#aiops Development Tutorials & Tips | Roast Dev

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Everything You Need to Know About LiteLLM Python SDK

This guide provides a comprehensive deep-dive into the LiteLLM Python SDK, designed to help you effectively integrate over 100+ Large Language Models (LLMs) into your applications using a single, cons...

29.03.2025 0 Read More

Building LiteLLM Plugins with `async_pre_call_hook` for Proxy Mode

You're using the LiteLLM Proxy, appreciating its ability to unify access to various Large Language Models (LLMs). But what if you need more? What if you need to dynamically route requests based on use...

29.03.2025 0 Read More

Comprehensive Guide to PromptL and the Its Python Library (promptl-py)

Working with LLMs is powerful, but crafting and managing the prompts that drive them can quickly become complex. As you move beyond simple questions, you start juggling system messages, user inputs, e...

30.03.2025 0 Read More

The New Enterprise IT Frontier: How AI & MLOps Are Transforming Business Operations

The future of IT isn’t just “digital transformation”—it’s AI-driven revolution. But here’s the catch: AI without MLOps is like a Ferrari with square wheels. Let’s see how the future of e...

31.03.2025 0 Read More

Understanding MCP (Model Context Protocol) with Examples

Introduction The Model Context Protocol (MCP) is a structured way to manage and exchange contextual information between AI models and applications. It allows AI systems to maintain state, rem...

01.04.2025 0 Read More

Easiest AI param changes in Realtime

The easiest (and free) way to modify configuration parameters for AI algo, while the algo is running, in true real-time, is using the SDK and a free “Team Starter” plan by Kiponos.io How ...

01.04.2025 0 Read More

AI-Driven DevOps: How AI is Changing CI/CD and Automation

Introduction In the fast-paced world of software development, automation and continuous integration/continuous deployment (CI/CD) pipelines have become indispensable. However, with the growin...

01.04.2025 0 Read More

AIOps: Automating Incident Management with AI & Machine Learning

Introduction The increasing complexity of modern IT environments presents significant challenges for DevOps teams. As infrastructure scales, handling incidents manually becomes impractical, l...

03.04.2025 0 Read More

AI Agents with MCP: Practical Takeaways from n8n and GitHub Copilot

Key Takeaways for Developers ✅ Successful Approaches: Breaking down tasks into focused, single operations Maintaining control over the workflow instead of letting AI decide Using AI for spe...

07.04.2025 0 Read More

LLM Benchmarking on the Nosana grid

Intro The Nosana grid contains about two thousand nodes with various hardware configurations, which are actively running AI models. At the start of the Nosana test phase, these nodes have mos...

07.04.2025 0 Read More

Everything You Need to Know About LiteLLM Python SDK

Building LiteLLM Plugins with `async_pre_call_hook` for Proxy Mode

Comprehensive Guide to PromptL and the Its Python Library (promptl-py)

The New Enterprise IT Frontier: How AI & MLOps Are Transforming Business Operations

Understanding MCP (Model Context Protocol) with Examples

Easiest AI param changes in Realtime

AI-Driven DevOps: How AI is Changing CI/CD and Automation

AIOps: Automating Incident Management with AI & Machine Learning

AI Agents with MCP: Practical Takeaways from n8n and GitHub Copilot

LLM Benchmarking on the Nosana grid

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