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There Is Only One Key Difference Between Observability 1.0 and 2.0

honeycomb.io

In this article, Charity Majors goes over the simple, technical distinction between observability 1.0 and observability 2.0.

13 pages link to this URL
charity.wtf

charity wtf's about technology, databases, startups, engineering management, and whiskey.

0 inbound links website en agentic developmentagentsAI-SREcontextdataobservability 2.0three pillarsaisresreconbookobservability engineeringwritingcrosspostedmartin fowleroperationsopspicking fightssubstackdeploysfriday deploysethicsauf wiedersehnfarewellgoodbyeso longthanks kids <3monitoringrageguyunified storagevendorsbunniesmultiple pillarso11y 2.0help
Agent Observability: Can the Old Playbook Handle the New Game?

As Agentic AI explodes in 2025, traditional observability faces new challenges. Can the three pillars of Metrics, Logs, and Traces handle agent workloads? This article explores how Agent Observability points toward Wide Events and Observability 2.0.

1 inbound link article en observabilityAI AgentWide EventsOpenTelemetry
charity.wtf

charity wtf's about technology, databases, startups, engineering management, and whiskey.

0 inbound links website en agentic developmentagentsAI-SREcontextdataobservability 2.0three pillarsaisresreconbookobservability engineeringwritingcrosspostedmartin fowleroperationsopspicking fightssubstackdeploysfriday deploysethicsauf wiedersehnfarewellgoodbyeso longthanks kids <3monitoringrageguyunified storagevendorsbunniesmultiple pillarso11y 2.0help
Joshua Wood

Joshua Wood’s personal website - software developer, photographer, and Honeybadger.io co-founder. Writing about software, entrepreneurship, and life in the Pacific Northwest.

0 inbound links website en
A Software Observability Roundup

I spent some time recently catching up on my #to-read saves in Obsidian. More than a few of these were blog posts from 2024 about software observability. Talk of "redefining observability", "observability 2.0", and "try Honeycomb" had caught my eye in a few spaces, and so I had been hoarding links on the topic. After spending a few days immersing myself in those articles and branching out to others, I decided to write this bullet-form roundup.

The APM paradox

Application Performance Monitoring (APM) means many things to many people. At its core, it enables developers to diagnose why their applications are slow and helps them provide a better experience to their users. Traditionally, this is accomplished by collecting a lot of data and displaying it in the form of dashboards and request traces. The problems you’re trying to solve are generally known up front.

0 inbound links article en
Observability for Generative AI

Overview of the challenges of observability for LLMs, with comparisons to ML observability challenges.

0 inbound links article en Machine Learning AI 10Machine Learning 7nocourse 3
charity.wtf

charity wtf's about technology, databases, startups, engineering management, and whiskey.

0 inbound links website en agentic developmentagentsAI-SREcontextdataobservability 2.0three pillarsaisresreconbookobservability engineeringwritingcrosspostedmartin fowleroperationsopspicking fightssubstackdeploysfriday deploysethicsauf wiedersehnfarewellgoodbyeso longthanks kids <3monitoringrageguyunified storagevendorsbunniesmultiple pillarso11y 2.0help