All you need is Wide Events, not “Metrics, Logs and Traces”

This week we have observability, tooling, aws lambda architecture and some AI.

Let's get shredding

Nearing the end of our series, Dave Lucia explores observability tools and strategies for Elixir teams in midsize settings, sharing how to boost application monitoring and reliability from startups to Series C/D companies and more!

In this blog post, Charity Majors goes over the reasons it's time to version observability, and what to expect from observability 2.0.

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.

A step by step guide to building a RAG system with Postgres

All you need is Wide Events, not “Metrics, Logs and Traces” … when it comes to the distributed systems at scale what’s more important is an ability to “dig” into data - “slice and dice” it, build and analyse various views, correlate, search for anomalies… And systems that offer all of this do exist. Wide Event is just a collection of fields with names and values, pretty much like a json document.

OpenTelemetry is not perfect, but the value of having one shared standard for instrumentation and telemetry is huge

Originally posted on the Honeycomb blog on November 19th, 2024 We’ve been talking about observability 2.0 a lot lately; what it means for telemetry and instrumentation, its practices and sociotechn…

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

Augh! I am so behind on so much writing, I’m even behind on writing shit that I need to reference in order to write other pieces of writing. Like this one. So we’re just gonna do this quick and dir…

The existing articles on Wide Events define the concept well but leave the implementation details to the reader.

How a Wide Events-Driven Logging Approach Powers Effective, Scalable, and Cost-Efficient ML Observability

Good reads