Operations | Monitoring | ITSM | DevOps | Cloud

Enhancing Alerts with AI: Leveraging Amazon Bedrock and LLM's for Graylog

In this talk, we’ll explore the cutting-edge work InfusionPoints has done to process and enrich alerts from Graylog using Amazon Bedrock and advanced Large Language Models (LLMs) from Amazon Titan and Anthropic. Discover how we’ve harnessed the power of AI to elevate the accuracy, relevance, and actionable insights of our security alerts, transforming how we respond to potential threats.

Lessons from Building an AI Copilot

Artificial intelligence is reshaping industries at an unprecedented pace. AI has found its way into almost every vertical, from writing code to diagnosing illnesses, promising efficiency and innovation. The idea of an AI Copilot—a tool that acts as your assistant to tackle complex tasks—is particularly exciting. In our space, observability, the possibilities seemed endless. We asked ourselves how AI could simplify troubleshooting in microservices.

Summarizing SRE/Ops Podcasts Using an LLM

There are plenty of good SRE/Ops related podcasts out there. I follow a few of them and listen to episodes whose titles sound interesting. The problem with podcasts is that some episodes focus on one topic, and other episodes deal with a host of topics. In between there is filler and things that are not relevant to the topic but are necessary to carry on a conversation. Spending 30-60 minutes listening to podcasts is not always a great use of time.

Six Enterprise AI Predictions for 2025

In many ways, the upcoming year is shaping up to be one of opportunity and innovation as IT leaders see more benefits and options around AI than ever before in running the enterprise. By the same token, this progress is creating new complexities and choices for organizations to navigate. Through conversations with ScienceLogic customers, leading industry analysts, partner companies and key executives, several AI-related themes have emerged moving into 2025.

Lightrun AI Autonomous Debugger

This video showcases how with Lightrun developer observability platform, developers can leverage the AI debugger within the platform plugin to swiftly identify critical code level issues through automated hypothesis and insertion of debugging actions at runtime (Lightrun dynamic logs, virtual breakpoints (Snapshots) and more. That helps reduce MTTR to mere minutes.

CNBC Says AI Will Replace Tech Support - Here's What They Got Wrong

Another day, another AI headline designed to spike your blood pressure. The Service Management industry is no stranger to dramatic proclamations about AI, and neither are you. But what’s the real story behind CNBC’s latest take, “The tech support desk at work is one of the first jobs AI is rapidly replacing?” Does the Palo Alto Networks company need media coverage? Does CNBC? CompTIA? All of them? Perhaps there is a hidden agenda behind the article being published.

Are Our Networks Ready for AI?

With all the hype surrounding AI, it’s critical to focus on building resilient networks capable of handling the performance demands that AI will introduce. As I often say, if your network observability solution isn’t detecting packet loss, neither will your AI engine. When you ask, “What’s the status of our global network health this morning?” a flawed or incomplete response could jeopardize critical decisions.