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Month: June 2025

Diskless Kafka in Practice

Hugh Evans lays it out:

I joined Aiven as a Developer Advocate in May, shortly after the Kafka Improvement Proposal KIP-1150: Diskless Topics was announced, which is reduces the total cost of ownership of Kafka by up to 80%! It was very exciting to join Aiven just as the streaming team were making this major contribution to open source but I wanted to take my time to understand the KIP before sharing my thoughts.

In this article I’ll share my first impressions of Diskless Kafka, walk you through a simple example you can use to experiment with Diskless, and highlight some of the great resources that are out there for learning about the topic. First though, what actually is Diskless Kafka?

Click through for that answer, as well as more.

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Myths of the DBA-less Cloud

Kevin Hill has a reminder for us:

Here’s a common theme I hear from small IT teams:

“Our SQL Server is in the cloud now. We don’t need a DBA.”

Not quite.

When you’re running SQL Server on cloud virtual machines like Azure SQL VM or AWS EC2, you’re still responsible for a lot of the same challenges you faced on-prem. The difference? Now you’re paying cloud rates for the same headaches. But you don’t have to deal with hardware and some of the other infrastructure hassles.

Read on to see what that entails in practice. Though I’m pretty sure my target audience generally understands this and it’s people two or three levels up who should give Kevin’s post a read.

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Building a Better Trigger

Steve Jones is done with mousetraps:

This seemed to work, but did it really?

The Problem

Let’s illustrate the big problem with this change. I’ll run this code:

Steve hit on one of the problems in trigger design, but there’s another problem that we often see. Steve’s code doesn’t have this problem, but quite often, people assume that rows update one at a time. But if you write a T-SQL UPDATE statement that affects five rows, the trigger fires once for all five. Steve correctly uses the inserted and deleted pseudo-tables to handle all changes, rather than just assuming a single row.

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Thoughts on Multi-Primary Replication in PostgreSQL

Jan Wieremjewicz wants to know if you really need it:

Active-active, also referred to as multi-primary, is a setup where multiple database nodes can accept writes at the same time and propagate those changes to the others. In comparison, regular streaming replication in PostgreSQL allows only one node (the primary) to accept writes. All other nodes (replicas) are read-only and follow changes.

In an active-active setup:

  • There is no single point of write.
  • Applications can write to any node.
  • The database needs a way to sort out conflicts when two nodes try to concurrently change the same data.

Read on for some of the challenges around this, tooling that is available, and thoughts on when this can be important.

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The New Item Creation Experience in Microsoft Fabric

Dan Liu has an announcement:

Have you ever found yourself frustrated by inconsistent item creation? Maybe you’ve struggled to select the right workspace or folder when creating a new item or ended up with a cluttered workspace due to accidental item creation.

We hear you—and we’re excited to introduce the new item creation experience in Fabric! This update is designed to address those pain points head-on. With the new unified creation flow, you’ll have a streamlined way to select the exact workspace and folder where your items belong. More importantly, this improvement brings consistency and cohesion to item creation across all Fabric items, so you can stay organized and productive.

Click through to see what it looks like.

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EchoLeak: Zero-Click Copilot Vulnerability

Alex Woodie reports on a vulnerability:

The Microsoft Copilot vulnerability, dubbed EchoLeak, was listed as CVE-2025-32711 in the NIST’s National Vulnerability Database, which gave the flaw a severity score of 9.3. According to Aim Labs, which discovered EchoLeak and shared its research with the world last week, the “zero-click” flaw could “allow attackers to automatically exfiltrate sensitive and proprietary information from M365 Copilot context, without the user’s awareness, or relying on any specific victim behavior.” Microsoft patched the flaw the following day.

The blog post linked above is pretty interesting. Microsoft has patched the vulnerability, so this particular attack vector shouldn’t be an issue. But it will certainly open up the doors for more fun ways of exploiting generative AI-based services.

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Restoring a Database via dbatools

David Seis digs into the Restore-DbaDatabase cmdlet:

In this blog post, we will audit the dbatools command Restore-DbaDatabase. I will test, review, and evaluate the script based on a series of identical steps. Our goal is to provide insights, warnings, and recommendations to help you use this script effectively and safely. Restore-DbaDatabase is powerful tool to automate the restore of any database, and it works well in automated solutions such as daily refreshes or weekly refreshes of production to a lower environment.

David’s blog post takes a look at the cmdlet’s functionality, but also thinking about it from a security perspective.

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Maintaining Statistics Information Post-Update in PostgreSQL 18

Laurenz Albe takes a peek at an upcoming feature:

Everybody wants good performance. When it comes to the execution of SQL statements, accurate optimizer statistics are key. With the upcoming v18 release, PostgreSQL will preserve the optimizer statistics during an upgrade with dump/restore or pg_upgrade (see commit 1fd1bd8710 and following). With the beta testing season for PostgreSQL v18 opened, it is time to get acquainted with the new feature.

It’s kind of wild to me that this wasn’t in place years ago for PostgreSQL.

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