Automation Consultants

We use Postman for API testing - our products are built with either a REST API, or a GraphQL API and Postman enables us to easily manage our API testing sessions and speed up API development.

We use JUnit and Jest to perform the bulk of our automated test scenarios, with additional work with Apache JMeter for performance testing - for example, the Atlassian Data Center compliance testing is performed with JMeter. Jest provides testing for the React interfaces, which make up the backend of our App offerings. JUnit is used for Unit Testing our Server-based Apps. Mocha is another tool we use.

We use Git, via the AWS CodeCommit application to host our Version Control System (VCS). This utility provides an easy way to manage work being performed on a single repository by multiple developers, through the use of branches. Other features, such as automated merge conflict resolution and commit tagging round out this system.

We use Amazon SES to provide the email services of our Cloud Apps - it provides a robust, stable service that we interface with to provide our customers' with timely notifications on actions - for example - in Approvals for Confluence we email the approvers when their approval is requested.

We currently use Google Analytics in our stack to monitor page views across our Marketplace listings, Documentation site and primary website. We're currently also investigating using Segment to provide in-app analytics in our Cloud App offerings. We expect to use Segment to guide our App development efforts, by monitoring, anonymously which features our clients use the most - but this is in early stages and will involve an update to our privacy policy.

We use Sass to style our React-based App frontends. It allows us to mix CSS and SCSS to provide good-looking interfaces in React, without including the styles in with the application logic.

We use Amazon S3 because it provides a reliable, fast and relatively cheap storage system for storing archived application data and CDN-optimized resources. The Glacier storage classes also allow us to store data for longer periods of time (e.g. logs) with lower costs.

A number of our non-core utilities use Python as their scripting language in order to make use of useful libraries such as Boto3 which provides an interface to AWS. Python is very useful for making small functional scripts.

Node.js powers our Cloud App Servers and performs the server-side logic required to provide useful business operations like those in Approvals for Confluence. Our Node.js Apps are written in TypeScript and use the ExpressJS framework to serve requests, along with other libraries to manage data storage and security. In production these Node.js processes are run in Docker containers, split across multiple Cluster nodes using the Amazon EC2 Container Service.