How to Choose the Right Software Deployment Method!

Software Deployment

The modern software development landscape is fast-paced; users expect to get their hands on applications quickly and reliably. Choosing the right software deployment method is essential for leaving users satisfied.

Traditionally, software deployment involves installing applications on physical servers within native data centres. However, the introduction of cloud computing has introduced new deployment models providing more scalability, flexibility, and cost-effectiveness.

Below, we look at different software deployment methods to help you make the right decision.

Understanding Your Needs

There are several deployment methods to choose from, but it’s important to understand your needs before getting your head around them. Here are some key considerations:

  • Deployment frequency. How often will you need to deploy software updates? Frequent deployments are best suited to automated and streamlined approaches like continuous integration/continuous deployment (CI/CD).
  • Application complication. Do you have a simple web application or a complex microservice architecture? More complex software also benefits from CI/CD to reduce errors and achieve optimal iteration. 
  • Containerisation. Are you leveraging containerised applications? If so, containerised orchestration platforms like Kubernetes can automate container deployment and management across a multitude of machines to provide scalability, security, and speed. 
  • Scalability requirements. Do you need to scale your application based on user demand? 
  • Downtime tolerance. Can your software cope with downtime? Remember, downtime can affect user trust.

A Breakdown of Deployment Methods

Understanding deployment requirements is the first part of the puzzle. Now it’s time to dissect different approaches to software deployment. This defines how you will deliver new versions of software to end-users. 

Manual Deployment

The traditional software deployment method involves manually performing updates onsite. While this approach offers superb flexibility and control, it’s resource-heavy and more susceptible to errors.

Additionally, manual deployment doesn’t work well with software demanding scalability and frequent updates.

Automated Deployment

Automated deployment utilises scripts and tools to automate the deployment process. Scripts are responsible for handling a range of tasks including configuring servers, transferring files, and restarting services. 

If you’re working with a containerised application, you can even harness the power of managed kubernetes services delivered by cloud providers. These services help software cope with cluster management and underlying infrastructure, which frees up developers to focus on containerised deployment.

Continuous Integration/Continuous Delivery Pipeline

The CI/CD approach to software deployment brings together deployment, testing, and other relevant deployment tasks into a continuous flow. When the code changes, it triggers automated builds, tests, and deployments, making for rapid delivery of new features with very little human intervention. 

Choosing the Right Deployment Strategy

Deployment methods refer to the overall approach to delivering new updates, but the deployment strategy refers to how traffic is transferred from old versions to new versions within the chosen method. The strategy you choose will largely depend on risk tolerance and software characteristics. 

Big Bang Deployment

Big Bang deployment is the simplest strategy. It involves updating the entire software and replacing the old version with the new one on every server. This strategy is beneficial because it’s quick and straightforward.

However, it comes with significant risks of total downtime during deployment. Big Bang is best used for basic software where downtime isn’t too much of an issue. 

Phased Deployment

This strategy involves rolling updates out to different server clusters or groups of users gradually. The benefit of Phased Deployment is a controlled rollout and minimal disruption because only a small number of users would experience potential downtime.

If your software is complex and downtime isn’t an option, this strategy will fulfil your requirements. 

Pilot Deployment

The Pilot Deployment strategy involves rolling out updates to a very limited set of users and servers first. Doing this gives developers the time to identify bugs in a controlled environment. If the pilot’s results are successful, the update is then rolled out to the entire user base.

This strategy offers fantastic risk reduction, which can help to establish authority and trust. 

Blue/Green Deployment

The Blue/Green Deployment strategy involves two different production environments: “Blue” to run the current version and “Green” to run the new version. When the Green environment has been fully tested, traffic is transferred from Blue to Green without any issues.

If your application must be available 100% of the time, the Blue/Green Deployment will help with this. 

Canary Deployment

The Canary Deployment strategy is similar to Pilot Deployment because it involves rolling out new updates to small amounts of production traffic. This approach allows for real-world monitoring and testing before rolling out the update to the entire user base. It is ideal for minimising risks and identifying issues. 

Best Practices and Automation

Choosing the correct deployment strategy and method is the scaffolding, but implementing the best practices and automation will greatly improve the deployment process. These are some of the key areas to focus on:

  • Testing. Integrate extensive testing into the entire development lifecycle including unit, integration, and end-to-end testing. Doing this ensures the new version functions as expected. 
  • Version control.  Keep a clear version history of your software’s source code using a version control system like Git. This lets you roll back at any time if issues arise, and it also encourages more effective collaboration. 
  • Monitoring. Continuous software performance monitoring including uptime, resource utilisation, and response times helps to identify and resolve issues swiftly. 
  • Communication. Keep stakeholders informed at each step of the deployment process. Set up clear communication and ensure 100% transparency. 

Automation tools and scripts are also important for modern software deployment because they save time, reduce errors, and decrease spending. Here are some specific ways automation can help:

  • Infrastructure as Code (IaC). Tools like Ansible and Terraform allow you to define your infrastructure configuring, which allows for automated environment management. 
  • Deployment scripts. Creating scripts to automate server configuration, file transfers, and server restarts promotes consistency and minimises human error. 
  • Automated build and testing.  Compiling code, generating deployment packages, and running tests can all be automated to reduce resources.

Choosing the right software deployment strategy and method involves carefully analysing your software’s needs. By understanding complexity, rollout speed, and risk tolerance, you can choose an approach that ensures seamless transitions to new software versions. 

Article and permission to publish here provided by Sara Edwards. Originally written for Supply Chain Game Changer and published on April 23, 2024.

Cover image by Innova Labs from Pixabay.

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