Shipping Resilient And Scalable Applications With Node.js And Artillery
Description
In this talk, we will learn about load testing and how to load test APIs, microservices and production applications (yup!) with Artillery and Node.js
Artillery is a modern open-source alternative to traditional load-testing tools such as JMeter with a strong focus on developer experience. (It is written in Node.js, naturally.)
Learning objectives
How do we make sure that our systems are performant and resilient? For example, how do we make sure that our e-commerce application can handle Black Friday traffic, or that our IoT service's data collection API can scale up to deal with tens of thousands of messages per second periodically? How do we make sure that new code does not introduce a memory leak that will result in you getting paged at 10pm on a Friday night?
Load testing done right can help you deal with all of those problems.
We will cover the fundamentals of performance testing (open vs close models, various ways to model the load on a system), we'll look the difference between benchmarking webservers and testing applications, we'll learn about what capacity testing, scalability testing and stress testing are and how they differ, and most importantly we will learn how to develop realistic load-testing scripts based on dissecting and analysing the system under test and using historical data from Google Analytics, New Relic, DataDog etc.
Title
Shipping Resilient And Scalable Applications With Node.js And Artillery
Description
In this talk, we will learn about load testing and how to load test APIs, microservices and production applications (yup!) with Artillery and Node.js
Artillery is a modern open-source alternative to traditional load-testing tools such as JMeter with a strong focus on developer experience. (It is written in Node.js, naturally.)
Learning objectives
How do we make sure that our systems are performant and resilient? For example, how do we make sure that our e-commerce application can handle Black Friday traffic, or that our IoT service's data collection API can scale up to deal with tens of thousands of messages per second periodically? How do we make sure that new code does not introduce a memory leak that will result in you getting paged at 10pm on a Friday night?
Load testing done right can help you deal with all of those problems.
We will cover the fundamentals of performance testing (open vs close models, various ways to model the load on a system), we'll look the difference between benchmarking webservers and testing applications, we'll learn about what capacity testing, scalability testing and stress testing are and how they differ, and most importantly we will learn how to develop realistic load-testing scripts based on dissecting and analysing the system under test and using historical data from Google Analytics, New Relic, DataDog etc.
City of residence
London 🎩