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#observability

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Last week I shared 5 "myths" - things CIOs and other IT practitioners believe about #monitoring and #observability that are simply not true.

What were those myths?
1) Monitoring is just an IT operations problem
2) More data equals better visibility
3) Internal metrics tell the full story
4) AI will fix monitoring automatically
5) Downtime is the only metric that matters.

If you'd like to hear more - not just about the myths themselves but also how their history, the modern truth, and how to move past them - then check out the video link below.

youtube.com/watch?v=IIwUHCJIEwA

the state of #observability is deplorable, the landscape fractured and mostly focused on competition, a significant portion of the telemetry emitted useless and overloaded while important stuff is still missing, the tooling itself hard to "observe" and OMG the usability and the ability to automate things EASILY...
this is really one of those "that's it I'm writing my own" moments. it won't even be slower than setting up existing tools properly and squeeze everything into yesterday's concepts.

My obsession with #MCP servers continues. And like many of my obsessions, I love finding ways in which they intersect with other obsessions (hello, #Observability). I decided to leverage the #Dynatrace MCP server to use natural language to query #OpenTelemetry data in Dynatrace. End result? Well, you’ll need to read the blog post!

dt-url.net/dt-mcp-medium

Medium · Querying OpenTelemetry Data with the Dynatrace MCP ServerBy Adriana Villela