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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.

Why Observo AI and SentinelOne Are Building the Autonomous SOC Together

Today's announcement that Observo AI is joining SentinelOne isn't just about combining two companies. It's about accelerating a fundamental transformation in how security operations work—moving from reactive, manual processes to truly autonomous defense. The vision is bold: security operations that think, adapt, and respond faster than any human team could alone. But that future requires rethinking security data from the ground up.

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.

What is Infrastructure Monitoring? How it Works, Key Metrics & Use Cases

Infrastructure monitoring is the process of continuously collecting, analyzing, and visualizing data from an organization’s IT infrastructure. With infrastructure monitoring, DevOps teams can maintain system health, meet SLAs, reduce downtime, and detect and resolve issues proactively. This ensures optimal performance, availability, and reliability. Key networks components infrastructure monitoring typically covers.

Transform your public sector organization with embedded GenAI from Elastic on AWS

Elastic featured in AWS Generative AI Hub for public sector Elastic is proud to be featured in the new AWS Generative AI Content Hub for public sector — a destination showcasing the most impactful ways agencies can securely adopt and scale generative AI (GenAI).

The Fourth Pillar of Observability

Your application is only as reliable as the infrastructure it runs on. Most commonly, that means Kubernetes is doing the job by managing fleets of containers, scaling services on demand, and keeping workloads distributed across nodes. Traditional dashboards weren’t built to scale with this reality. They give you snapshots of raw metrics. They don’t scale to multi-cluster environments. They don’t map relationships between resources.