Planet MySQL HA Blog

The Planet MySQL HA Blog aggregates content from sources that cover topics related to high availability (HA) for MySQL databases.

MEM is dead, long live Oracle Database Management

In this post, we will see how to use Oracle DB Management to monitor an on-premise MySQL instance.

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Percona Bug Report: April 2025

| Percona

At Percona, we operate on the premise that full transparency makes a product better. We strive to build the best open-source database products, but also to help you manage any issues that arise in any of the databases that we support. And, in true open-source form, report back on any issues or bugs you might encounter along the way.

We constantly update our bug reports and monitor other boards to ensure we have the latest information, but we wanted to make it a little easier for you to keep track of the most critical ones. This post is a central place to get…

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ClusterControl adds Kubernetes Database Operator management in v2.3.2

| Severalnines

ClusterControl v2.3.2 is here and is taking its first sincere step into the cloud native world with its Kubernetes operator management panelTech Preview and support for PostgreSQL’s cloudnative-pg and MySQL’s MOCO operators. It also comes with new major versions for PG and MySQL, as well as a new metrics watchlist mode for improved situational awareness! […]

The post ClusterControl adds Kubernetes Database Operator management in v2.3.2 appeared first on Severalnines.

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Learn MySQL Performance

| Hack MySQL

Every year new cohorts of programmers, DBAs, managers, and more learn MySQL. After MySQL and HeatWave Summit 2025 a few weeks ago, I realized what job needs to be done for these people and how I could help them make progress: revamping this website to focus on “the path”.

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Creating a Highly Available HeatWave Database System Using Oracle Cloud Shell

In this blog, we will walk through the process of creating a HeatWave HA Database system using Oracle Cloud Shell.

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Oracle Dev Days 2025 – French Edition

| MySQL expert Diary

Join the Oracle Dev Days – French Edition, from May 20 to 22, 2025!
This must-attend event (in French) offers a rich program exploring the latest advancements in AI, databases, cloud, and Java.

Join me on May 21 at 2:00 PM for the day dedicated to “Database & AI.” I’ll be presenting “Building an AI-Powered Search Engine with HeatWave GenAI.” I’ll show you how to go beyond the limits of traditional SQL to harness the power of LLM-driven semantic search.

The post Oracle Dev Days 2025 – French Edition first appeared on dasini.net - Diary of a MySQL expert.

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Improve Primary Selection on Failover in MySQL Group Replication

The latest update to MySQL Enterprise Edition, version 9.3, introduces a significant enhancement focused on improving primary selection on failover. This update includes an improvement to Group Replication primary failover, providing users with a better selection method of a new primary based on the member's most current data. This enhancement results in a seamless experience during failover, maintaining high availability and data integrity.

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Optimize Database Performance with HeatWave's Enhanced Read Operations

Managing read traffic efficiently is crucial for maintaining a high-performing database. With Read Endpoints playing a critical role in directing read traffic, having a flexible, configurable and scalable Read Endpoint solution is a must for ensuring high availability and performance in the DB system, or simplifying application configurations.

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Without Good Data, AI is Useless

When training AI models, it is important to use "good" data. Without good data, the model si pretty much useless. In this post, I share what I learned when trying to train an AI model for use in Episode 89 of MySQL Shorts.

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Anomaly Detection with HeatWave AutoML

Anomaly detection is an effective technique for finding abnormalities in data. HeatWave AutoML offers an automated machine learning pipeline for anomaly detection based on patented algorithm that can detect various types of anomalies and provides better accuracy compared to other anomaly detection techniques. It also supports semi-supervised learning, Principal Component Analysis (PCA) and internally developed technique called Generalized Local Outlier Factor (GLOF).

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