People approach Continuent for many reasons, including:
Even though Percona Monitoring and Management 2 (PMM) comes with a lot of dashboards and metrics out of the box, sometimes we need to extend the default metrics by running custom MySQL queries.
For example, suppose you want to have information about cached indexes from Innodb tables from innodb_cached_indexes table. That metric is not being captured by any default dashboard, but it is possible to extend PMM and make it capture the result of custom queries.
Getting Started With Custom Queries
Custom queries can be added to mysqld_exporter by adding them to the appropriate config file in /usr/local/percona/pmm2/collectors/custom-queries/mysql. There are three subdirectories inside it: high-resolution, low-resolution, and medium-resolution. PMM allows …
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The Southeast Linuxfest will be virtual this year and I am happy
to announce that I have two sessions.
Friday, June 12th
(All times US EDT, GMT-4. Time between talks is used for
Q&A, discussion, wanton displays of old hardware and boxed
Linux software hoarding, and breaks.)
6:00 - 7:00 PM: Dave Stokes - MySQL JSON Document
Validation
JSON is a popular data interchange format and MySQL has had a
native JSON Data Type for a few years. But until recently
there was no way to make sure JSON data included required fields,
data type checking, or range checking. But thanks to the
JSON-Schema.org's designs, there is now a way to ensure that the
JSON data going into your MySQL Database is correct. You
will learn how to use constraint checks with the new JSON
validation …
Quarkus is a supersonic Java framework built with a cloud-native first mentality. It’s blazing fast in startup and has a much smaller memory footprint compared to Spring Boot. Quarkus is [...]
The post Use MySQL in Quarkus with Hibernate and Panache appeared first on Geeky Hacker.
Our latest Solution Brief uses our relationship with Patreon to detail the ways that Percona services work together to provide customers with a complete database infrastructure solution.
Last year Patreon enlisted Percona’s help with their MySQL databases. Utilizing the full range of Percona Services (Managed Services, Support, Consulting, and Training) has allowed Patreon to make the most of their database infrastructure.
Percona worked with …
[Read more]These days databases spanning across multiple clouds are quite common. They promise high availability and possibility to easily implement disaster recovery procedures. They are also a method to avoid vendor lock-in: if you design your database environment so it can operate across multiple cloud providers, most likely you are not tied to features and implementations specific to one particular provider. This makes it easier for you to add another infrastructure provider to your environment, be it another cloud or on-prem setup. Such flexibility is very important given there is fierce competition between cloud providers and migrating from one to another might be quite feasible if it would be backed by reducing expenses.
Spanning your infrastructure across multiple datacenters (from the same provider or not, it doesn’t really matter) brings serious issues to solve. How can one design the entire infrastructure in a way that the data will be …
[Read more]Three weeks ago, I released the Pluto Beta of Planet for the MySQL Community. Since then, a few things changed and I think it is worth doing an update to the Ecosystem. The change I am the most happy about is that Ivan Groenewold started helping with the project (you can find him in the people of the oursqlcommunity.org GitHub organization). So Planet for the MySQL Community is
Data SRE – Building Database Systems Infrastructure Operations for Performance and Reliability
Recently ( on Friday, 5 June 2020 – 06:00 PM PDT to 06:45 PM PDT ) our Founder and Principal ( Shiv Iyer ) did a webinar on building Database Systems Infrastructure Operations for Performance and Reliability. In this webinar, he discussed about capacity planning / sizing, observability & resilience, performance audit / health-check / diagnostics / forensics, performance optimization & tuning and building highly available / fault-tolerant / self-healing systems architecture. You can download the PDF of the webinar here . Thanks for joining the webinar and making it a success, Looking forward to seeing you all in the next webinar.
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A common MySQL strategy to perform updates with accumulating
functions is to employ user-defined variables, using the
UPDATE [...] SET mycol = (@myvar := EXPRESSION(@myvar,
mycol)) pattern.
This pattern though doesn’t play well with the optimizer (leading to non-deterministic behavior), so it has been deprecated. This left a sort of void, since the (relatively) sophisticated logic is now harder to reproduce, at least with the same simplicity.
In this article, I’ll have a look at two ways to apply such logic: using, canonically, window functions, and, a bit more creatively, using recursive CTEs.
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Backup of Database is the pillar of our system which is necessary
and mandatory to provide us data incase of crash, new machine
provisioning and many other scenarios listed here.
As part of the backup process, a snapshot is taken, and the data
is transferred to the Recovery Services vault with no impact on
production workloads. The snapshot provides different levels of
consistency, as described below:1. Application-consistent:
App-consistent backups capture memory content and pending I/O
operations. App-consistent snapshots use a VSS writer (or
pre/post scripts for Linux) to ensure the consistency of the app
data before a backup occurs.When you're recovering a VM with an
app-consistent snapshot, the VM boots up. There's no data
corruption or loss. The apps start in a consistent state.2.
File-system consistent: File-system consistent backups
provide consistency …
