Operations | Monitoring | ITSM | DevOps | Cloud

Signal Enrichment: Turning Noisy Alerts into Actionable Intelligence

This is the fourth post in our series on the future of incident management, which builds upon The Future of Incident Management: Your Blueprint for Operational Excellence, How Native Process Automation and Auto-Remediation Drive Operational Excellence, and Service Intelligence is the Future of Proactive Incident Management.

Automated RAG pipeline evaluation and benchmarking with RAGAS

Retrieval-Augmented Generation (RAG) pipelines have become an integral part of how Large Language Models (LLMs) access information beyond their training cutoff. These pipelines enable LLMs to deliver current, accurate, and grounded responses. By fetching relevant external documents, RAG mitigates common LLM challenges like factual inaccuracies and hallucinations. However, this methodology introduces a new complexity: evaluating RAG pipeline performance is particularly challenging.

The observability maturity curve: How IT leaders are shifting from tools to outcomes

Observability has come a long way from its origins in monitoring logs and metrics. Today, it sits on a maturity curve: Organizations move from fragmented tool stacks to unified platforms to proactive engineering practices that tie reliability to business outcomes. To better understand where IT leaders are on this curve, Grafana Labs surveyed 150 decision-makers across industries in advance of ObservabilityCON 2025.

How to automate sending SquaredUp dashboards to Slack with the Notification API

SquaredUp's existing notifications fire when monitors change state. With Notification API, you control the trigger. Send dashboards on a schedule, before meetings, or on-demand through chat commands. In this step-by-step guide, you’ll learn how to automate sending SquaredUp dashboards to Slack. I’ll use Power Automate as the example, but the same approach works with other automation tools such as Zapier, Make, n8n, or even a custom script, as long as it can send an HTTP request.

LLM Observability Explained: Prevent Hallucinations, Manage Drift, Control Costs

Large Language Models (LLMs) are transforming how businesses interact with users, automate workflows, and deliver insights in real time. But as powerful as these models are, running them at scale comes with unique challenges, from hallucinations and latency spikes to cost overruns and user trust issues.

How to Perform Ping Tests: Different Tools and Techniques

If you’re a remote worker struggling with video calls, or a gamer noticing lag, a quick Internet ping test using an online ping tester can give you a simple yes/no answer: Is my connection alive, and how fast does it respond?. But if you’re a network admin or IT professional, that’s just scratching the surface. Business networks are more complex beasts.

Top 10 HIPAA-Compliant Messaging Apps (2025): A Guide to Secure Healthcare Communication

Secure communication in healthcare is no longer optional. With patient data, lab results, and care coordination increasingly handled over mobile and digital channels, hospitals and clinics need tools that keep messages safe and compliant with HIPAA regulations. A HIPAA-compliant messaging app goes beyond standard texting apps, offering encryption, audit trails, and signed Business Associate Agreements (BAAs) to meet the requirements of the HIPAA Security Rule.

Why DEX Scores Must Be Part of Every Total Cost of Ownership Study

Price is not the same as cost. When organizations evaluate new end-user technology investments, whether that’s laptops, operating systems, or management tools the conversation inevitably turns to Total Cost of Ownership (TCO). TCO studies traditionally focus on direct, measurable costs: hardware procurement, software licensing, support contracts, and lifecycle services. But there’s a growing blind spot in these calculations: the employee experience.

How Redgate's Foundry is Shaping the Future of Database Innovation with AI

Learn how Redgate’s Foundry drives AI innovation in database management - from intelligent monitoring and ML-based automation, to smarter SQL optimization. In today’s rapidly evolving database landscape, innovation is essential. With the rise of artificial intelligence (AI), machine learning (ML), and automation, database management is undergoing one of its most significant transformations in decades.

Scaling Datadog observability: 1,000 integrations and counting

Integrations have always been central to the Datadog platform, enabling customers to collect the data they need directly from the technologies they use every day. By unifying signals from infrastructure and applications to security and SaaS applications, teams gain both high-level visibility and the ability to drill into the details that matter the most. With more than 1,000 integrations now available, the Datadog ecosystem continues to expand alongside the platforms our customers rely on.