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The latest News and Information on Observabilty for complex systems and related technologies.

lightrun

Top 5 Continuous Monitoring Tools and Why Runtime Context Is the Layer They Are Missing

Apr 7, 2026 By Lightrun Team In Lightrun
Continuous monitoring tools track system health, performance, and behavior in real time across production environments. For a deeper understanding of how this fits into modern DevOps practices, see this guide on continuous monitoring and its impact on DevOps. They collect logs, metrics, and distributed traces across the infrastructure and application layers, giving engineering teams visibility into how their systems are running, where anomalies occur, and when something needs immediate attention.
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honeycomb

AI Working for You: MCP, Canvas, and Agentic Workflows - Part 2

Apr 6, 2026 By Ken Rimple In Honeycomb
In our previous post in our series on observability for the agent era, we looked at how Honeycomb provides unique visibility into LLMs operating in your production environment. Now, let’s flip it around and explore how Honeycomb provides observability insights uniquely suited to helping your AI agents rapidly diagnose and fix production issues, and build production feedback into the next round of development.
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honeycomb

The Fundamentals: Fast, Deep, and Ready for What Comes Next - Part 3

Apr 6, 2026 By Ken Rimple In Honeycomb
The previous two posts in this series have looked at some of the use cases Honeycomb customers are implementing to observe LLMs in production and power agentic observability workflows. In this third and final post, we’ll take it back to basics and look at how the fundamental capabilities and infrastructure of Honeycomb provide the comprehensive data and fast performance that makes these use cases work at production scale. AI capabilities built on a weak observability foundation fall apart fast.
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We Know Before it Breaks: Observability-Driven Development

Apr 6, 2026 By Datadog In Datadog
When stakeholders push for faster growth (new markets, new features, newly modernized stack) your engineering model has to change too. At FitnessPassport, the shift from offshore waterfall delivery to an in-house team meant rebuilding not just services, but confidence: legacy systems with weak logging and little visibility made it hard to know whether changes were working and impossible to spot issues before users did. In this talk, Director of Engineering Rob Mitchell will share how FitnessPassport adopted Datadog and used structured logs, metrics, and traces to tighten feedback loops.
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Paris | Observability Unleashed - Boostez vos opérations IT, DevOps & SRE

Apr 3, 2026 By Splunk In Splunk
La complexité des environnements IT ne cesse de croître. La visibilité en temps réel n'est plus une option. Le 14 avril 2026, Stéphane Estevez , EMEA Observability Market Advisor chez Splunk, vous invite chez Cisco à Paris pour un événement dédié à l'observabilité, avec les équipes Splunk & Cisco. Au programme : Observabilité assistée par l'IA Stratégies de données intégrées OpenTelemetry simplifié De la donnée à l'action, avec des cas concrets et démos live Observabilité pour l'IA et par l'IA.
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honeycomb

KubeCon + CloudNativeCon EU 2026: What We Learned About AI, Observability, and Fast Feedback Loops

Apr 3, 2026 By Abdullah Chowdhury In Honeycomb
Honeycomb was excited to attend KubeCon + CloudNativeCon Europe, where one theme stood out across sessions: as AI reshapes how software is built and run, teams are being pushed to rethink how they understand their systems. Without strong observability and feedback loops, AI can accelerate confusion, misalignment, and operational risk.
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selector

The Business Case for AI-Driven Observability in Network Operations

Apr 3, 2026 By Dallon Robinette In Selector
Modern network operations generate an extraordinary amount of telemetry. Metrics, logs, events, topology data, cloud signals, and service context all contribute to a richer picture of system behavior. As environments expand across cloud, data center, edge, and SaaS, the opportunity for operations teams is clear: when that telemetry is unified and understood in context, it becomes a powerful source of resilience, efficiency, and business insight.
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When we say "Observability AI Reckoning," what are we actually talking about?

Apr 3, 2026 By Virtana In Virtana
We’ve spent the last decade collecting more telemetry. Now AI is analyzing it. Here’s the catch: AI needs the full dependency chain to reason correctly. If it sees spans but not storage contention… Services but not Kubernetes scheduling… Frontend metrics but not downstream providers… It will confidently optimize the wrong thing. AI doesn’t lower the need for observability. It raises the standard.
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