Having a backup of your database is like insurance, you have to pay a monthly price to ensure you have a service available when you need to. When talking about backups, the storage required to keep your backups is what comes into factor when talking about price, the bigger your backup, or the bigger the retention period, the more it will cost.

Compressing your backups is a common practice to reduce this cost. Currently, Percona XtraBackup (PXB) has support for two compression algorithms: quicklz (which is an abandoned project and will soon be deprecated in PXB) and LZ4.

Today we are glad to introduce support for a new compression algorithm in Percona XtraBackup 8.0.30 – …

Every day we use dozens if not hundreds of applications connecting to some kind of data repository. This simple step is normally executed over the network and, given so, it is subject to possible sniffing with all the possible related consequences.

Given that, it is normally better to protect your connection using data encryption like SSL, or at the minimum, make the information you pass to connect less easy to be intercepted.

At the same time, it is a best practice to not store connection credentials in clear text, not even inside a table in your database. Doing that is the equivalent of writing your password on a sticky note on your desk. Not a good idea.

Instead, the main options are either transforming the passwords to be less identifiable via hashing or storing the information in an external centralized vault.

In MySQL, the passwords are transformed to not be clear text, and several different plugins …

MySQL 8.0.31 added INTERSECT and EXCEPT to augment the long-lived UNION operator. That is the good news. The bad news is that you have to be careful using the EXCEPT operator as there is a trick.

Let’s start with some simple tables and load some simple data.

SQL > create table a (id int, nbr int);
Query OK, 0 rows affected (0.0180 sec)
SQL > create table b (id int, nbr int);
Query OK, 0 rows affected (0.0199 sec)
SQL > insert into a (id,nbr) values (1,10),(3,30),(5,50),(7,70);
Query OK, 4 rows affected (0.0076 sec)

Records: 4  Duplicates: 0  Warnings: 0
SQL > insert into b (id,nbr) values (1,10),(2,20),(3,30),(4,40);
Query OK, 4 rows affected (0.0159 sec)

Records: 4  Duplicates: 0  Warnings: 0

So each table has four rows of data with two rows – (1,10) and (3,30) – appearing in both.

SQL > select id,nbr from a;
+----+-----+
| id | nbr |
+----+-----+
|  1 |  10 |
|  3 |  30 |
|  5 |  50 |
|  7 |  70 | …

Not long ago, we found a long-running query in one of our clients on Managed Services. While reviewing this long-running query, we found it was generated by a pt-archiver operation. That doesn’t sound good, right?

I was able to reproduce the issue on my test environment. In this article, I will show you how to use pt-archiver to purge data from a table using a secondary index. First, we need to have the full picture before going any deeper. Here is a representation of the table structure:

Create Table: CREATE TABLE `sbtest1` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `k` int(11) NOT NULL DEFAULT '0',
  `c` char(120) NOT NULL DEFAULT '',
  `pad` char(60) NOT NULL DEFAULT '',
  PRIMARY KEY (`id`),
  KEY `k_1` (`k`)
) ENGINE=InnoDB AUTO_INCREMENT=4000001 DEFAULT …

MySQL is an outstanding database for online transaction processing. With suitable hardware, it is easy to execute more than 1M queries per second and handle tens of thousands of simultaneous connections. Many of the most demanding web applications on the planet are built on MySQL. With capabilities like that, why would MySQL users need anything else?  

Well, analytic queries for starters. Analytic queries answer important business questions like finding the number of unique visitors to a website over time or figuring out how to increase online purchases. They scan large volumes of data and compute aggregates, including sums, averages, and much more complex …

As we have Kubernetes installed in part one (see Using Percona Kubernetes Operators With K3s Part 1: Installation), now we will install Percona Server for MySQL Operator into the running cluster.

I will copy some ideas from Peter’s Minukube tutorial (see Exploring MySQL on Kubernetes with Minkube).

In this case, I will use not Percona XtraDB Cluster Operator but a regular Percona Server for MySQL with Asynchronous replication.

We have recently released version 0.3.0 and it is still in the technical preview state, so we are actively looking for more feedback!

If we go with all …

The microservice architecture is not a new pattern but has become very popular lately for mainly two reasons: cloud computing and containers. That combo helped increase adoption by tackling the two main concerns on every infrastructure: Cost reduction and infrastructure management.

However, all that beauty hides a dark truth:

The hardest part of microservices is the data layer

And that is especially true when it comes to classic relational databases like MySQL. Let’s figure out why that is.

MySQL and the microservice

Following the same two pillars of microservices (cloud computing and containers), what can one do with that in the MySQL space? What do cloud computing and containers bring to the table?

Cloud computing

The magic of the cloud is that it allows you to be cost savvy by letting you easily SCALE UP/SCALE DOWN the size of your instances. No more wasted money on …

We are looking to provide simplified ways to deploy Percona software in cloud environments, especially for more advanced scenarios like replication and multi-node cluster (in the case of Percona XtraDB Cluster).

For this I propose trying out our new Terraform provider, with the capabilities:

• Deploy in AWS or GCP Cloud. The provider will automatically create instances and deploy Percona Server for MySQL
• Deploy either Percona Server for MySQL or Percona XtraDB Cluster
• Choose instance size
• Choose storage volume size, type, and IOPs
• Multi-node async replication or multi-node Percona XtraDB Cluster
• Customize MySQL configuration file
• Capability to deploy MyRocks …

In a post written earlier this year – Percona Server for MySQL Encryption Options and Choices –  I discussed some of the options around encryption in MySQL.  Being such a complex topic, that post was meant to clarify and highlight various aspects of “encryption” at different levels.  I recently had this topic come up again, but specifically around column-level encryption and various options so I wanted to touch on this in more detail.

As of the current release of Percona Server for MySQL, there is no built-in way to define a single column as encrypted.  Ideally, there could be some metadata passed in a create statement and this would just automatically happen, such as this:

CREATE TABLE pii_data ( …

This article outlines the basic configurations for setting up and deploying Percona XtraDB Cluster 8.0 (PXC) on Amazon EC2, as well as what is new in the setup compared to Percona XtraDB Cluster 5.7.

What is Percona XtraDB Cluster an ideal fit for?

Percona XtraDB Cluster is a cost-effective, high-performance clustering solution for mission-critical data. It combines all the improvements, and functionality found in MySQL 8 with Percona Server for MySQL‘s Enterprise features and Percona’s upgraded Galera library.

A Percona XtraDB Cluster environment is an ideal fit for applications requiring 5-9s uptime with high read …