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

What Is NetFlow, and How Does It Reveal Where Traffic Goes?

In this video, learn what NetFlow is and why it's one of the most effective technologies for understanding network traffic. Discover how NetFlow goes beyond basic bandwidth monitoring by showing who is using your network, what applications are consuming bandwidth, and how traffic patterns change over time. Whether you're a network administrator, IT operations engineer, or infrastructure manager, this video explains NetFlow in simple terms and shows how it helps identify bandwidth hogs, troubleshoot slow networks, and make smarter capacity planning decisions.

A Four-Step Blueprint for Faster Root Cause Analysis: A Logz.io Webinar

Incident investigations take so long not because the fix is hard, but because finding the right fix is. Most engineers spend 20 to 60 minutes just understanding what’s wrong before they can act, not fixing anything, just trying to see the full picture. The framework that changes this has four steps: Orient, Isolate, Hypothesize, and Verify, and the order matters more than the tools.

Coralogix vs Sumo Logic: Support, Pricing, Features & More

Coralogix and Sumo Logic are two different answers to the same observability platform decision. Where Coralogix processes telemetry in flight, stores it in your own Amazon Simple Storage Service (S3) bucket, and prices on data ingested, Sumo Logic keeps data in vendor-managed storage and, under its Flex model, bills for data scanned at query time. Both platforms have introduced pricing and artificial intelligence (AI) changes in the past year, and those changes have widened the difference between them.

Coralogix vs New Relic: Comparison Guide (2026)

Coralogix and New Relic both cover the full observability surface, but they charge for it and store it in different ways. One prices purely on data ingested and writes telemetry to a bucket you own, while the other combines ingest pricing with per-user licensing and retains data in its own backend. This guide covers how the two platforms compare on core features, pricing structure, AI observability, archiving and retention, security coverage, and support, then shows when each one is the stronger choice.

What Is Agentic Observability? The Complete Guide for Enterprise Engineering Teams

TL;DR Agentic observability uses AI agents to autonomously investigate incidents, identify root causes, and take action in production environments. Unlike traditional monitoring (which alerts and waits) or AIOps (which assists human analysis), agentic platforms conduct the investigation themselves. Key capabilities include autonomous incident triage, evidence-backed root cause analysis, alert noise reduction, and governed remediation.

Logz.io Webinar Recap: A Four-Step Blueprint for Faster Root Cause Analysis

Incident investigations take so long not because the fix is hard, but because finding the right fix is. Most engineers spend 20 to 60 minutes just understanding what’s wrong before they can act, not fixing anything, just trying to see the full picture. The framework that changes this has four steps: Orient, Isolate, Hypothesize, and Verify, and the order matters more than the tools.