Platform

Developers

Resources

Pricing

Release Cycles

A release cycle, also known as a software or product release cycle, is the process by which a software product goes from initial concept to being available for use. It involves several stages, including planning, development, testing, and deployment.

Stages of a Release Cycle

1. Planning

This is the initial stage where the team identifies the features and improvements to be included in the new release. It involves gathering requirements, setting goals, and creating a roadmap.

2. Development

In this stage, the software engineers start coding the features and improvements identified in the planning stage. This stage also includes unit testing to ensure each piece of code works as expected.

3. Testing

Once the development stage is complete, the software undergoes various types of testing, such as integration testing, system testing, and user acceptance testing. The goal is to identify and fix any bugs or issues before the software is released.

4. Deployment

After testing, the software is ready to be deployed. This involves packaging the software and making it available for users to download and install.

Best Practices for Release Management

Effective release management helps teams and companies deploy software safely at scale. Here are some best practices:

  1. Document Releases: Knowing what was released and when it was released can help diagnose if a release is the cause of an improvement or regression in a product metric, performance monitor, or other indicators.

  2. Communicate with the Team: People need to know when a new release is happening. This can be as simple as an automated bot message letting people know which release is going out, what phase it's in, etc.

  3. Stage Release Rollouts: Rather than rollout out from 0-100, release your new version in stages. This helps bound the impact of a new release and identify issues before they arise more broadly.

  4. Monitor, Monitor, Monitor: If you do all of the above, but have no diagnostics or monitoring, you are flying blind. Monitoring helps catch issues at the early stages of rollout.

  5. Automate Releases (and Everything: Automation can help reduce the opportunities for error in any release process. This can include automatically generating release candidates, posting when a release is happening, following a staged rollout plan, running tests on releases before they go out, and monitoring metric regressions.

Example of a Release Cycle

An example of a release cycle can be seen in the way Facebook stages its releases. They start by releasing the new version to employees, then to 2% of production traffic, and finally to 100% of production. Monitoring is applied at each step to catch any potential issues early.

Join the #1 Community for Product Experimentation

Connect with like-minded product leaders, data scientists, and engineers to share the latest in product experimentation.

Try Statsig Today

Get started for free. Add your whole team!

What builders love about us

OpenAI OpenAI
Brex Brex
Notion Notion
SoundCloud SoundCloud
Ancestry Ancestry
At OpenAI, we want to iterate as fast as possible. Statsig enables us to grow, scale, and learn efficiently. Integrating experimentation with product analytics and feature flagging has been crucial for quickly understanding and addressing our users' top priorities.
OpenAI
Dave Cummings
Engineering Manager, ChatGPT
Brex's mission is to help businesses move fast. Statsig is now helping our engineers move fast. It has been a game changer to automate the manual lift typical to running experiments and has helped product teams ship the right features to their users quickly.
Brex
Karandeep Anand
President
At Notion, we're continuously learning what our users value and want every team to run experiments to learn more. It’s also critical to maintain speed as a habit. Statsig's experimentation platform enables both this speed and learning for us.
Notion
Mengying Li
Data Science Manager
We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one, including everything from the stats engine to data ingestion.
SoundCloud
Don Browning
SVP, Data & Platform Engineering
We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig.
Ancestry
Partha Sarathi
Director of Engineering
We use cookies to ensure you get the best experience on our website.
Privacy Policy