Application deployment: definition, process and more

Application deployment is the process of making a software application available to users by installing and configuring it on servers or cloud platforms. It focuses on releasing new or updating existing software with minimal disruption and optimal performance for a smooth user experience.

Application deployment offers several key advantages that enhance the efficiency of software applications.

• Consistency and reliability - deployment processes make sure that the application is consistently and reliably set up across different environments (development, testing, production). This reduces the chance of discrepancies and bugs, making it easier to identify and fix issues.
• Security - regular and controlled deployments can include security updates helping to protect the application and its users from vulnerabilities.

• Rollback and recovery - well-designed deployment processes often include rollback mechanisms, allowing you to quickly revert to a previous version if complications arise.

Let’s look at the application deployment process briefly:

Building phase

At this stage, the application's code is compiled and changed into a format that can be used. For example, in a Java application, the source code is compiled into bytecode and packaged into a JAR or WAR file.

Testing

The application is tested in a staging environment that replicates the launch environment. Testing in this environment helps to identify and fix any bugs or issues that might not have been apparent during development. It includes various types of testing such as unit testing, integration testing and system testing‌.

Deployment

The tested and approved application is then deployed to the production environment, often using automated tools like Jenkins, Kubernetes or AWS CodeDeploy. These tools help the application in getting installed and configured and maintain consistency along with reducing the risk of human error.

Monitoring and validation

Post-deployment, the application is closely monitored to check if it's running smoothly and to detect any issues that may arise. Also, continuous validation is performed to confirm that the application meets all performance and reliability standards, and is functioning as expected.

Application deployment strategies are methods used to release new versions of an application to production. Here are some common deployment strategies:

Big Bang deployment

In a Big Bang deployment, the entire application is replaced with the new version all at once. This approach is straightforward but risky, as any issue can cause significant downtime and affect all users.

Blue-Green deployment

Blue-Green deployment involves running 2 identical production environments, one active (blue) and one inactive (green). The new version is deployed to the inactive environment, and once verified, traffic is switched to the new environment. This minimises downtime and allows for easy rollbacks.

Canary deployment

Canary deployment gradually rolls out the new version to a small subset of users. This helps monitor the performance and stability of the new version before a full rollout, reducing the risk of widespread issues.

Rolling deployment

Rolling deployment updates the application in stages. It gradually replaces the old version with the new one. This approach makes the application remain available during the update process and can be paused if bugs arise.

A/B Testing

A/B testing involves deploying both the old and new versions of the application simultaneously and routing a portion of users to each version. This allows for direct comparison of user experiences and performance metrics between the 2 versions.

Here are some common challenges you might face during app deployment, along with ‌possible mitigation techniques.

Unexpected bugs

Bugs that aren't fixed during testing can cause problems when the software is deployed or after it's been installed. Therefore, its always important to implement comprehensive automated testing and code review processes to catch bugs early.

Compatibility issues

To make an application work across different environments and devices might be challenging. So, you can use containerisation tools like Docker and conduct thorough cross-environment testing.

Performance dissatisfaction

Poor software performance can lead to user dissatisfaction and system instability. So, before deploying an application, you can optimise code and use performance monitoring tools to identify and address software limitations.

Security vulnerabilities

Deploying insecure code can expose the application to malfunctions and attacks. So, you must integrate security testing into the deployment procedures with the help of automated security scanning tools.

Here’s a list of things you must check to make the deployment process smooth and successful.

Pre-deployment preparation

• Check the code carefully to make sure the new application version is good and safe
• Perform unit, integration‌ and system testing to verify that the application works as expected
• Create a backup of the current production environment and data to facilitate quick recovery if needed

Deployment planning

• Plan the deployment time to minimise impact on users, typically during low-traffic periods
• Make a detailed plan to roll back if the deployment fails or problems are found
• Inform stakeholders and users about the deployment schedule and any expected issues that might arise
• Check that the correct version of the application is being deployed

Deployment

• Automate the configuration of the production environment to match the required settings

• Document any manual configuration steps that need to be performed
• If required, perform data migration or synchronisation to the new version
• Manually restart services if automated scripts aren't enough.

Post-deployment verification

• Run simple tests to monitor if the application meets the expected standards
• Configure alerts to inform the team of any critical issues which might surface

Rollback and recovery

• If issues are detected, execute the rollback plan to revert to the previous version
• Verify that recovery plans are in place and can be executed if needed

Documentation and communication

• Make and share release notes that explain the changes and improvements in the new version
• Conduct a post-deployment review to document any issues encountered and lessons learned
• Inform users about the new features, bug fixes‌ and any changes in the application’s behaviour

Security and compliance

• Perform security checks and vulnerability assessments on the new version
• Check that the deployment complies with all relevant regulations and standards
• Verify that access controls and permissions are correctly configured in the production environment

The future of app deployment is set to be revolutionised, driven by the integration of Artificial Intelligence (AI) and Machine Learning (ML). For instance, by analysing historical data, AI can predict potential issues and identify patterns that might signal future complications, allowing teams to take precautionary measures.

Furthermore, AI-driven testing can simulate a wide range of user scenarios for applications to perform well under various conditions.

The rise of outsource software teams spread remotely has led to the development of collaboration tools that streamline app deployment processes. Tools like Slack, Microsoft Teams‌ and Jira are already being used a lot for communication and project management. But in the future, we'll have specialised solutions like real-time collaboration platforms that integrate directly with development and deployment pipelines, allowing team members to monitor and contribute to deployments in real-time, regardless of their location.

Emerging trends like adoption of cloud-native architectures will revolutionise software deployment, making it ‌more scalable. Also, the prevalence and adoption of composable software development platforms like Builder.ai will ease app development and deployment, making it accessible to a broader range of users, including those without extensive programming experience.

Finally, these will drive the adoption of more advanced security practices, such as automated security audits for deployments to be fast and secure.