have identified now, logs are exactly the telemetry type that we need the most.

Are you ready for the next outage? How a to prepare for any crisis

We live in an “always on” world, so unplanned outages are more than just inconvenient. They can result in lost revenue, damaged reputations, and, more importantly, frustrated customers. While preventing outages is impossible, the most resilient teams must be prepared with a solid plan, a “technical go bag,” so to speak: a collection of tools, plans, and resources ready to activate at the first sign of trouble.

The Hidden DevOps Problem: Why Tools Alone Aren't Enough

In today’s fast-paced software product development world, efficiency and innovation aren’t just important — they’re everything. DevOps engineers and SREs are tasked with maintaining high-performing systems, improving deployment frequency, and ensuring stability while navigating a dizzying amount of tools. Developers who write code also need to learn these tools and are dependent on them to do their jobs. So what’s the problem?

The Top 10 LLM Evaluation Tools

The emergence of Large Language Models (LLMs) such as GPT-4, BERT, and their counterparts has revolutionized artificial intelligence across industries. These advanced AI systems power a variety of applications, from chatbots and content generation to sophisticated decision-making tools. However, deploying LLMs in real-world scenarios brings challenges such as ensuring accuracy, fairness, robustness, and efficiency. LLM evaluation tools have become essential for organizations aiming to maintain high standards of performance and reliability in these AI-driven systems.
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3 Primary Differences Between CRM Tools and Workflow Management Software

When companies think of tools for managing customer relationships and internal operations, CRM (Customer Relationship Management) software is often one of the first to come to mind. CRMs are powerful tools for tracking leads, managing sales pipelines, and ensuring smooth customer acquisition. However, once a customer is closed and the focus shifts to delivering services, companies often realize that CRMs alone are insufficient. This is where workflow management software becomes essential.