Postgres monitoring with USE and RED
Brendan Gregg’s USE (Utilization, Saturation, Errors) method for monitoring is quite known. There’s also Tom Wilkie’s RED (Rate, Errors, Durations) method, which is suggested to be better suited to monitor services than USE. I want to talk about how we employ these methodologies when we develop our Postgres monitoring in okmeter.io.
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Andrei Salnikov Data Egret
Major upgrade for PostgreSQL
In this master class, I will take you step-by step through a major upgrade of PostgreSQL. Through our practice we see a lot of different PostgreSQL servers in production environment and often, almost too often teams who once made PostgreSQL their database of choice never update it following the initial installation. The are many different reasons for it, the result, however, is the same - they all miss out on the new useful features of the newer releases and reduced database performance.
The goal of my masterclass is to equip attendees with necessary tools for performing PostgreSQL upgrade. I will take you through each step of the major upgrade and will dive into each executed command. I will also explain the particular order in which I perform an upgrade and explain the consequences of not following this order or missing a particular step. We will perform an upgrade of PostgreSQL 9.0 to 11. My hope is that following this masterclass number of outdated PostgreSQL database will reduce since participants will then go back to their databases and make sure that they are running the most recent version. -
Nikolay Samokhvalov Nombox LLC
Enterprise-level approach to PostgreSQL tuning: database experiments
Shared_buffers = 25% – is it too much or not enough? Or it's the right value?
How can we ensure that this – pretty much outdated – recommendation suit well our needs?
It is time to start apply enterprise-level approach to tuning postgresql.conf. Not using various blind auto-tuners or advices from old articles and blog posts, but based on the following two aspects:
- comprehensive database experiments, conducted in automated fashion, repeated multiple times in conditions as close to production as possible, and
- deep understanding of DBMS and OS internals.
Using Nancy CLI (https://gitlab.com/postgres.ai/nancy) we will consider a concrete example: infamous shared_buffers, under various circumstances, in various projects. We will try to figure out, how to optimize this settings for given infrastructure, database, and workload.
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Aleksander Pavlov Modulbank
How to break your DBMS with arised-from-nothing high loads?
As any ordinary software developers, we just pursued a goal to develop a system robust for high loads, and even succeeded. The system architecture was fine, but the data volume was keeping increased and revealed the painful issues and errors that nobody had expected. We faced very strange queries seemed to be unbelievable. In my short talk I would like to share sad experience of arised-from-nothing high loads in DBMS and solving the challenge.
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Александр Смолин Красноярский ИВЦ - СП ГВЦ - ОАО "РЖД"
Configuring and profiling VMware virtual infrastructure for PostgreSQL intensive input/output
Virtualization in companies has become an alternative to the conservative "one task-one server" approach, which allows efficient use of hardware resources, centralized management of server infrastructure, saving energy and cooling resources. The report explains how to configure the VMware environment for intensive input / output PostgreSQL and profiling tools virtual infrastructure to monitor performance and resolve identified problems.