Software Deployment in 2025: 7 Strategies & 5 Steps with Checklist

What is software deployment (application deployment)?

Software deployment is the process of making a software application available for use in a specific environment. It involves installing, configuring, and testing the software on target systems to ensure it functions as intended. This process is crucial for delivering software to end-users and can be managed manually or through automation.

Key aspects of software deployment include:

• Planning and preparation: Defining requirements, selecting the appropriate deployment method (manual, automated, etc.), and preparing the software package (installers, configuration files).
• Configuration: Tailoring the software to meet the needs of users or departments.
• Testing: Conducting thorough testing in a controlled environment to identify and resolve potential issues before a full rollout.
• Deployment: Installing the software on target systems, often during off-peak hours to minimize disruption.
• Post-deployment monitoring: Verifying the software’s functionality in the production environment and monitoring its performance. Ongoing Maintenance: Ensuring the software remains up-to-date and secure through regular updates and maintenance.

Benefits of proper software deployment include:

• Improved efficiency: Automation streamlines the process, reducing manual effort and errors.
• Enhanced security: Timely updates and patches address vulnerabilities, minimizing security risks.
• Increased reliability: Thorough testing and monitoring ensure the software functions as expected.
• Reduced downtime: Staggered releases and automated rollbacks minimize disruption to users.
• Cost savings: Efficient deployment can reduce IT support costs and improve resource usage.

Common deployment methods include:

• Manual deployment: Involves human operators manually installing and configuring the software. While simple for small deployments, it can be prone to errors and inconsistencies.
• Automated deployment: Uses tools and scripts to automate the deployment process, ensuring consistency and efficiency.
• Agent-based deployment: Relies on agents installed on target systems to facilitate the deployment process.
• Cloud-based deployment: Uses cloud infrastructure for deploying and managing software.
• Blue/green deployments: A method where two identical environments are maintained, one for the current version and one for the new version. Traffic is gradually shifted between the two to minimize disruption.
• Continuous Deployment: An automated approach where code changes are automatically deployed to production environments as soon as they are ready.
• Canary deployment: Releases updates to a small group of users first, then expands rollout based on stability and feedback.
• A/B testing: Runs two versions of software in parallel with different user groups to compare performance or user behavior.
• Multi-service deployment: Deploys multiple interdependent services together, common in microservice-based architectures.
• Shadow deployment: Deploys a new version alongside the current one, processing mirrored traffic without exposing it to users.

Octopus is a best-of-breed solution for software deployments.

This is part of an extensive series of guides about DevOps.

Why is software deployment important?

Software deployment plays a central role in delivering value to users of software products. A well-managed deployment process enables organizations to respond faster to market changes, implement user feedback, and release new features without unnecessary delays. This speed and consistency can provide a significant competitive edge.

Efficient deployment also reduces downtime and minimizes the stress on development teams. Instead of spending time troubleshooting release problems, teams can focus on building and improving features. Over time, streamlined deployment processes improve both developer productivity and user satisfaction.

When deployments fail, the impact can be severe: Service outages, dissatisfied customers, revenue loss, and reputational harm. To avoid these risks, modern teams invest in robust practices such as remote deployment and Continuous Delivery, which allow frequent, reliable updates while maintaining stability in production environments.

Software deployment vs software release

While software deployment and software release are closely related, they refer to different aspects of the software lifecycle.

A software release is the final version of the software that is prepared and packaged for distribution. It marks the point at which the software is considered ready for use and includes the necessary files, documentation, and release notes. The release process often involves versioning to track the different iterations of the software.

Software deployment is the process of actually delivering the released software to the target environment where it will be used. This process includes installing, configuring, and enabling the software on a server or device so that end-users can access it. While a release can be considered a “product” ready for deployment, deployment itself involves the technical steps to make the software operational in a specific environment.

A feature release is the process of enabling functionality through a switch or toggle to make it available to end users. This allows the visibility of a new feature to be decoupled from the deployment process. Feature flags also allow new functionality to be enabled for subsets of users for a pilot or for an incremental rollout.

Software deployment process stages and quick deployment checklist

Let’s review the primary stages involved in modern software deployment. In each stage, we’ll provide a short checklist of things you need to be aware of.

1. Planning and preparation

You may be able to deploy your software whenever it’s ready, or you might need to be more careful when you perform a deployment. Your planning and assessment stage helps you think about when you can deploy, what testing needs to be done before you are confident enough to deploy a software version to production, who needs to be involved, and how you’ll achieve a reliable repeatable process for deployments.

You’ll also work out what you’ll do if something goes wrong during a deployment, so you don’t need to come up with a plan in the midst of a crisis.

To create your plan, you’ll assess the current process, infrastructure, system requirements, and potential barriers to successful deployment. You can then present a plan that all stakeholders can agree on so the objectives, timelines, roles, and process are aligned.

Deployment checklist:

• Define deployment objectives
• Identify stakeholders and responsibilities
• Assess infrastructure and system requirements
• Review compliance and security considerations
• Create rollback and recovery plans
• Establish deployment timeline
• Document approval process

2. Development / configuration

During this stage, the software is either created from scratch or configured from an existing framework to meet the specified requirements. This phase involves coding, integrating various components, and setting up the necessary environments and dependencies.

Effective communication and coordination among development and operations teams are crucial during this phase to ensure that the software aligns with the business requirements and technical specifications. Proper configuration and custom development lay the groundwork for integration and functionality in the deployment phase.

Deployment checklist:

• Set up development environment
• Configure dependencies and integrations
• Implement version control
• Apply coding standards and guidelines
• Document configuration settings
• Prepare environment variables
• Validate infrastructure-as-code templates

3. Testing and quality assurance

Quality can’t be inspected into software, it needs to be part of the normal software delivery process. The shift-left movement recognizes the need for quality to be integral early in the process. The sooner you find a defect, the easier and cheaper it is to fix it.

You can use a mix of testing methods throughout the software delivery process, such as unit testing and integration testing or human-driven methods like user acceptance testing (UAT) and exploratory testing. You should aim to automate tests as much as possible, so people don’t need to run repetitive test scenarios manually.

You should design your initial automated test suite to complete in under 5 minutes, so developers can get fast feedback about the deployability of their new software version. Slower tests can take place in a second phase, while any manual testing should be reserved only for scenarios where all the automated checks have passed.

Deployment checklist:

• Run unit tests
• Run integration tests
• Perform automated regression tests
• Conduct user acceptance testing
• Validate performance and load tests
• Verify security and compliance tests
• Review test coverage reports

4. Deployment

The deployment stage is where the software is pushed to the production environment. This phase involves executing the deployment plan, performing the necessary configurations, and ensuring that the software is accessible and functional for end-users.

This stage requires attention to detail and coordination among various teams to manage the live transition smoothly. Any issues encountered during deployment need to be quickly addressed to minimize downtime and ensure a seamless user experience.

Deployment checklist:

• Verify pre-deployment requirements
• Apply infrastructure configuration
• Execute deployment scripts
• Migrate data if needed
• Validate application availability
• Monitor system health during rollout
• Confirm rollback readiness

5. Post-deployment monitoring and maintenance

Monitoring and maintenance are ongoing activities post-deployment. Continuous monitoring ensures the software operates as expected, capturing performance metrics and identifying any issues that arise in a live environment.

Regular maintenance includes applying updates, patches, and improvements to keep the software secure and efficient. Proactive monitoring and maintenance help in sustaining software performance and reliability over time, providing a stable user experience.

Deployment checklist:

• Enable application monitoring
• Track performance metrics
• Set up error logging and alerts
• Apply patches and updates
• Conduct security audits
• Review system capacity regularly
• Document incidents and resolutions

Key software deployment strategies and techniques

Here are some of the primary techniques organizations use to deploy applications, commonly known as deployment strategies.

1. Manual deployment

Manual deployment relies on administrators or operators to install, configure, and update applications directly on target systems. This may involve copying files, running setup scripts, and manually adjusting configuration settings.

It is simple and works well for small-scale systems but does not scale. Manual processes are error-prone, inconsistent, and difficult to repeat reliably across multiple environments.

2. Automated deployment

Automated deployment uses tools and scripts to handle installation, configuration, and verification steps without human intervention. This approach reduces manual effort, enforces consistency, and speeds up delivery.

Automation is essential for modern DevOps and Continuous Delivery practices. It allows for repeatable processes, easier rollbacks, and deployments at scale across multiple environments.

3. Agent-based deployment

Agent-based deployment relies on lightweight software agents installed on target systems. These agents communicate with a central deployment server to receive updates, execute tasks, and report status.

This model simplifies deployments in large or distributed environments by enabling centralized management. However, it adds operational overhead, since agents must be installed, maintained, and updated.

4. Cloud-based deployment

Cloud-based deployment uses cloud infrastructure to deliver applications quickly and at scale. Deployments can be managed through cloud provider services or specialized tools designed for cloud-native environments.

This approach supports elasticity, allowing systems to scale up or down automatically. It is well-suited for modern architectures but requires cloud expertise and can increase reliance on a single provider.

5. Blue/green deployment

Blue/green deployment uses two identical production environments. One environment (blue) runs the current version of the application, while the new software version is deployed to the other (green) environment. Traffic is switched to the green environment once the new version is confirmed to be stable and functional, ensuring a transition with minimal downtime.

This method provides a fail-safe mechanism. If the new version encounters issues, traffic can be switched back to the blue environment, ensuring service continuity. Blue/green deployment significantly reduces risks and allows for testing in a production-simulated environment before fully switching over.

6. Continuous Deployment

Continuous Deployment is a practice where every change that passes automated testing is released directly to production without manual approval. This approach requires a highly reliable deployment pipeline with strong automated testing, monitoring, and rollback mechanisms in place.

It enables teams to deliver features and fixes to users quickly and continuously. While it reduces lead time for changes, it also demands mature DevOps practices and a strong culture of automation to ensure stability and reliability.

7. Canary deployment

Canary deployment involves releasing the new version of software to a small subset of users before rolling it out to the entire user base. This gradual exposure allows for monitoring and gathering feedback on the new release while minimizing the risk of widespread issues. If the deployment proves successful, the rollout continues until all users are on the new version.

You need strong monitoring in place for the canary approach, so you can quickly identify potential problems and halt the deployment if necessary. It works well in environments that demand high availability, enabling teams to validate changes and gather user feedback without impacting the entire user population.

8. A/B testing

A/B testing is a method where two versions of software are deployed simultaneously to different user groups to compare qualities such as system performance or user response to a change. This approach helps identify the more effective version based on defined metrics such as user engagement, performance, or other key indicators.

By analyzing the results from each group, teams can make data-driven decisions about which version should be fully deployed. This strategy ensures that the chosen version has been validated to provide the best outcome, leading to higher satisfaction and better overall performance.

9. Multi-service deployment

Multi-service deployment focuses on deploying multiple, interdependent services either simultaneously or in a sequence, depending on their relationships and dependencies. This method is commonly used in microservice architectures where different services perform specific functions within the application ecosystem.

Careful orchestration of these deployments is critical to ensure that service dependencies are handled correctly and that the overall system remains functional during the deployment process. Multi-service deployment allows for greater modularity and independent scaling of components, enhancing the system’s flexibility.

10. Shadow deployment

Shadow deployment involves running the new version of the software in a production environment alongside the current version but without exposing it to users. The new version processes a mirror of the live traffic, allowing for testing and performance monitoring without impacting the user experience.

This strategy provides insights into how the new version interacts with real-world data and scenarios, helping to identify and rectify issues before fully transitioning to the new version. Shadow deployment significantly mitigates risks associated with new releases, enabling smoother transitions.

Common challenges of manual software deployment processes

Traditional IT operations teams would carry out the software deployment process manually, perhaps aided by scripts that would automate certain parts of the process. It is now understood that a manual process is not suitable for modern development processes, in which organizations aim to release software on a weekly, daily, or even hourly basis.

Here are some of the challenges traditionally encountered in the deployment process:

Risk of downtime

Manual deployment processes often lead to increased risk of downtime due to human errors, such as incorrect configuration settings or missteps during the deployment sequence. This can severely impact user experience, leading to loss of revenue and customer dissatisfaction. Unplanned downtime makes it difficult to diagnose and resolve issues quickly.

Failed deployments

Failed deployments can occur due to incomplete or incorrect deployment scripts, missing dependencies, or misconfigured environments. These failures often require time-consuming rollback procedures or emergency patches, which can disrupt operations and delay new feature releases. Traditional deployment processes are error-prone, leading to failed deployments.

Loss of data integrity

Manual processes increase the risk of data corruption or loss due to human error, such as running incorrect scripts or failing to back up data before making changes. Once data integrity is compromised, it can be challenging to restore the system to its original state, potentially leading to operational disruptions and loss of critical information.

Slow feedback loop

Manual deployments typically result in a slow feedback loop, where it takes considerable time to detect and respond to issues. Without automated processes, teams may not discover deployment-related problems until they have already impacted the production environment. This delay in feedback leads to prolonged troubleshooting sessions and longer resolution times.

Resistance to change

Manual software deployments were infrequent, and typically represented large changes to existing systems or complete replacement of previous systems, leading to resistance within the organization. Modern deployments occur much more frequently and represent small, incremental changes, largely overcoming this challenge.

What is a deployment pipeline?

Your deployment pipeline includes the steps required to take a software version all the way through to your production environment.

Modern deployment pipelines are an automated process that streamlines the entire path from code commit to production release. It consists of a series of stages that a new software version passes through, each designed to validate the functionality, performance, and security before it is deployed to a live environment.

The primary goal of a deployment pipeline is to ensure that software changes can be released reliably, frequently, and with minimal risk. An automated deployment pipeline can solve most of these challenges, turning software deployment into a routine, low-risk, and low-toil activity.

When implementing a deployment pipeline, organizations can choose between two approaches:

• Continuous Delivery: Software is ready to deploy at all times, but actual deployment to production requires manual approval.
• Continuous Deployment: Every change that passes tests is automatically deployed to production. This requires rigorous testing and high maturity of deployment pipeline automation.

Related content: Read our guide to progressive delivery

Top benefits of automating software deployment

Automating software deployment offers several advantages that significantly improve the efficiency, reliability, and scalability of the deployment process. Here are some of the key benefits:

• Reduced human error: Automation minimizes the manual steps involved in the deployment process, reducing the risk of errors that can occur due to oversight or incorrect configurations. This leads to more consistent and reliable deployments.
• Faster time to market: Automated deployments accelerate the release cycle by streamlining the deployment process. This allows organizations to deliver new features and updates more frequently, meeting market demands and customer expectations more effectively.
• Enhanced Scalability: Automated deployment processes can easily be scaled to handle large volumes of releases across multiple environments, ensuring that software can be deployed efficiently regardless of the size or complexity of the application.
• Improved consistency and repeatability: Automation ensures that the deployment process is consistent across different environments. This repeatability is critical for maintaining the integrity of deployments, as the same process is executed in the same way every time.
• Continuous Integration and Continuous Delivery (CI/CD): Automation is a cornerstone of CI/CD practices, enabling continuous integration of code changes and automated deployment to production environments. This leads to more frequent and smaller releases, reducing the risk associated with large, infrequent updates.
• Enhanced monitoring and feedback loops: Automated deployments often integrate with monitoring tools that provide real-time feedback on the deployment process and application performance. This enables teams to quickly detect and resolve issues, improving the stability and reliability of the software.

What are software deployment tools?

Software deployment tools are designed to capture the deployment process, automates steps, and apply configuration values appropriate to each instance. The tools make sure a new software version passes through pre-production environments before they are eligible to be deployed in a live environment.

Unlike a Continuous Integration (CI) tool, which should fail as soon as a build or test error occurs, a Continuous Delivery (CD) tool can pause on error and request human intervention. This allows a human operator to resolve transient issues to unblock the deployment, or re-deploy a previous version if they decide not to proceed.

Because deployment steps are automated, they are never forgotten during a deployment and they are always performed precisely and accurately. Automated deployments are also faster and less risky, as people don’t need to access the infrastructure to perform manual tasks.

Software deployment tools will apply the correct configuration as deployment progresses through the development, test, staging, and production environments. They may also be able to apply different configurations based on other factors, for example, when software is deployed to many physical locations like retail stores or cloud regions, or if customers each have a dedicated instance of the software.

Software deployment best practices

Automate deployments to ensure consistency and reduce human error

Great deployments are repeatable, reliable, and secure. Automated deployment tools are the best way to achieve this. An automated deployment runs the same steps in the same order every time. This reduces risk and speeds up the deployment process.

With automated deployments, you can deploy more often with a lower change failure rate. Instead of dreading deployments, they can become low-stress and even happy events as the focus shifts from the anxiety of changing the production environment to the celebration of launching improved software.

Maintain documentation of deployment process and configurations

Adequate documentation is essential for a successful deployment process. Detailed records of the deployment procedures, system configurations, and any changes made help in troubleshooting issues, training new team members, and maintaining consistency across deployments.

Documentation provides a reference point that ensures all stakeholders understand the deployment workflows and can follow standardized practices. It also aids in compliance and auditing processes by providing clear evidence of the deployment activities.

Use separate environments for development, testing, and production

Using separate isolated environments for development, testing, and production. This helps avoid conflicts and reduce risks associated with software deployment. Development environments allow for experimentation and feature development, while testing environments allow comprehensive testing without affecting production systems.

This separation provides a controlled setting for identifying and addressing issues before the software reaches the production environment. It also enhances security and stability by isolating environments, preventing unintended interactions and ensuring smoother deployments.

Make pre-production environments close analogs of production

Ensuring that pre-production environments closely mimic production environments is critical for reliable software deployment. These environments should mirror production in terms of hardware configurations, software versions, network settings, and data volumes. This alignment helps identify potential issues that may only manifest in the production environment, allowing them to be addressed before deployment.

Good analogs also enable accurate performance testing and load balancing, ensuring that the software behaves as expected under real-world conditions. By maintaining this fidelity, organizations can reduce the risk of unexpected failures post-deployment, leading to smoother releases and more predictable outcomes. This practice also fosters greater confidence in the deployment process, as it helps ensure that what works in pre-production will work in production as well.

Implement strict version control to manage codebase changes

Strict version control is critical for managing codebase changes and ensuring that every change is traceable, reversible, and reproducible. Tools like Git provide robust version control capabilities, allowing teams to track modifications, manage different versions, and collaborate effectively.

Version control helps keep a clear history of code changes, facilitating rollback if issues arise. It also supports branching and merging, allowing multiple development streams to exist simultaneously, thus enhancing flexibility and collaboration in development efforts.

Establish proactive monitoring to detect and respond to issues

Proactive monitoring is essential for detecting and addressing issues promptly during and after deployment. Monitoring tools collect real-time data on application performance, user activity, and system health, providing insights that help in identifying and resolving problems before they escalate.

Established monitoring practices enable swift responses to anomalies, minimizing downtime and ensuring a smooth user experience. Continuous monitoring also supports performance optimization and security measures, contributing to the long-term stability and reliability of the software.

Automating software deployment with Octopus

Octopus handles complex deployments at scale. You can capture your deployment process, apply different configurations, and automate the steps to deploy a new software version or upgrade a database.

With Octopus, you can manage all your deployments whether it’s cloud-native microservices on Kubernetes or older monoliths running on virtual servers. This means you can see the state of all your deployments in one place and use the same tools to deploy all your applications and services.

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See additional guides on key DevOps topics

Together with our content partners, we have authored in-depth guides on several other topics that can also be useful as you explore the world of DevOps.

Developer experience

Authored by Octopus

• [Guide] Developer Experience: Importance, Metrics, And 6 Ways To Improve
• [Guide] The SPACE Metrics: A Holistic Measure Of DevOps Productivity
• [Product] Octopus Deploy | Continuous Delivery and Deployment Platform

Mainframe modernization

Authored by Swimm

• [Guide] 7 Approaches to Mainframe Modernization
• [Guide] Working with JCL in Mainframe: Practical Guide & Tutorial
• [Whitepaper] Automating legacy code documentation
• [Product] Swimm | Document your codebase

Kubernetes cost optimization

Authored by Finout

• [Guide] Kubernetes Cost Optimization: 4 Cost Factors & 6 Cost Cutting Tips
• [Guide] What Is Kubernetes? Definitions, Components & Use Cases [2025]
• [Blog] Kubernetes Deployment Anti-patterns
• [Product] Finout | Enterprise-Grade FinOps Platform

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