Operations | Monitoring | ITSM | DevOps | Cloud

AI

The Hater's Guide to Dealing with Generative AI

Generative AI is having a bit of a moment—well, maybe more than just a bit. It’s an exciting time to be alive for a lot of people. But what if you see stories detailing a six month old AI firm with no revenue seeking a $2 billion valuation and feel something other than excitement in the pit of your stomach? Phillip Carter has an answer for you in his recent talk at Monitorama 2024. As he puts it, “you can keep being a hater, but you can also be super useful, too!”

ScienceLogic Wins "AI Breakthrough Award" for Best AIOps Platform

ScienceLogic, a leader in automated IT infrastructure monitoring and AIOps, has won the “Best AIOps Platform” award in the seventh annual AI Breakthrough Awards! Run by Tech Breakthrough, a leading market intelligence and recognition platform for today’s most competitive global technology markets, the awards highlight some of the world’s most innovative artificial intelligence (AI) companies, technologies, and products.

Building an AI Assistant in Splunk Observability Cloud

Splunk Observability Cloud is a full-stack observability solution, combining purpose-built systems for application, infrastructure and end-user monitoring, pulled together by a common data model, in a unified interface. This provides essential end-to-end visibility across complex tech stacks and various data types, such as metrics, events, logs, and traces (MELT), as well as end-user sessions, database queries, stack traces and more.

Bridging the Gap between Financial Services and Customer Satisfaction with AI Support

The financial services industry is evolving rapidly, and customers demand exceptional service and personalized experiences. Artificial Intelligence (AI) bridges the gap between traditional financial services and modern customer expectations.

10 Steps to Optimize Software Operations with AI

How can businesses maintain a competitive edge and ensure operational efficiency? The answer lies in optimizing software operations with Artificial Intelligence (AI). By leveraging AI, companies can automate processes, enhance decision-making, and significantly improve their software operations. Are you curious about how AI can benefit your business? This guide aims to provide a comprehensive roadmap for integrating AI into your software operations, addressing common concerns and questions from IT managers, software engineers, and business leaders.
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Enhancing Aspire with AI: integrating Ollama for local error resolution

In this article, we'll explore how we developed an Aspire component that spins up an Ollama container and downloads a Large Language Model, ready for use. If you're new to any of these technologies, you can continue reading, otherwise feel free to skip to the technical walkthrough. As a quick bit of background, we recently released an Aspire component that brings a free, lightweight Raygun app into your local development environment to help debug exceptions. We then subsequently enhanced this with AI Error Resolution capabilities which runs entirely on your local machine.

Practical Demo: Harnessing the Power of #AI and #Automation

Harnessing the Power of AI and Automation This webinar delves into the adoption of generative AI and its role in ITSM, decision making, user experience transformation, ticket classification, self-healing, and virtual agents. It also covers incident summarization, knowledge article generation, and the AI Configuration Hub. The benefits of AI and automation, such as improved data accuracy, analyst productivity, and employee experience, are highlighted.

Identify anomalies, outlier detection, forecasting: How Grafana Cloud uses AI/ML to make observability easier

At Grafana Labs, our No. 1 approach when building AI/ML tools is to enable humans (a.k.a. all of us!) to understand complex systems. In other words, we want to make observability still human, but less complicated. (Our second use case? Making social media more fun.) We believe that AI/ML tools in observability should work towards minimizing toil and the need for everyone in your organization to have the same deep domain knowledge about your increasingly complex stack.

Handling LLM Hallucinations: Taking Your LLM Features From Prototype to Production

This is a vendor guest post authored by the team at Lytix. Lytix being discussed on this blog is not an endorsement by Taloflow or an approval by Taloflow of any of the content contained herein. Taloflow is not compensated for this vendor guest post in any way and presents this post for purely informational purposes and the benefit of site users.

How Meta and Google use AI to improve incident response

The world population in 2024 is approximately 8.12 billion people. Of these, 4.3 billion people use Google regularly, while 3.74 billion are active users on Meta's platforms. Any disturbance involving these tech giants will surely make headlines, as seen in the recent Google’s Unisuper incident. The scale of these tech companies brings fascinating challenges in every aspect of their operations, including incident response.