In the previous post of this series, we looked at the hardware specifications and operating system settings of the host server through the lenses of a pt-summary report. Now that we know the foundation on which the database is running, we can turn our focus to MySQL itself. The second of our triad of tools from the Percona Toolkit will help us with that:

pt-mysql-summary conveniently summarizes the status and configuration of a MySQL database server so that you can learn about it at a glance. 

The goal for this part is to find what MySQL distribution and version is being used if the server …

After Oracle released MySQL version 8.0.24 on April 20, 2021, our engineering team got started right away with merging our enhancements to prepare the corresponding 8.0.24 version of Percona Server for MySQL.

However, Oracle released MySQL version 8.0.25 shortly afterward on May 11, 2021, to fix a critical bug that we also observed during our initial testing and reported back to them.

Therefore, we have decided to skip releasing Percona Server for MySQL 8.0.24 both as a standalone product and a distribution as well as the …

Back in December 2018, when we announced the general availability of Percona Server for MySQL 8.0, we also announced that the TokuDB Storage Engine has been marked as “deprecated” in this release, recommending to use the MyRocks Storage Engine as an alternative. We believe that MyRocks provides similar benefits for the majority of workloads and is better optimized for modern hardware.

Since then, we have continued maintaining the storage engine in the 8.0 release, e.g. by incorporating bug fixes. However, the ongoing amount of …

Percona Server for MySQL 8.0.23-14 was released last week and I wanted to take a minute to call out some of the interesting new features that we have introduced in this release. These are included in addition to the features and improvements in MySQL 8.0.23 that were introduced by the Oracle MySQL team (and to which Percona also contributed).

Hashicorp Vault Plugin Support for KV Secrets Engine – Version 2 (PS-5364)

As of Percona Server for MySQL 8.0.23-14, the Hashicorp Vault plugin can be configured to specifically use either V1 or V2 Secrets Engine API or it can be configured to probe and auto-detect the best version to use.

…

This blog post will show how to compile the Percona XtraBackup (PXB) tool for ARM. For this, we are going to use an AWS EC2 ARM instance with Ubuntu 20.04(Focal Fossa).

The motivation for this was born in my interest in the new generation of ARM processors and if this is a viable option for the future. Ideally, I do not recommend installing all the necessary packages to compile Xtrabackup in a production environment for security reasons. Still, you can have a “compiling” server for this purpose and then move the binaries around.

Machine Configuration

For this blog post, I picked a c6g.2xlarge instance. The machine has the following hardware configuration:

Multi-writer replication has been a challenge in the MySQL ecosystem for years before truly dedicated solutions were introduced – first Galera (and so Percona XtradDB Cluster (PXC)) replication (around 2011), and then Group Replication (first GA in 2016).

Now, with both multi-writer technologies available, do we still need traditional asynchronous replication, set up in active-active topology? Apparently yes, there are still valid use cases. And you may need it not only when for some reason Galera/PXC or GR are not suitable, but also when you actually use them. Of course, the most typical case is to have a second cluster in a different …

Apologies for the silly title, but the issue is a real one, even though it is not a new thing. Schema upgrades are not an ordinary operation in Galera. For the subject at hand, the bottom line is: under the default Total Order Isolation (TOI) method, “the cluster replicates the schema change query as a statement before its execution.” What this means in practice is that a DDL issued in one node is replicated to other nodes in the cluster before it is even executed in the source node, let alone completed successfully.

As a result of this, it may fail in one node and be successful in another, and this without raising loud alerts or stopping nodes to protect against data inconsistency. This is not a bug in itself but rather a compromise of design. With new changes in MySQL and the …

While I was working on my grFailOver POC, I have also done some additional parallel testing. One of them was to see how online DDL is executed inside a Group Replication cluster.

The online DDL feature provides support for instant and in-place table alterations and concurrent DML. Checking the Group Replication (GR) official documentation, I was trying to identify if any limitation exists, but the only thing I have found was this:

“Concurrent DDL versus DML Operations.  Concurrent data definition statements and data manipulation statements executing against the same object but on different servers is not supported when using multi-primary mode. During execution of Data Definition Language (DDL) statements on an object, executing concurrent Data Manipulation Language (DML) on the …

Where x is >= 22

The Problem

There are few things your data does not like. One is water and another is fire. Well, guess what:

If you think that everything will be fine after all, take a look:

Given my ISP had part of its management infrastructure on OVH, they had been impacted by the incident.

As you can see from the highlight, the ticket number in three years changes very little (2k cases) and the date jumps from 2018 to 2021. On top of that, I have to mention I had opened several tickets the month before that disappeared. 

So either my ISP was very lucky and had very few cases in three years and sent all my tickets to /dev/null… or they have lost THREE YEARS of data.   

Let us go straight to the chase; they have lost their …

This blog provides high availability (HA) guidelines using group replication architecture and deployment recommendations in MySQL, based on our best practices.

Every architecture and deployment depends on the customer requirements and application demands for high availability and the estimated level of usage. For example, using high read or high write applications, or both, with a need for 99.999% availability.

Here, we give architecture and deployment recommendations along with a technical overview for a solution that provides a high level of high availability and assumes the usage of high read/write applications (20k or more queries per second).

Layout

Components

This architecture is composed of two main layers:

• Connection and distribution layer
• RDBMS …