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The latest News and Information on Observabilty for complex systems and related technologies.

APM vs Observability: What comes next?

Remember how I said that blog was going to be my last entry on the topic of "APM vs Observability?" Well, it turns out I had a little more to say. I'd like to spend a few moments talking about the future of APM and Observability. I think it comes down to two major initiatives: AI and Open Telemetry. (NOTE: in this section, I'm using the word "observability" to refer to the discipline of monitoring and observability as a whole, rather than any specific tool, technique, or vendor-based solution.)

Understand, diagnose, and optimize SQL queries: Introducing Grafana Cloud Database Observability

It’s widely acknowledged that most application performance problems stem not from the application itself, but from the underlying database. Slow or inefficient database queries are often the primary cause of these issues, acting as the biggest driver of application performance incidents. If you’ve been troubleshooting slow API calls or sluggish services, chances are the root cause likely resides within your database layer.

OpenTelemetry Java Agent for Spring Boot: Complete Setup Guide

The OpenTelemetry Java Agent provides zero-code instrumentation for Spring Boot applications through bytecode manipulation. This guide covers setup, configuration, auto-instrumentation capabilities, and production deployment strategies for implementing distributed tracing and observability.

How OpenTelemetry can enhance observability in distributed systems: Practical examples

Observability has become one of the fundamental elements of performance and reliability as modern applications move toward cloud-native architectures, microservices, and multi-cloud. Traditional monitoring techniques often fall short in such dynamic, distributed environments. That’s where OpenTelemetry (OTel) , an open-source observability framework comes into picture.

Conquer Complexity, Accelerate Resolution with the AI Troubleshooting Agent in Splunk Observability Cloud

The digital landscape has transformed dramatically, and with it, the demands on our systems have grown exponentially. Traditional monitoring tools struggle to provide sufficient insight into complex, distributed, cloud-native environments. Observability is the answer, moving beyond merely knowing "what" is happening to understanding "why" it's happening, and its impact on user experience and business outcomes.

If it Wanted to, it Would: The Bitter Lesson for LLM Users

There’s a viral saying folks use about flaky crushes, spouses, and forgetful friends: "if he wanted to, he would." The idea is straightforward: when someone cares, they make the effort. As it turns out, the same principle applies surprisingly well to AI. Systems, like people, have things they "want" to do. Each model has patterns of reasoning and synthesis it performs naturally.

The Hidden Bottlenecks in AI Infrastructure (and How to Fix Them)

Artificial intelligence has entered an era where infrastructure is the real moat. Teams spend millions on GPUs, yet models still stall, latency spikes unpredictably, and throughput flatlines at 20% of what spec sheets promise. These hidden bottlenecks lurk far beneath the surface - in power grids, network fabrics, memory bandwidth, orchestration layers, and even governance policies. In this guide, we uncover where AI infrastructure actually breaks, what the emerging data and research reveal, and how Clarifai's reasoning and orchestration stack helps eliminate these unseen friction points.

SIEM Migration in 68 Days

In this session, we will discuss how the University of Pittsburgh was able to modernize their data processing strategy, migrate to a new SIEM solution, and avoid ballooning SIEM costs all within 68 days from the first install of a Cribl product. We will showcase how we were able to use Cribl's software to easily handle the following scenarios: 100% agent replacement and consolidation using Cribl Stream Workers and Edge.