Vitess 15 is now generally available, with a number of new enhancements designed to make Vitess easier to use, more resilient, and easier to scale! VTOrc release # VTOrc, a Vitess-native cluster monitoring and recovery component, is now GA. VTOrc monitors and repairs Vitess clusters, eliminating paging and manual intervention and automating recovery. This makes Vitess fully self-healing and resilient to MySQL server failures. It also obsoletes the third-party integration with Orchestrator that users have traditionally relied on to recover from MySQL server failures.

This week is KubeCon in Detroit, and in preparation for attending I have been polishing up my Kubernetes skills. This big rush to put software in containers and have Kubernetes run everything is getting a lot of push in the industry. Many software applications run perfectly well in ready-made packages from a container made for ephemeral consumption much like a can of Campell’s tomato soup. But generally, relational databases like permanence, stability, and a consistent presence. Databases like to run to stock caches and build statistics, so they are not great at running well after being started. But this article is the first in a series for ‘us’ database folks to learn how to keep our databases happy in a containerized world.

With the trip to the Motor City on my calendar, it was time to answer the question “What is the minimalist …

We’re ecstatic and energised about the prospect of sowing seeds of knowledge in our opensource database community.

Thank you to everyone who joined us for the 17th edition of MyWebinar. We hope that our time together helped to elevate and seam your work to perfection. We’re committed to giving back to the opensource database community in the coming days by presenting more LIVE events.

Maha Lakshmi Ganapathineedi from Mydbops was successful in making this event more interactive, engaging, and, most importantly, productive for the audience. Thank you for your continuous contribution to the opensource community.

Topic: Redo …

New MySQL HeatWave capabilities released in 8.0.31

Whether we’re talking about music, movies, or other digital services, real-time access has become an expectation for most of us, something we take for granted, and we easily get irritated when that expectation can’t be fulfilled. Yet, real-time analysis of marketing/advertising campaign performance is far from being a given for too many marketers. While they […]

Many companies and digital marketing agencies want to aggregate data from various sources in real-time to build rich, highly segmented customer profiles to send the right offer to the right prospect, via the right channel, at the right time—and are struggling. MySQL HeatWave helps solve this problem.

Writing a weekly newsletter is hard, dedicated work. But, I enjoy reading each week’s edition myself and I hope you do as well. OpenLampTech issue #49 is ready for you. Enjoy this week’s content!

The Newsletter for PHP and MySQL Developers

Receive a copy of my ebook, “10 MySQL Tips For Everyone”, absolutely free when you subscribe to the OpenLampTech newsletter.

In OpenLampTech issue #49, we have content covering:

• Laravel Eloquent tips
• 13 Linux distros from scratch
• Improve your WordPress site’s performance
• Most popular databases for PHP
• And much much more

A free weekly subscription helps support the …

With MySQL Cluster you can now from version 8.0.31 use transparent data encryption (TDE). Together with the encrypted backup feature it encrypts all data persisted on disk for tables that uses the Ndb storage engine in MySQL. This complements other already existing features that encrypts data at rest in MySQL.

TDE encryption uses XTS-AES and is transparent to applications accessing the data via MySQL or directly using the C++ NdbAPI. The same application can run unmodified whether …

With the latest MySQL release (8.0.31), MySQL adds support for the SQL standard INTERSECT and EXCEPT table operators.

Let’s have a look how to use them.

We will use the following table:

CREATE TABLE `new` (
  `id` int NOT NULL AUTO_INCREMENT,
  `name` varchar(20) DEFAULT NULL,
  `tacos` int DEFAULT NULL,
  `sushis` int DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB

For our team meeting, we will order tacos and sushi’s.

Each record represent the order of each team member:

select * from new;
+----+-------------+-------+--------+
| id | name        | tacos | sushis | …

I continue to dig up and share this simple approach for production data masking via SQL to create testing data sets. Time to codify it into a post.

Rather than generating a set of names and data from tools such as Mockaroo, it is more practical to use actual data for a variety of testing reasons.

The SQL below is a self-explanatory approach of removing Personal Identifiable Information (PII), but keeping data relevant. I use this approach for a number of reasons.

• We are using production data rather than synthetic data. Data volume, distribution, and additional column values are realistic. This is a subset of an example, but dates and locations are therefore realistic
• Indexes (and unique indexes) still work, and distribution across the index is adequate for searching. Technically the index …