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The latest News and Information on Log Management, Log Analytics and related technologies.

The Answer to SRE Agent Failures: Context Engineering

AI agents for SREs were supposed to slash mean time to resolution and eliminate alert fatigue. Instead, most teams got expensive, unreliable tools that burn through tokens without delivering insights. But what if the problem isn't the AI models themselves? Recent benchmarking reveals the real bottleneck: context engineering. When we tested our context engineering approach against conventional methods, the results were dramatic: Scroll down for our benchmark results to see the full comparison.

Cribl to the rescue for SIEM migrations

Your security teams face escalating data volumes, vendor changes, and cost pressures when they migrate between SIEM platforms. Cribl simplifies these migrations by giving you flexible data routing, reducing storage costs, and accelerating time-to-value. How? Let’s look at how a global customer used Cribl Stream to migrate CrowdStrike FDR logs from Splunk to Microsoft Sentinel efficiently and cost-effectively.

Introducing Event iQ: Smarter Event Correlation in Splunk IT Service Intelligence (ITSI)

Every day, IT teams are flooded with alerts—thousands of messages about performance issues, service outages, or suspicious activity. With so many notifications, it’s easy to get overwhelmed, miss critical problems, or waste time chasing false alarms. Correlating related alerts into groups can help reduce the noise and make sense of everything, but setting up those correlations takes time, experience, and a lot of both system and historic knowledge.

Monitor the Health, Performance, and Security of Your AI Application Stack with AI Agent and AI Infrastructure Monitoring

At this year’s.conf25, we introduced an exciting new chapter in observability at Splunk — one that is unified, AI-powered, and agentic — to ensure ITOps and engineering teams are digitally resilient in the AI era.

Powering AI Innovation with Splunk: Meet the Cisco Data Fabric

If you are leading technology innovation in your organization, you know the relentless surge of machine data is rewriting the rules of the digital enterprise. The upside? Incredible opportunities for AI-driven transformation. The challenge? Unprecedented complexity. Today’s leaders are under enormous pressure to unify, analyze, and act on a deluge of data streams across multiple environments.

What Are Buckets in Elasticsearch? (Explained in 60 Seconds)

Overwhelmed by raw data? In this short video, we demonstrate how Elasticsearch utilizes buckets to group and organize data by time, value, region, or any other shared trait. Whether you're tracking error codes or hourly sales trends, buckets and nested aggregations help turn chaos into clarity. Additionally, discover how time-based bucketing enables you to spot patterns and zoom in on valuable insights quickly.

Empowering an MCP server with a telemetry pipeline

This blog was authored by Jason Bloomberg, Managing Director, Intellyx BV ‍ Observability depends upon telemetry – the data streaming from various applications, services, and systems that indicate their internal state in real-time. Various tools consume such telemetry to enable both operational and cybersecurity tasks.

How to Transform Telemetry Data with the OpenTelemetry Transformation Language

This demonstration shows how to use the OpenTelemetry Transformation Language (OTTL) to transform, filter, and enrich telemetry in the OpenTelemetry Collector without changing application code. We walk through a sample Python application and OpenTelemetry configuration file, generate real traffic, and then analyze the results in Splunk Observability Cloud.

What Are Vector Embeddings? (Explained in 2 Minutes)

In under 2 minutes, we explain what vector embeddings are, how they work, and how to use them in real-world applications like text expansion. We'll also show how Elasticsearch supports vector search with two powerful models: E5, open-source text embedding models designed for multilingual search, and ELSER, a sparse embeddings model from Elastic.