Testing changes in a full-stack pre production environment prevents integration issues in production 

Icon_Reduce FailuresLegacy Testing Processes Slow Down Innovation

In today’s development process there is no place for developers to quickly and easily test code changes against production-ready services. And, there is no efficient way for devs to share software development changes with other teams who need to review and validate bug fixes and new code and changed code prior to merging to the production environment.


icon-thumbsup"Works on my machine" becomes a thing of the past...

“Works on my machine: an application that works great on a developer’s laptop but is completely non-functional in production.”

It is hard to believe, that with some many innovations in technology, that developers are still testing code changes against static and stale staging sites. A staged site simply can’t provide access to the latest versions of upstream and downstream dependencies and because of this, the issue with “works on my machine” perpetuates. 

icon-rocketshipEphemeral pre-production environments solve testing issues from legacy traditional software tools

Roost.ai provides developers with a full-stack pre-production environment that automatically tests changes against the code repository using existing test frameworks. The DevOps platform ensures development processes are: fast, accurate, shareable, scalable, managed, and easy to reproduce at every step:

Removes bottlenecks waiting for testing

Lowers cost of managing and maintaining Kubernetes clusters and ecosystems 

Faster turn-times for product features 


Roost's proprietary technology ensures that all code changes made will not only “work on my machine” but also works with the rest of the dependent services and, most importantly, every step of the way to the production environment.



pre prod environment

SVG-How it Works Full-093022

Roost.ai provides developers with an ephemeral
pre-production environment that automatically test code changes using existing workflows.

Meet Rishi Yadav, Roost's Co-Founder and CEO. In this one-minute video he shares the three steps that Roost takes to understanding complex development environments.

Here are some frequently asked questions that help you understand preproduction environments.

What is a pre production environment?
A pre-production environment where your development and software engineering team builds and tests software for web applications. Your pre-production environments will likely include: one or more development environments where your developers can build, test, and experiment with new software.
Why should I test in a pre-production environment instead of production?

The only way to ensure your pull request (PR)  is 100% accurate and ready to merge into production is to test the PR in a pre production environment that mirrors the entire application. Hand crafting these environments for every PR would be impossible and at the end of the day they are still just static. An ephemeral pre-production test environment, by design, is dynamic and runs “test cases'' automatically and “learns” from system behavior so it can run dependency tests in a much faster and more efficient way. When a PR is merged (or a change moves to the next step) it’s already validated and ready to be merged to the production environment.

Why do we need a pre-production environment?

An ephemeral pre-production environment allows all service changes to be tested and certified by developers thus the traditional CI phase is not needed anymore. Furthermore, once these changes go to production, the chances of failure are close to none.

By eliminating the need for traditional CI, and left-shifting the battle-hardening of services and applications into the hands of developers, releases can be accelerated by at least 60%.


How do automated tests in a pre-production environment work?

Here are five steps that Roost.ai takes to automatically test code changes in a pre-production environment:

1. Discovers pre-production configuration by continuously scanning code repositories.

2. Connect to your service repos, define your build/deploy/test configs

3. On creation of a pull request a test an ephemeral environment is automatically launched

4. Automatically test your pull request or code changes using existing workflows

5. Continuously learn about your environment and service dependencies (e.g. next cycle, test only dependent services, etc.)

6. Takes a snapshot of the change (sharable preview URL) for approval/validation/replay

How do I create an ephemeral pre-production environment?

The Roost.ai platform automatically creates a pre-production environment based upon a pull request or code change. Roost's proprietary  software automatically builds and tests the pre-production environment with necessary service dependencies which are auto-discovered as each application is run. The platform’s AI-enabled discovery service keeps updating service dependencies in a real-time way so that your application always gets the latest working environment.


What is the difference between a development environment and a staging environment?

A development environment is where engineers work to build, refine and debug software. It is usually done on a local computer and does not affect production. 

The staging environment is where software code is deployed to test against a production-like environment to ensure it works properly against upstream and downstream services. It is where code is reviewed by stakeholders and Q/A teams to ensure it is accurate and performs correctly prior to being released to production. 

Why are test environments and staging environments important? And, why must they be dynamic?

In order to ensure code changes, bug fixes, or feature enhancements perform correctly when released to production they have to be tested against a dynamic pre-production environment that is an exact replica of production. The problem lies with the fact that a traditional static test environment allows developers to perform only basic testing and validation of code because they can not for efficient testing to occur when dealing with modern complex architectures such as containers, micro services and cloud-native applications.Using an ephemeral pre-production environment solves these issues because they are dynamic in nature and tests can be run in parallel using the latest microservices to run tests.