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Day: January 3, 2023

A Review of Prometheus Changes at PromCon

B.C. Gain reports on sessions from PromCon EU 2022:

Prometheus’ installations are now in the hundreds of thousands range with millions of users, Richard (RichiH) Hartmann, director of community at Grafana Labs and a CNCF Technical Advisory Group Observability chair, said during his talk “I don’t have to convince this room that Prometheus is a de facto standard in cloud native metric based monitoring.”

But as Prometheus’ maintainers celebrate its 10-year anniversary, the community’s needs for monitoring Kubernetes are evolving quickly. Users are also becoming smarter about what they want and need. PromCon EU 2022, held in Munich in November, the Prometheus annual user’s conference, served as a forum about how and why Prometheus must evolve and what Prometheus maintainers must do.

Prometheus is a critical part of the modern service monitoring stack; read on to learn more about histogram updates and work at the core which should help Prometheus users along the way.

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Avoid Unnecessary Indexes: Postgres Edition

Laetitia Avrot has some advice:

This is why, when I’m called for a performance problem (or for an audit), my first take is to look at the size of the data compared to the size of the indexes. If you store more indexes than data for a transactional workload, that’s bad. The worst I’ve seen was a database with 12 times more indexes stored on disk than data! Of course, it was a transactional workload… Would you buy a cooking book with 10 pages of recipes and 120 pages of indexes at the end of the book?

The problem with indexes is that each time you write (insert, update, delete), you will have to write to the indexes too! That can become very costly in resources and time.

Click through for some Postgres-specific guidance and links to some useful scripts along the way.

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DAX Window Functions and Power BI DirectQuery

Chris Webb points out another benefit of DAX window functions:

The new DAX window functions (announced here, more details on Jeffrey Wang’s blog here and here) have generated a lot of excitement already – they are extremely powerful. However one important benefit of using them has not been mentioned so far: they can give you much better performance in DirectQuery mode because they make it more likely that aggregations are used. After all, the fastest DirectQuery datasets are the ones that can use aggregations (ideally Import mode aggregations) as much as possible.

As always, Chris has a demo for us, so check it out.

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Running SQL Server on an M2 Processor

Anthony Nocentino operates a Mac:

Last week I purchased a shiny new MacBook Air with an M2 processor. After I got all the standard stuff up and running, I set out to learn how to run SQL Server containers on this new hardware. This post shows you how to run SQL Server on Apple Silicon using colima.

Colima is a container runtime that runs a Linux VM on your Mac. This Linux VM runs using the Virtualization framework hypervisor native in MacOS. Your containers will run inside this virtual machine.

Read on to see what you’d need for the task.

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