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

Unified Logs, Traces, and Errors: Why One Tool Beats Three

Jul 10, 2026 By Sarah Morgan In Scout

Last updated: July 2026 Your Rails app throws a 500. You open Sentry and find the exception. The stack trace points to a controller action, but it does not tell you why the database call failed. You switch to Datadog and search for the request trace. The trace shows a 3-second query, but you do not know what the application was logging at that moment. You open your log aggregator, paste in the request ID, and scroll through output until you find the slow query log line that explains the lock contention.

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When and what should I be logging?

Jul 9, 2026 By Ben Coe In Sentry

This is a follow-up to Sergiy’s post Errors, traces, logs, metrics: when to reach for what. Modern observability platforms, like Sentry, give developers a lot of choice. For a given problem, should you use traces, profiles, metrics, logs? If you take away one thing from this post, I hope it’s this: when in doubt, start by adding a few targeted log lines.

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Time Series Foundation Model: The AI That Stops Disasters

Jul 9, 2026 By Splunk In Splunk

It's time to go from reactive firefighting to predictive prevention. Learn how the Time Series Foundation Models can forecast system failures before they cascade.

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Build an SRE Agent Harness for AIOps Without Context Blowout

Jul 9, 2026 By Mezmo In Mezmo

An agent harness for AIOps is the runtime layer that coding agents like Claude Code were never built to provide: context isolation, decision traceability, and gated execution for tools that touch production. Aura is Mezmo's open-source (Apache 2.0) agent harness, purpose-built for operations work rather than software development.

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The future of governing AI agents

Jul 8, 2026 By Marcus Jeffes In Elastic

How to build governance into autonomous security agents from the architecture up The industry has moved fast on capabilities. Agents now triage alerts, investigate endpoints, create detection rules, and enrich indicators, and they are even capable of performing most actions we as security operators can perform. The architecture patterns are maturing, as are the models, but governance is not keeping pace.

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Small Language Models Can Save You a Fortune on AI Costs

Jul 8, 2026 By Splunk In Splunk

Small language models are cheaper, run privately on your own hardware, and often beat the big models on focused tasks like sorting emails or summarizing transcripts — and they're perfect for checking a large model's work. The key is knowing when to use which.

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Reducing token usage by 90%?

Jul 7, 2026 By Coralogix In Coralogix

Watch the full episode: MCP vs CLI: Does it even make a difference? Live Laugh Logs ep. 3.

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Called it (mostly): Checking in on 2026 predictions so far

Jul 7, 2026 By Sumo Logic, Inc. In Sumo Logic

On this episode of Masters of Data, we revisit the predictions Adam White, Zoe Hawkins, and David Girvin made at the end of last year, checking our own scorecard halfway through 2026. The hits: agents running amok and deleting databases, MCP becoming the backbone for tracking what agents actually do, growing security gaps around personal data, and a collective rejection of low-quality AI content. The misses: we underestimated how fast companies would cut staff for AI, then quietly start rehiring once the agents couldn't cover the work, and we're still arguing about whether token burn is a cost problem or a coming attack vector.

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Q&A: How Elastic and Anyshift are bringing AI-powered context to incident response

Jul 6, 2026 By Sunnie Weber In Elastic

Incident response often depends on connecting two kinds of context: what changed in the environment and what the logs say happened next. Through a new integration with Elastic, Anyshift’s AI agent, Annie, can read from a customer’s Elasticsearch deployment to search logs, surface error and warning spikes, and correlate log evidence with infrastructure change history.

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SLA vs SLO vs SLI Explained: What Should You Track?

Jul 6, 2026 By Motadata In Motadata

In this video, learn the difference between SLA, SLO, and SLI and why understanding each one is essential for delivering reliable IT services. Discover how these three service level metrics work together and why tracking the right one helps improve service reliability, customer satisfaction, and operational performance. Whether you're an IT operations professional, SRE, DevOps engineer, or service manager, this video explains SLA, SLO, and SLI in simple terms so you can build measurable goals and realistic service commitments.

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