Fernando Laudares Camargos

Fernando Laudares Camargos

Fernando Laudares Camargos

Senior Support Engineer, Percona


Fernando joined Percona in early 2013 after 8 years working at Révolution Linux as what now is known as a DevOps Engineer role. At Percona he specialized in MySQL and MongoDB. After a brief sabbatical in 2016 to work in a personal project and a short stint at VividCortex he's back at Percona with the added challenge of taking on PostgreSQL support.

All Sessions

High Availability and Automatic Failover in PostgreSQL using Open Source Solutions

PostgreSQL is an advanced open source database that is completely community driven. Continuous development and performance improvements while maintaining a secondary focus on Oracle compatibility gave PostgreSQL a great market penetration. When a database server is deployed in production we often wish to achieve several 9's of availability. Is that even possible with PostgreSQL? What is the combination of tools that you could combine and implement to achieve High Availability (HA) and automatic failover in PostgreSQL? How can we avoid data loss during such failover's? We'll address these questions and then some more in this talk.

Open Source Database Performance Optimization and Monitoring with PMM

This is a hands-on tutorial covers how to set up monitoring for MySQL, MongoDB, and PostgreSQL database servers using the Percona Monitoring and Management (PMM) platform.

PMM is an open-source collection of tools for managing and monitoring MySQL, MongoDB, and PosgreSQL performance. It provides thorough time-based analysis for database servers to ensure that they work as efficiently as possible.

You will learn about:

- MySQL, MongoDB, and PostgreSQL monitoring best practices
- Metrics and time series
- Data collection, management and visualization tools
- Monitoring deployment
- How to use graphs to spot performance issues
- Query analytics for MySQL and MongoDB
- Alerting using Grafana
- Trending and capacity planning
- How to monitor HA

Please bring a laptop with an ssh client as you will be connecting to a Cloud-provisioned instance on which you will deploy PMM.

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