Percona Monitoring and Management is quickly growing in both functionality and adoption. In this talk, we will discuss how to integrate it with other Database Management Systems, to get the best out of it on environments that not only use MySQL- or MongoDB-based solutions.
We will focus on how to set up monitoring for PostgreSQL and ClickHouse.
The presentation will be a real-life study on how we use PMM for monitoring of 120+ MySQL and ProxySQL-servers, as well as query optimization
We will show how we've been able to deploy PMM on a large scale, with 120+ (and growing) monitored instances, as well as how we're using it to find problems, both system health and performance-wise, sometimes even before impacting the production environment.
During the project, we found a few caveats, that others embarking this journey should be aware of. We've also found a few ?hidden features?, where we're able to use PMM in ways beyond the standard interfaces, due to the fact that it's all built on open and battle-tested software.
While GitHub isn't the biggest database around in terms of the amount of data we hold in MySQL, it is among the top 50 busiest sites on the internet. Facing an immediate need to distribute load, we came up with creative ways to move a significant amount of traffic off of our main MySQL cluster, with no user impact. Moving five of our hottest tables required collaboration between engineers, DBAs and SRE. This talk will describe when and how to do it, and prove it to be an efficient database scalability solution.
Moving tables required changes to our database infrastructure as well as our application. I'll explain the impetus for this work and why we did it. We'll walk through the application-level changes that allowed us to change connections while still serving data. Then, I'll discuss the ways we moved tables to different clusters, using MySQL replication, or in some cases, temporary sharding and copying billions of rows. Finally, I'll outline the orchestration of the actual cutovers.
Time series databases are sprouting up like mushrooms. At Grafana Labs, the company behind Grafana, we built a new engine specifically for GrafanaCloud. Why would we do that? Learn about the design considerations, lessons learned, and tradeoffs we made in designing this engine that is compatible with both Graphite and Prometheus.
Query tuning can be complex. It's often hard to know which knob to turn or button to press to get the biggest performance boost. In this presentation, Janis Griffin, database performance evangelist at SolarWinds, will share her secrets for determining the best approach for tuning queries by utilizing the performance schema (specifically instrumented wait events and thread states), query execution plans, SQL diagramming techniques and more.
Regardless of the complexity of your database or your skill level, this systematic approach will lead you down the correct tuning path with no guessing, saving countless hours of tuning queries and optimizing performance of your MySQL® databases.
? Learn how to effectively use the performance schema to quickly identify bottlenecks and get clues on the best tuning approach
? Quickly identify inefficient operations through review of query execution plans
? Learn how to use SQL diagramming techniques to find the best plan
At Yelp we have a constantly growing polyglot data tier consisting of datastores such as Cassandra, Elasticsearch, MySQL and Zookeeper. These distributed datastores often ask to be treated like pets but can only be reared like cattle given the scale of our systems. Requiring engineers to pamper them individually is neither feasible nor scalable. We need cluster automation which is powerful, resilient and reliable, and more importantly safe. This is where Taskerman steps in.
Taskerman is a distributed cluster task manager, wearing many hats to keep our clusters highly available, consistent, secure and in an optimal condition. Reusability has also been our focus, hence Taskerman has been built on top of AWS and existing open source infrastructures like Yelp PaaSTA, Zookeeper and Sensu.
This talk covers the genesis of Taskerman inside Yelp, its architecture and evolution. Much like the infrastructure it stands on top of, we also hope to open-source Taskerman in the future.
Optimizing MySQL performance and troubleshooting MySQL problems are two of the most critical and challenging tasks for MySQL DBA's. The databases powering your applications need to be able to handle heavy traffic loads while remaining responsive and stable so that you can deliver an excellent user experience. Further, DBA's are also expected to find cost-efficient means of solving these issues.In this presentation, we will discuss how you can optimize and troubleshoot MySQL performance and demonstrate how Percona Monitoring and Management (PMM) enables you to solve these challenges using free and open source software. We will look at specific, common MySQL problems and review the essential components in PMM that allow you to diagnose and resolve them.
In this talk we will review the new functionality released by Amazon Web Services, that allows us to import data from our non-RDS MySQL instances, to RDS instances (MySQL or Aurora). We'll see what works, what doesn't, and how to do it.
Database backup and validation is a trending topic these years. In order to survive from all the possible accidents, Facebook designed and implemented a MySQL backup and validation system for large scale deployment. In this talk, I'll share the implementation detail for this system and the evolution story of it.