What Is Software Deployment?

Software deployment is the process of testing, configuring, and installing software so that it runs optimally and meets user expectations. To work properly, a software module requires IT infrastructure, integration with existing software systems, and ongoing maintenance. Software deployment delivers software to the intended audience on IT infrastructure that optimizes performance and security. It involves environment setup, managing code changes, and ongoing performance monitoring.

Software release is part of the software development process that provides a working version of the software to end users. It provides up-to-date application code and its interdependencies in production. All changes are tagged with version numbering to differentiate them from previous releases. Each release may feature improvements such as bug fixes, new features, and security patches.

In contrast, software deployment is installing new software releases in any environment where it must be used. It could include a test environment, development environment, or other customer infrastructure.

From an end-user perspective, the terms can be used interchangeably. Software or application deployment allows the latest software release to run on computers, servers, or the cloud. However, from a developer perspective, there is a difference. A release is software that the developer builds and releases or hands over to the end user. In contrast, deployment is just getting the software to work in the environment the developer chooses.

The software deployment process is essential to ensure organizations, employees, and end users benefit from the software systems developers build. These are the reasons why development teams deploy software.

Testing software in multiple environments

Developers deploy software in separate environments to assess its performance before releasing it into a live environment. For example, you can test if a software update is functional and bug-free by deploying it in a staging environment, which almost resembles the production environment. This way, developers can deploy the software more confidently to end users, knowing that it will run with minimum or no issues when they use it.

Integrating with business applications

Organizations install and use enterprise applications that operate independently to achieve common business goals. To streamline operations, they build intermediary software that allows different applications to communicate with each other. Deploying the intermediary software enables organizations to implement, monitor, and update the custom software system by collecting, requesting, and exchanging operational data.

Making software accessible to end users

Software deployments enable end users to access timely updates, security fixes, and functional applications. Often, developers collect user feedback to implement changes to existing codes. Then, they test and deploy a new version to address requests that users submitted.

We share different infrastructures where software teams can deploy the applications below.

On-premise deployment

Conventionally, organizations deploy software on on-premise servers. While this model offers complete control, software teams must manually provision servers, databases, networking, and other computing resources required to run the applications. Moreover, organizations must invest substantially in purchasing and maintaining hardware, operating systems, and other resources.

Cloud-based deployment

Cloud-based deployment allows software teams to deploy software systems on distributed servers owned by cloud service providers. Instead of investing in physical infrastructure, organizations pay only for the computing resources they use to host and run software applications.

Cloud deployment is especially suitable for microservice architecture, where developers build an application by combining several smaller interdependent components. When deploying the app to the cloud, developers package the software files into special modules called containers. Then, they deploy the containers on cloud servers.

Scaling cloud-based applications is more effortless, but some degree of resource provisioning is still required.

Serverless deployment

The serverless software deployment model allows developers to deploy on cloud-based infrastructure without provisioning the underlying compute resources. Despite relinquishing complete server control to the cloud provider, software teams can deploy their code on the cloud quickly without tedious configuration. For example, Coca-Cola used AWS Lambda, a cloud-based serverless computing service, to deploy low-latency web applications in just 100 days.

In modern applications, software runs on a group of logical or physical server components called nodes. When updating software, developers might replace the nodes with different software deployment methods.

Basic deployment

With basic deployment, software teams replace all nodes with the latest version. While basic deployment is quick, the approach is risky because it prevents teams from quickly rolling back the changes if the newly deployed updates fail.

Rolling deployment

Rolling deployment allows developers to gradually replace one or several nodes in the production environment. It’s less risky than basic deployment because developers can confirm that new updates are functional before replacing other nodes.

Multi-service deployment

Multi-service deployment is similar to basic deployment, except several different app versions run in a single environment. During deployment, developers update the respective nodes to a newer version. For example, version 1.0 is updated to 1.1, 1.5 to 1.6, and 2.4 to 2.5. While deploying different services is less risky because not all versions might fail simultaneously, rolling back the changes is still complicated. In addition, monitoring several new versions of live apps is challenging.

Canary deployment

Canary deployment offers a less risky and balanced approach to software deployment in production. Instead of replacing all nodes with new software releases, it does so in phases. At each phase, developers update a small group of nodes and verify the changes before replacing more nodes. End users are gradually exposed to the new version with canary deployment, allowing developers to measure the app performance under growing usage traffic. If required, developers can easily roll back the updates to the original version.

Shadow deployment

Shadow deployment allows developers to deploy a different application version in stealth. Unlike other deployment methods, the stealth application is hidden from the users. Users interact with the current application without knowing there’s another shadow application running behind it. When the current application receives user requests, it passes them to the shadow application. Then, the shadow application processes all requests but doesn’t return the results. As such, this method is helpful to test new changes in applications in the production environment without affecting end users.

A/B testing

A/B testing involves deploying several versions of an application alongside the current application in the same environment. Developers use A/B testing to evaluate how different versions perform in the same operating condition. Then, they choose the best version to replace the current application.

Successful software deployment requires careful planning, implementation, and follow-ups in the software development lifecycle. We share the steps that developers use to deploy software solutions.

Planning

Developers set deployment goals and ensure the exercise aligns with the organization’s objectives. For example, is the deployment meant to address bugs in existing applications? Or is the organization planning to introduce new features to meet evolving trends?

Preparation

With clear directions, developers customize an existing codebase or build an entire solution from scratch. Then, they consolidate all required codes, libraries, configurations, and modules into a single software package. In modern application development, we call the process containerization.

Testing

Before deploying the software, software teams put the code into stages of rigorous testing. This is important to prevent bugs, security flaws, or other coding issues from affecting customer experience. Based on the testing results, developers rework the code and prepare for deployment.

Deployment

Deploying software applications involves installing, configuring, and enabling the code in a live environment. Depending on the deployment mode, the environment might reside in a physical center, public cloud, or hybrid architecture. Regardless of the setups, developers must plan for zero or minimum downtime as they transition existing users from the previous version to the new version. This might involve updating databases, informing users of the planned deployment, and preparing contingency plans for unexpected outcomes.

Monitoring

After the new application goes live, software teams observe possible performance issues and respond to any problems. On top of that, software teams might need to release subsequent updates, fixes, or patches to ensure the new app performs as intended.

Organizations can accelerate software delivery, reduce risks, and improve customer satisfaction by integrating software deployment with these practices.

Use automation

Automation allows software teams to deploy codes without heavily relying on manual processes. Various parts of the software deployment process can benefit from automation. For example, you can automate software testing, packaging, and reporting to save time and reduce human error in the software release cycle.

Prepare a rollback strategy

Some software updates may encounter issues after being deployed. A backup plan, such as a rollback strategy, limits the impact on end users. Organizations should back up all data, configuration, and resources the current software uses before deploying a new release. This allows the software team to restore the previous working version if required.

Adopt a hybrid cloud architecture

Some organizations have invested in physical servers to host existing applications. With growing demands, on-premise infrastructure might be at capacity and can’t handle more traffic. Adopting hybrid cloud architecture through cloud bursting allows organizations to retain their physical setups and leverage the cloud’s scalability. cloud bursting is a practice that channels excessive on-premise traffic to the cloud to ensure optimal software performance.

Use of AI

Artificial intelligence (AI) can assist software teams in making informed decisions when preparing for software deployment. For example, you can use AI to predict deployment issues, analyze testing results, and monitor applications in newly deployed environments.

AWS provides tools, infrastructures, and services that help you deploy applications on the cloud more effortlessly.

For example, software teams use AWS CodeDeploy to automate software deployment across development, test, and production environments. With CodeDeploy, you can automatically monitor the application’s status and roll back changes if necessary.

AWS also allows development teams to deploy machine learning (ML) applications with AWS Deep Learning Containers. These containers consist of frameworks software teams can use to add machine learning microservices to their applications. Instead of provisioning the ML environment from scratch, you can access pre-packaged deep learning capabilities in the container.

Whether deploying modern applications on serverless or cloud-based infrastructure, you can use managed AWS services to reduce time to market and save costs.

• Use AWS Serverless and AWS Step Functions to visualize and orchestrate workflows when deploying distributed systems.

• Store, manage, and deploy your containers on AWS with Amazon Elastic Container Registry, Amazon Elastic Container Service, and more.

• Choose from hundreds of cloud computing setups on Amazon EC2 to power and scale your deployed workloads.

Get started with software deployment by signing up for an AWS account today.