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Automation of deployments enables faster release of applications and features while eliminating manual intervention requirements.
Deployment automation enables you to quickly deploy software into testing or production environments at the push of a button, significantly decreasing production deployment risks while providing quick feedback on product quality.
Automation Of CI/CD, Deployment, And Automation
Deployment automation is an integral component of devOps and pipeline management.
Continuous Integration/Continuous Delivery (CI/CD) is an approach to quickly deliver applications to customers that combines continuous automation with continuous monitoring throughout the lifecycle, from development and testing through delivery and Deployment.
Continuous integration occurs when developers upload changes to an application repository(or Container Registry) for testing.
The code is then automatically tested for bugs before being uploaded into production (via deployment automation).
After developers integrate their changes into an application, they must be verified through automated builds and various levels of automated tests - typically unit and integration testing to ensure they didn't break it.
Continuous Deployment (CD) refers to using deployment automation to implement changes from developers' repositories into production where customers can utilize them.
Continuous Deployment relies on test automation, as there is no physical gate in the pipeline before production.
Automation of continuous Deployment offers a solution to teams overburdened with manual processes that slow app delivery.
Automating the next step in the deployment pipeline enhances the advantages achieved through continuous integration.
Automating DevOps Support
The Continuous Integration/Continuous Deployment process must be implemented agilely by teams from development and operations working collaboratively using Site Reliability Engineering (SRE) or DevOps methodologies.
We are adopting Agile methods in software development resulting in faster release cycles.
When the development team configures or deploys an environment one way. In contrast, operations teams change it later.
Deployment automation fails to work effectively. Consistency is critical in an automated environment. All environments, including production ones, should use the same deployment process to ensure optimal results.
Suppose these teams don't work in concert. In that case, there is a danger that the operations team will handle deployments manually, potentially leading to errors, inconsistent results, and slower release cycles.
DevOps is an effective way of ensuring teams work in harmony. DevOps and development teams should work collaboratively on creating your deployment automation process to guarantee consistency and repeatability.
Automate Software Deployment Processes
A deployment pipeline typically consists of three main steps: build, test, and deploy. This pipeline streamlines the deployment process so code is deployed swiftly when committed.
- Build: A software developer commits the code to a repository. Code changes must be integrated into environments similar to the production environment.
- Test: A deployment automation tool, such as Jenkins Ansible(r), will detect the new code and run a series of tests. After a build passes all tests, it can be released into production. This step is done manually without deployment automation.
- Deployment: In the deployment stage, the application is available for users.
Testing should take place concurrently with development in agile and DevOps environments. Feedback from the development team should be received on an ongoing basis.
Continuous integration (CI) is an integral component of development cycles to address this ongoing stream of updates and ensure compatibility among code changes, being built, tested, and then merged back into shared repositories without conflict between each update.
A successful CI can be defined as any time new code modifications are built, tested, and then merged back into shared repositories - successfully managing updates without creating conflicts among updates!Your process should allow for on-demand Deployment of environments. Otherwise, it becomes inefficient.
What Is A Deployment Pipeline?
A deployment pipe in software development refers to an automated set of processes designed to move updates and additions from version control into production quickly and reliably, in the past, writing, building, and deploying code required manual steps that took time-consuming effort by both developers and operations teams for testing and release.
Automation within a deployment pipeline allowed development teams to focus more on innovation and improving user experiences.
By automating manual tasks, teams could deploy code updates faster and with reduced human error.
This article will outline the stages and benefits of creating a software deployment pipeline and provide advice on how to construct one.
The Main Stages in a Deployment Process
A deployment pipeline has four stages:
- Version Control
- Acceptance tests
- Independent Deployment
- Production Deployment
Version Control (VC) is the initial stage in a deployment pipeline. Once a developer completes a code addition and commits it to a source-control repository, the deployment pipeline kicks in immediately:
- Automatically compiling and unit testing of code.
- Analysis through the installer creation process.
- Binaries are generated and stored in the repository of artifacts upon passing the Version Control stage and being validated before moving on to subsequent steps in the pipeline.
Acceptance Testing is the stage where newly-compiled code goes through a series of tests designed to ensure it satisfies your team's predefined acceptance criteria.
Tests must be written based on company goals and user needs - they'll run automatically once integrated into the deployment pipeline. However, update or modify them regularly to comply with user and company expectations.
After acceptance testing and Independent Deployment, the code is automatically deployed into a development environment.
To ensure an accurate representation of functionality, this development environment should mirror production environments as much as possible so teams can address bugs without impacting live user experiences.
Production deployment is the final stage in any deployment pipeline, similar to Independent Deployment. Still, it occurs live rather than just being copied over.
At this point, any bugs or issues need to be addressed promptly to provide users with an optimal experience; DevOps usually takes care of this step, with zero downtime being their goal.
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Benefits Of A Deployment Pipeline
The team, stakeholders, and end users of your software engineering system can all benefit from an integrated deployment pipeline in a variety of ways.
An integrated deployment pipeline has numerous important advantages.
- Teams using DevOps software can release features and updates more rapidly by automating manual steps involving compilation, testing, and code deployment. By automating compilation testing deployment, development teams can focus on constantly innovating products without interruption from human errors.
- Troubleshooting updates are much quicker when they can be easily rolled back, simplifying the whole troubleshooting process. Production teams can respond more rapidly to user needs by prioritizing minor updates with frequent and faster releases. How to Create a Deployment Pipeline
An organization's deployment pipeline must be tailored to its company and user's expectations and vary depending on its service or product type.
No single deployment strategy fits all; planning and testing must be performed.
Three essential elements are required when planning your deployment pipeline:
- Build Automation: Build automation is called Continuous Integration, or CI for short. These automated steps ensure continuous integration - including compilation, building, and merging code - ultimately leading to more excellent reliability for software projects.
- Automated Tests: Automated tests can be created through custom-written test cases that run automatically during deployment pipeline steps to check against predefined criteria and validate new code.
- Deploy Automation: Like continuous integration, deploy automation using Continuous Deployment/Delivery (CD for short) can speed up code delivery by automating releasing updates into a shared repository and automatically deploying them to either development or production environments. The primary goal of your deployment pipeline should be to eliminate any need for manual steps or interventions. It means creating custom algorithms to automatically build/compile, test, and deploy new code. DevOps teams and developers can spend more time developing new features and updates for the highly competitive market.
What Are Continuous Integration (CI) And Continuous Delivery Pipelines (CDP)?
Continuous Delivery Pipelines (CDP) are Continuous Integration (CI) and Continuous Development (CD) pipelines which continuously compile, validate and deploy code updates as they are written rather than waiting for specific release or merge dates to release or merge them into the product.
CD/CI Pipelines are integral to a complete deployment pipeline system.
Deployment Pipeline Tools
Utilizing existing tools is critical to fully automating and maximizing your pipeline. Various elements must be considered when setting up a deployment pipeline, such as source control, build/compilation, and containerization.
An effective development pipeline should constantly evolve. It should introduce and use new tools to increase speed and automation.
Here are some tools you should use in your deployment pipeline:
- Jenkins
- Azure DevOps
- CodeShip
Pipelines are automated processes designed to help developers and DevOps experts compile, build and deploy code reliably and efficiently to their production computing platforms.
However, no specific rules exist regarding the design and use of pipeline components. Some common ones include:
Build automation/continuous integration
- Test automation
- Deployment automation
Pipelines are usually made up of the following tools;
- Source Control
- Build Tools
- Containerization
- Configuration Management
- Watching
Common Pitfalls In Deployment Automation
You may encounter the following problems when automating your deployment process:
- The complexity of existing processes
- Dependencies between services
- Components not designed for automation.
- Poor collaboration between teams.
Complexity
Complexity can be a trap. Test automation automating fragile and complex manual processes often results in complex automated ones.
Therefore, to optimize deployment ability, you should redesign for deployment ability. This means keeping deployment scripts simple while pushing complexity onto infrastructure platforms or application code instead.
In particular, cloud native apps running on platforms-as-a-service such as App Engine, Cloud Run, or Pivotal Cloud Foundry typically deploy with one command without any deployment scripting requirements: this should be your ideal process.
An effective deployment process must have two main characteristics. First, each step in the Deployment must be as idempotent as possible so you can repeat them if necessary; secondly, they should also be order-independent; otherwise, they would crash uncontrollably if any component or service is missing, forcing services to operate at reduced capacity until their dependencies have returned.
At our firm, we advise incorporating these principles as requirements of any new products or services from their inception.
Retrofitting existing systems with automation may require extra work either to implement these characteristics or add telemetry so the deployment process detects inconsistent states gracefully and terminates smoothly.
Read More: Brief Explanation of Software Development Life Cycle
Dependencies
Second, many deployment processes in enterprise environments are orchestrated. You must deploy services in an ordered fashion while performing other tasks synchronization, such as database migrations.
Unfortunately, tools designed to aid this scenario are just bandages covering up a structural problem: tight coupling between components and services that must gradually be addressed for deployments to proceed without orchestration.
Designing services to support backward compatibility is essential, enabling clients to upgrade individually rather than all at once.
API Versioning or other techniques may be employed to achieve this effect. Your services must also continue functioning even if some of their functionality becomes unavailable if they cannot connect to services they rely on to reduce cascading errors and ensure client continuity.
The circuit breaker pattern can be used to design distributed systems, whereas decoupling database updates from services using Parallel Change Pattern is another practical approach to designing distributed systems.
Not Intended For Automation
Components that aren't automated are another common pitfall. Automating any process that involves manually logging in or clicking around on a console should be improved upon; most platforms (including Google Cloud) now offer APIs that your deployment scripts can leverage; otherwise, you could change the configuration directly in a database file, or switch out with one that does offer such an API instead.
Poor Collaboration Between Teams
Lastly, an additional pitfall arises when IT operations and developers don't work together in sync. This may take several forms; developers might deploy using one method while IT operations take an alternate approach; environments configured differently could increase the risk that the deployment process be manually performed by IT Operations, leading to inconsistencies or errors during the deployment process requiring human involvement resulting in inconsistency or errors requiring manual intervention by IT Operations leading to inconsistency or errors requiring manual execution by them as well.
Therefore developers and IT operations should collaborate in creating a deployment automation process where both teams understand, maintain, and evolve it by working together on creating a deployment automation process, allowing both teams to understand and evolve this automated deployment process together.
How To Improve Deployment Automation
Documenting your current deployment process is the first step. This should be accomplished using a tool accessible to developers and operations personnel.
After documenting, take steps to streamline and automate it incrementally by performing specific tasks such as:
- Package code for Deployment.
- Create pre-configured virtual machines or containers.
- Automating middleware deployment and configuration.
- Copying files or packages into the production environment.
- Restarting applications, servers, or services.
- Generate configuration files using templates
- Automated deployment tests ensure the system is configured correctly and working.
- Testing procedures are run.
- Database migrations can be automated by scripting.
Measurement Of Deployment Automation
Software Delivery Pipelines are meant to automate all steps and minimize manual intervention. Manually performing tedious and repetitive tasks introduces human error into the equation, which could compromise deliverables and SLAs by creating botched deployments.
Deployment Pipeline
Deployment Pipeline (DP) is an automated process that takes code from version control and makes it available to your users.
A team of developers working on a project or feature requires a reliable, efficient way to test, build and deploy their work; in the past, this was typically completed manually with many delays due to communication or human error.
Following are the stages of a typical pipeline for Deployment.
Version Control
Software developers writing code often commit their updates to source control.
- Code Compilation
- Unit tests
- Code Analysis
- Installer creation
Once the steps have been completed, executables will be assembled into binaries that can be stored in an artifact repository and used later.
Acceptance tests
Acceptance Testing is performing tests on compiled/built code to check against predefined acceptance criteria.
Independent Deployment
Independent Deployment is the process of introducing tested and compiled artefacts into testing environments. Your development environments should ideally be very similar to your production environments so that you may test your software's functionality before moving on to more automated or manual testing.
Production Deployment
The operations team or DevOps usually manages this step similarly to independent deployments, delivering code directly onto production servers.
Blue/Green or Canary releases allow for zero-downtime deployments and version rollbacks should unexpected issues arise. In contrast, release windows are usually negotiated within companies for non-zero-downtime deployment capabilities.
Continuous Integration & Continuous Delivery Pipelines
Continuous integration (CI) refers to regularly and repeatedly checking code into a version-controlled repository, with these check-ins activating automated build pipelines that facilitate rapid error detection.
The main benefits of CI include:
- Integrating small changes into larger code bases is more straightforward, and your team can better recognize your work. Early identification of bugs makes them simpler to resolve, leading to reduced debugging efforts. Code compilation/build consistency testing should also be conducted before the final release.
- Rapid code delivery is made possible due to reduced integration issues. Continuous Delivery (CD) allows developers and engineers to reliably, quickly, and sustainably deliver bug fixes, new features, and configuration changes in production. Code delivery pipelines can be set up on demand or run regularly by CD.
- CDs offer many advantages. Their low-risk releases, Canary and Blue/Green releases, offer zero downtime releases without user detection, allowing them to roll back quickly.
- Continuous Integration/Continuous Deployment makes bug fixes and feature delivery easier. Once features or bugs have been completed and passed the acceptance/integration tests, CD pipes allow them to be swiftly delivered into production.
- Continuous delivery allows teams to work on features and bug fixes in small batches, providing users with faster feedback. In addition, continuous delivery allows for rapid changes during development - decreasing project time and costs overall.
Blue/Green Deployments
Blue/Green deployment processes can help minimize risk and downtime by creating two mirror copies of your production environment, with one named Blue and one designated Green; at any one time, only one environment serves production traffic.
Production traffic won't be affected when installing software in a non-live environment for deployment purposes.
Once all tests are passed successfully, traffic is routed toward this system which currently doesn't support live production traffic.
In the second Deployment, this process is repeated but with the original environment becoming inert.
Canary Deployments
Canary Deployments differ from Blue/Green deployments by not necessitating two environments to operate simultaneously.
Instead, Canary Deployments allow a live production test on some users/servers before rolling out to everyone.
Canary releases offer several advantages, with their primary function being early failure detection. Furthermore, canaries can help roll back changes quickly in cases of exceptions or failures and minimize service disruption for users or services affected.
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Conclusion
CI is a process that enables software development teams and their developers to automate code quality assurance and compilability testing.
At the same time, CD is a tool that helps Development and Operations Teams deliver new features and bug fixes to users quickly.
