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Category: Learning

Learning the Basics of Kafka via Notebook

Francesco Tisiot shares a way to learn about the basics of Apache Kafka using Jupyter notebooks:

One of the best ways to learn a new technology is to try it within an assisted environment that anybody can replicate and get working within few minutes. Notebooks represent an excellence in this field by allowing people to share and use pre-built content which includes written descriptions, media and executable code in a single page.

This blog post aims to teach you the basics of Apache Kafka Producers and Consumers through building an interactive notebook in Python. If you want to browse a full ready-made solution instead, check out our dedicated github repository.

The classic tutorials tend to use a couple command prompts and the built-in producer and consumer shell scripts. I like this approach as a way of being able to review the code and results later as a refresher.

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Service Endpoints in Azure SQL Database

Mike Wood takes us through service endpoints in Azure:

In previous installments of my “Securing Azure SQL Database” series, I covered Azure SQL Database firewall rules and private endpoints—the first of which is a way to help reduce the public exposure of your database endpoint and the second being a means to remove all public access if necessary. Each option has unique benefits, and some scenarios might call for a mix of the two options.

In this blog post, I’ll cover a third option for securing Azure SQL Database—service endpoints. This option is similar to private endpoints in that you restrict public access and only grant access to the database through your Virtual Network (VNet).

Read on to learn more.

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Getting Good Feedback

Cole Nussbaumer Knaflic explains how to get feedback:

We recently kicked off a new 10-week course, which has been really fun to develop, because it’s both longer than our typical workshops and spread out over a greater amount time. Combining these aspects means that we get to cover more topics related to data storytelling and go into greater depth on each. We kicked things off with a focus on feedback, due to the important role this will play throughout the course, and the critical role it plays in our skill development and efforts to communicate effectively with data in general.

There’s some good advice in here.

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An Important Vocabulary Lesson

Taiob Ali shares some commonly mistaken terms:

A list of items that people often get wrong. If you have a suggestion, let me know, and I will add them to this page.

On-premises and braces are the two I hear people get wrong the most. I had been afraid that the recognition of “braces” as the proper term had been so lost that I was like a monk in 9th century Ireland transcribing illuminations of worn tomes here.

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Understanding Interpolation

Joe Celko offers up some thoughts on interpolation:

Interpolation is a mathematical technique which was popular before we had a lot of cheap computing power. The basic idea is that if you’re given a set of data and looking for a value in the same range, you can interpolate it to get a reasonable estimation for the value that is not actually in the set.

If you can find an old calculus, finance, statistics or algebra book, they had lookup tables in the back. Remember that the only computational tools students had back then were pencil and paper or a slide ruler. If you wanted to use a pencil and paper, you had to know what formula to use. If you use the slide ruler, you can only have three decimal places in your answer (yes, there were a couple of over-sized specialized slide rulers which could go as high as four or five decimal places. They were very expensive). But if your slide ruler didn’t have a particular function you were trying to compute, it was hard to get even the three decimal places.

When you try to approximate a value outside the range of your set, that’s called extrapolation. It’s a different topic and requires a slight leap of faith.

Interpolation is a key part of regression techniques. Read the whole thing.

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Eight Fallacies of Distributed Computing

Kevin Sookocheff dives into things people tend to forget when building distributed computing solutions:

If we continue to develop microservices using the same set of assumptions we used for a monolith, we are operating with a now false set of assumptions that can prevent us from being successful. Even in a small distributed system with just two microservices we need to deal with networked communication that can turn our usual mental model of application development on its head. A common set of rules that can help us update our mental model to be more accurate in a distributed environment is the Eight Fallacies of Distributed Computing commonly attributed to Peter Deutsch, an engineer at Sun microsystems who worked on early versions of Ghostscript, as well as interpreters for Smalltalk and Lisp.

Click through for more information on each of the eight fallacies and what you can do to avoid their resulting pitfalls.

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PASS Under New Ownership

Steve Jones announces that Redgate is the captain now:

Redgate Software confirmed today that it has acquired the assets of the Professional Association for SQL Server (PASS), which ended operations on January 15, and will revive the Summit, continue SQLSaturdays, and make available the library of content and training sessions.

Note that this will be different from PASS as it existed, so membership in the old association doesn’t carry over to the new. If you’re interested in keeping up to date on this, check out https://www.red-gate.com/PASS.

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Rule 42 Software

John Mount describes a software development anti-pattern:

As software changes, it often accretes feature and drifts away from its design, if it even started with one, and many defaults and settings become undesirable. New users are blamed for not moving parameter settings away from the defaults to the “obvious” acceptable values.

Click through for the origin of the name and more info on how to avoid it.

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