Highload++ 2017 завершён!

Профессиональная конференция разработчиков высоконагруженных систем

СКОЛКОВО, Москва 7 и 8 ноября

11-я ежегодная конференция для разработчиков highload-систем, которая соберет   2 700 участников из разных регионов России и мира. Мероприятие направлено на обмен знаниями о технологиях, позволяющих одновременно обслуживать многие тысячи и миллионы пользователей.

Программа охватывает такие аспекты веб-разработок, как архитектуры крупных проектов, базы данных и системы хранения, системное администрирование, нагрузочное тестирование, эксплуатация крупных проектов и другие направления, связанные с высоконагруженными системами.

  • Главная
  • Базы данных и системы хранения

Capacity Planning for your Data Stores
Базы данных и системы хранения

Доклад отклонён
Percona

Colin Charles is the Chief Evangelist at Percona. He was previously on the founding team of MariaDB Server in 2009, and had worked at MySQL since 2005, and been a MySQL user since 2000. Before joining MySQL, he worked actively on the Fedora and OpenOffice.org projects. He's well known within open source communities in APAC, and has spoken at many conferences.

Тезисы

In the objective, I described a ticket sales website that does "normal" events like an M2M concert, but occasionally also sells tickets to the Harry Potter theatre show. This is a perfect capacity planning example because you don't want to be buying servers that aren't doing anything for much of the time. This is also why the cloud is so popular today. While the focus of this talk is not to help you plan for the application server loads and caches, the data layer is definitely a hard one to tackle.

Selling tickets require you to never sell more tickets than you actually have. You want to load balance your queries. You want to shard your data stores. You may want to split reads and writes. You need to determine where the system bottlenecks, so for that you need a baseline and know what regular traffic patterns are.

Beyond that, we will talk about storage capacity planning for OLTP and data warehousing uses.

The general idea here is that from metrics collection, you will be able to plan your requirements. Couple this with the elastic nature of clouds, and you should never have an "error establishing database connection".

Tools covered in this talk include but are not limited to: Box Anemometer, innotop, the slow query log, Percona Toolkit (pt-query-digest), vmstat, Facebook's Prophet, Percona Monitoring & Management (PMM).

Другие доклады секции
Базы данных и системы хранения

Rambler's Top100