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

How to Reduce Log Data Costs Without Losing Important Signals

You can cut your log costs by removing repetitive, low-value logs early and keeping only the parts that genuinely help you understand issues. Modern systems generate logs far faster than you expect. Even when your workload stays stable, infrastructure components, retries, and background workers continue producing a steady stream of repeated entries.

Search Telemetry Without Limits in a Multi Cloud and AI World

Cribl Search gives you one lens across all your telemetry data no matter where it lives. Instead of forcing teams to move data into one system or jump between tools, you get a familiar pipe based query experience with dashboarding and alerting built in. Storage and query processing stay separate so you decide where your data lives while your users get fast, simple access in one place.

Use OpenTelemetry with Observability Pipelines for vendor-neutral log collection and cost control

Today, many DevOps and security teams operate in a world of complex, hybrid, or multi-vendor environments. As more teams look to avoid lock-in by adopting open standards, OpenTelemetry (OTel) is quickly gaining adoption as the primary open source method for DevOps and security teams to instrument and aggregate their telemetry data. However, OTel alone may lack the advanced processing functions, native volume control rules, and hybrid environment support that large organizations need.

Architecture for the agentic era: How AI will reshape data, security, and observability

As AI agents move from copilots to autonomous systems, they’re generating and consuming data at unprecedented scale. The result is a new kind of infrastructure pressure — one that’s quietly reshaping how organizations think about data, cost, and control. Across IT, Security, and Observability, leaders are realizing a hard truth: too much data is too costly.

AI-Suggested Alert Thresholds for Mobile Telemetry

Life is pretty good. I’ve shipped a mobile app and I’m (happily) drowning in telemetry. Battery impact, time in foreground/background per screen, crash rates, slow frames, network retries – the works. The data is brilliant; the challenge is turning signals into reliable alerts that catch real issues which are relevant to my app’s functions. So… what should I actually listen for, and where should I set the thresholds?

Why Gaining Control of Your #telemetry Data Is a Game Changer

Disconnected pipelines. Unknown data sources. Costs that do not add up. Many teams struggle to answer a simple question. What data do we have and where is it going? In this clip, a Cribl customer explains how bringing all telemetry data together changed everything. With Cribl, their team can finally see what they collect, where it flows, and what it costs. That clarity unlocked smarter reduction, better routing decisions, and major optimization across security and observability workflows.

From Data Lake to Lakehouse. Why Cribl is Preparing for the Agentic #ai Era #telemetry

Customers asked for a simpler way to store and access telemetry data, and Cribl delivered. First came Cribl Lake. Cost effective data storage, flexible access, and identity based authorization instead of infrastructure based access rules. A simple way to retain data at rest and run slow, inexpensive analytics when needed. But the story did not end there.

KubeCon North America 2025: OpenTelemetry Recap from Atlanta

KubeCon + CloudNativeCon North America 2025 wrapped up in Atlanta last week, and it sure did feel like a big one for OpenTelemetry. Between Observability Day, the project updates, and the activity around the OpenTelemetry Observatory booth, you could feel how quickly the ecosystem is maturing.

Pastries with SREs: FinOps is to ROI as a coffee is to cannoli

In this episode of Pastries and SREs, our hosts tackle one of the hardest questions observability leaders face: "How do you prove the ROI of observability?" This isn’t just about uptime or dashboards. It’s also about aligning observability with business outcomes, cloud cost savings, and FinOps metrics that matter to leadership.