Introduction
A well-structured delivery pipeline ensures that software is shipped smoothly, reliably, and with confidence. Whether you're working in a small team or a large enterprise, having a clear, repeatable process is critical for delivering high-quality software.
This article breaks down a delivery pipeline setup I implemented for a project, optimizing it for small teams. It includes staging best practices, automated deployments, package management, and a ticketing system that simplifies releases.
If you're setting up a CI/CD workflow or refining your software deployment process, this guide is for you! 🚀
🎯 TL;DR
✔️ Always deploy to staging first before production.
✔️ Use nightly builds to test new features early.
✔️ Automate package publishing and CI/CD deployments.
✔️ Keep staging clients on staging APIs to prevent conflicts.
✔️ Use Jira statuses like "Ready for Deploy" to improve workflow.
1️⃣ The Importance of Staging
Why Staging?
Before any new feature or fix goes live, it must be tested in an environment that closely mimics production.
A staging environment serves as a sandbox for QAs and stakeholders to validate changes before they reach real users.
Golden Rule:
Never ship any new code to production if it has not yet been tested and approved for deployment!
But how should the testers access the changes if they exist only on the developer’s local system?
As the testers should act like end-users and not a part of the dev team, they should be able to access the final products in an environment that replicates the live version and includes all the latest changes that are ready to be tested. That is the staging environment.
So, the dev team should always deploy the latest finished changes to the staging environment and ask the QA to test them. Normally, the deployment might include some issues and bugs (which doesn’t mean that the dev shouldn't test everything locally first), which the testers will notice and report.
When the testers and the PO approve the current state of the staging environment, the team prepares for a release on production.
Deployment to Staging
- Developers push their latest changes to staging.
- Testers (QA) validate everything as end-users would.
- Product Owners (POs) approve before release.
- If it’s good, it goes live!
2️⃣ Think of Your Product Like a Pizza 🍕
Your product is like a pizza—it’s made up of different slices (components), and they all need to come together seamlessly when deployed. In most cases it is like a 3-slice pizza in fact:
In this case, a deployment includes:
1️⃣ Packages (code libraries and dependencies)
2️⃣ The Server (backend APIs)
3️⃣ The Client (front-end applications)
Each of these components must be properly staged, tested, and released together for a smooth rollout.
3️⃣ Managing Packages Efficiently
Most modern development relies on package management to handle dependencies. Here’s how to keep it clean:
Staging Packages with Nightly Builds 🌙
When developing a new feature, testers should have access to pre-release versions. A nightly build ensures the latest changes are packaged daily.
📌 How to publish a nightly build:
npm publish --tag nightly
✅ Benefits:
- Allows early testing before an official release.
- Ensures integration issues are caught early.
- Automates packaging, reducing manual effort.
Production packages, on the other hand, should be versioned properly using semantic versioning (semver) for clarity.
4️⃣ Deployment Workflow: From Code to Production 🚀
Note: Remember to set the dependency packages in nightly builds to refer to their nightly versions.
The Server
- Runs in cloud or dedicated server, hosting the backend APIs.
- New code is deployed to staging first before production.
- The CI/CD pipeline automates deployment.
The Client
- Any changes in the front-end must be deployed in sync with the backend.
- If a client instance depends on a new API, it must be tested in staging first before being moved to production.
5️⃣ Streamlining Task Management with Jira 📋
As we want the testers to have something already deployed to Staging for them to start testing and avoid doing it locally, we need to have a new state on for the tickets called “Ready for deploy”.
It would mean the following: “The code was written and reviewed and is ready to be delivered to the testers”.
Old Ticket Flow:
To Do → In Progress → Code Review → Testing → Done
New & Improved Workflow:
✅ To Do → In Progress → Code Review → Ready for Deploy → Testing → Done
After the sprint is finished and all the Done tasks are approved, the PO will identify the features that are ready to be delivered to the customers. For this kind of work, we will have separate deployment tasks that would skip the 3d and 4th steps during realization.
💡 Why this change?
- Before, testers had to wait and guess when developers manually deployed the latest version to staging.
- Now, with "Ready for Deploy", testers know when a feature is available in staging.
- This reduces bottlenecks and improves release efficiency.
🚀 Result: Faster deployments, happier testers, and smoother releases!
6️⃣ Final Steps to a Cleaner Pipeline
To fully optimize the delivery process, these improvements should be implemented:
- [Task Management] Add a "Ready for Deploy" status in Jira.
- [Automation] Improve CI/CD scripts to auto-publish nightly builds.
- [Versioning] Use semantic versioning for clarity in releases.
- [CI/CD Improvements] Automate deployment of server and client to both staging and production.
- [Environment Fix] Ensure all staging clients use staging APIs only.
🚀 By implementing these best practices, small teams can maintain a highly efficient delivery pipeline without unnecessary delays or confusion.
Conclusion: Why This Works for Small Teams 🏆
A structured delivery pipeline isn't just for large teams---it's critical for small teams too!
By automating testing and deployments, keeping environments clearly separated, and simplifying task tracking, you can:
✅ Ship faster
✅ Catch bugs earlier
✅ Reduce deployment stress
If you're setting up a CI/CD process for your team, start with these principles---they will save you a ton of headaches in the long run!
💬 What challenges have you faced with setting up a delivery pipeline? Let's discuss in the comments! 🚀
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