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Software deployment checklist
Mastering the art of software deployment: a step-by-step approach and essential checklist.
If you decide to implement your software project, you must understand that the software deployment process requires a solid approach and adherence to the planning strategy from the beginning. Software deployment covers a number of steps that you should follow to prevent unpredictable bugs and potential threats which can lead to project fiasco. As a result, 30 percent of app deployments fail.
Well-elaborated software deployment is an essential aspect of customers’ satisfaction since it facilitates smooth product interaction with them and can help them respond quickly to customers’ demands. The same deployment method that your dev team selects for building, testing, and deploying defines the capability of the project to implement new updates and features instantly across the customer journey.
Three steps toward successful software deployment
Software deployment can be complex, but breaking it down into three key stages – Planning and Preparation, Testing, and Deployment – can simplify the process and increase success rates. Each step is crucial for a smooth transition from development to production. Let’s explore these stages in detail.
1. Planning and preparation
At this stage, developers define the method of production data deployment, what configuration files and libraries will be used, and other related resources required for the application. Then they check the server to ensure the smooth and cohesive running of the code. Seamless interaction between team members is one of the main drivers for project success.
Before deploying the updates to the live environment, loading the code into the testing environment is essential. Based on the pre-configured set of tests, the development team can do automated tests to detect vulnerabilities and correct them accordingly.
To get approval from the team lead, it is recommended to copy updates in the testing and staging environment to the production environment. It is worth running scripts that allow updating the extensive database. Once the changes are performed, the final step is to test the server for bugs. If there are any errors and you want to identify the critical issue, you can roll back the server. All these steps are needed to avoid unforeseen problems. Therefore, if you deploy the software step-by-step, there is a low probability of running the risk.
Once you know the main stages of software deployment, let’s jump into a detailed software deployment checklist to be equipped with solutions to mitigate possible issues during the shadow deployment process.
Your software deployment checklist
Successfully deploying software requires more than just understanding the stages of deployment. It also involves a comprehensive checklist that covers all aspects, from team collaboration to continuous integration and delivery. This checklist serves as a roadmap, guiding you through the necessary steps to ensure a smooth and efficient software deployment. Let’s delve into these crucial elements that can make or break your software deployment.
Build collaboration between development and operations teams
Compared to traditional software development and infrastructure management processes, the DevOps (developers and operations) model denotes the teams’ unified efforts to improve the organization’s capabilities to deliver high-quality and high-speed products to customers. Compared to traditional approaches, teams work to achieve this goal throughout the entire software development lifecycle without being siloed.
By combining development and operations cultural philosophies, their workflows, best practices, technology stack, and tools, businesses can increase teams’ velocity, ensure rapid delivery and customer reliability, and compete effectively on the market.
Continuous integration (CI), continuous delivery (CD), and microservices architecture are the best practices to accelerate the software release process. More on that read in the sections below.
Set and track KPIs
Software deployment metrics and analytics are essential elements in planning and controlling the software deployment process and decision-making about further iterations to deploy software. Key performance indicators define server utilization, deployment frequency, mean time to recovery (MTTR), page load time, error rate, number of downloads, CPU usage, etc. Instant monitoring of KPIs helps achieve more excellent results and be in the loop of all software events permanently to adapt quickly if necessary.
Create SQL scripts in advance
SQL scripts are a series of instructions allowing developers to deploy new versions of the database system to the product while keeping current data before the changes. Therefore, if you plan to implement significant shifts in the database, SQL scripts are means by which you can quickly back up the whole database.
Create a rollback plan
You should ensure that your next deployment plan performs smoothly in unpredictable situations. For this purpose, a rollback strategy comes into play. Thinking about a backup copy of your latest version will be your airbag when an issue occurs. Furthermore, because numerous changes can affect the further software deployment process, a rollback plan will be a rescue allowing to return to the previous version.
Apply Synthetic Transactions Testing
With synthetic transactions monitoring, developers can track the performance of the software by applying the scripts that allow them to simulate user behaviors. For instance, by simulating database connections, you can view how the database would perform in terms of page loads impacted by the activity of real users.
Build and package your software once – and deploy it everywhere
Before software deployment, you need to build and package it. It will be a huge mistake when you build a specific codebase each time when deploying software to different environments since it can expose your software to serious risks. Based on the principle of continuous delivery, “build binaries only once,” we recommend building the deployment package only once for all environments. Subsequently, it would help if you reused the already-built binary.
Use feature flags to mitigate risks
Feature flags (aka feature toggles) are a software deployment technique allowing developers to change software functionality by turning it on or off in runtime without redeploying the code. Therefore, if new features are added, they can be available only to internal users who can access them using feature flags; other users will not be able to view changes. Thus, feature flags allow the deployment of new features in small quantities to a fraction of users. With the option to toggle on or off the feature, only certain users will have access to it, while you can keep adding more complexity to your code.
Such software deployment techniques contribute to Continuous Delivery, a recommended practice to ensure automated changes to the software environment at the production stage.
Adopt Continuous Delivery and Continuous Integration
With CI practice (continuous integration), code changes performed by all developers are combined in a unified repository, making the software deployment process consistent. Compared to past times, developers can immediately merge their differences before the document release versioning of their work is finalized. Continuous integration allows developers to optimize their time and prevent bugs since they can gradually fix them, fostering fast updates and delivery to customers.
The next step toward automation of the software release process is implementing the Continuous Delivery (CD) technique which aims at automated preparation of the code changes to the production. After the build stage, the application is in the pre-production or testing environment. Before deploying to customers, developers have a deployment-ready artifact that has been tested. The continuous delivery process has the following benefits:
- Automated software release product
- Enhanced developers’ productivity
- Early identification of bugs
- Fast updates delivery to the customers.
Apply automation tools
Manual deploying is an old-school approach that has already changed toward optimizing the workflow process. With new technologies and trends, software process automation has shifted the development quality and productivity paradigm.
With automated tools, the software release is amplified since automation allows developers to deploy tests, use code principles, and have all the scripts in version control, making deployment possible even for non-technical people. Deployment automation tools help reduce human errors, scale software delivery, streamline frequent and repeated processes, increase productivity, and foster fast and efficient deployment.
For example, with tools like Chef, Maven, Terraform, and AWS CodeDeploy, developers can facilitate easy and fast deployment with configuration and dependency management, use open-source infrastructures to manage hundreds of cloud services, and quickly release new updates without downtimes.
Deploy in small chunks and do it often
It is no secret nowadays that developers embrace Agile and Waterfall methodologies, according to which the development process lies in continuous iterations of unit tests. Deploying in small batch sizes, developers are empowered to make low-risk releases, fast delivery to users, and get quick feedback from them. You do not need to accumulate features that increase the release complexity and wait for their testing. Otherwise, if you deploy in big chunks, more features are developed, and you need to spend more time on testing and release.
Donald Reinersten explains in his book why and how deployment in small batches benefits developers’ efforts and increases ROI. To determine the optimal size for deployment, there should be a balance between transaction cost (the cost of deploying to the production) and holding cost (the cost of feature delay if not released earlier).
To learn how to handle smaller batches, dev teams must strive to lower transaction costs and frequently deliver new features to the end user. As mentioned above, such practices as continuous integration and delivery, automation tools, feature toggling, etc., and canary deployment should be the primary requirements for DevOps, who want to reduce risks and delivery lifecycle while accelerating feedback.After the initial deployment, we recommend monitoring the following:
- The server. It is essential to check the server performance (the percentage of CPU usage, used memory, disc storage utilization, network, and process utilization) by monitoring the availability of its resources. Also, monitor database instance activity and query behavior. The top server monitoring tools are Datadog, SolarWinds Server & Application Monitor, Nagios, and Zabbix.
- Monitor Exception Rates. Often, new errors (exceptions) never seen before will occur. Therefore, remember to apply an error tracking program allowing you to identify the mistakes and monitor them across all the servers. In addition, to ensure a smooth release, comparing your error rate before and after the deployment is good.
- KPIs. Once you set your KPIs, they should be monitored permanently so that you are aware of the performance of your software.
- Page load times depend on the volume of web traffic. To improve page loading speed and increase visitors’ engagement, reducing bounce rates and making web pages load quickly is essential. To measure page speed using Google PageSpeed Insights, GTmetrix, and YSlow.
Customer satisfaction metrics. CSTA score implies the percentage number of satisfied customers, which can be identified through surveys. There are such satisfaction metrics for your consideration: Net Promoter Score, customer acquisition score, customer satisfaction score, and customer effort score.
The “Big Bang” approach toward application deployment may cause a big fiasco for the project. Without a well-elaborated software deployment checklist, you expose your business to risk. Unfortunately, there is no rescue pill to release a successful product, but adhering to Agile approaches and automating your deployment processes can minimize issues for all stakeholders. Otherwise, businesses tend to experience slow deployment timelines and financial losses.
International Data Corporation (IDC) proves that unintended downtime during software deployment costs 1000 Fortune businesses between $1.25 billion to $2.5 billion annually. But how to avoid application deployment failures? The answer is to discover the faults in the early stages of product release. Applying novice practices and approaches can reduce the time and cost of fixing bugs.
Initial costs can be higher when implementing automation to your deployment processes; however, it’s not true since, in the long run, you will see a significant increase in your ROI. Furthermore, frequent deployments in small batches will avoid substantial losses. To evaluate all the risks and benefits of software and deployment methods, get in touch with our software expert.
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