Boosting MAAS performance
Unleashing MAAS performance with metrics, improvements, and user insights
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This guide explains how we measure MAAS performance, details recent improvements, and shows you how to track your own metrics.
Slicing and dicing performance data
We've improved MAAS API performance through rigorous testing, using scenarios that include five rack controllers, 48 machines per fabric, five VMs per LXD host, and machines with diverse features. Our testing setup is designed to reflect a range of real-world conditions.
We use continuous performance monitoring to track this variety.
Our daily simulations of 10, 100, and 1000 machines provide detailed insights into scalability. The Jenkins tool tests both the REST and WebSocket APIs, with results stored in a database for analysis through our dashboard.
Comparative testing of stable and development releases helps us identify and fix bugs early. For example, MAAS 3.2 machine listings load 32% faster than in MAAS 3.1 in our tests.
A look back at our performance journey
Our commitment to performance optimization is ongoing. Some highlights include:
- A video overview of recent enhancements.
- Efforts by our UI team to improve the user interface.
These examples represent just a part of our comprehensive performance improvement efforts.
Contribute by tracking your MAAS metrics and sharing them with us. Your input on machine counts, network sizes, and performance experiences is valuable. Join the discussion on our Discourse performance forum.
What's cooking: recent and upcoming enhancements
The MAAS 3.2 update has achieved a 32% speed increase in machine listing through the REST API. We're continuing to work on further enhancements.
Our focus now is on optimizing other MAAS features, including search functionalities.
Join us in this continuous journey of performance enhancement. Your feedback and insights are always welcome.