Software deployment pillars the software development life cycle (SDLC). It links users and developers, making it possible to gather and use feedback fast. This feedback loop raises software's quality, usability, and scaling propensities.
However, software deployment is challenging and requires careful planning and strategy. As a result, the deployment process's design has to be carefully considered. The effectiveness of the planning phase may determine whether a deployment is successful or unsuccessful.
”Your solution doesn’t work till others can use/tinker with it. Deployment enables that.”
In this article, I delve into the specifics of the planning stage of software deployment and provide an accurate walkthrough of everything that must be established. Although there are many different deployment methodologies, the DevOps methodology is the focus of this article.
Software deployment is the method by which applications, modules, updates, and fixes are distributed from developers to target environments. Pushing software into target environments entails actions that increase functionality, such as system management and operations. Deployment is the anti-penultimate stage of the SDLC.
Software production is frequently confused with software deployment. Although used synonymously, they have different meanings. Software production is more comprehensive; it involves several activities, including code and build development and deployment.
Software deployment is an amalgam of numerous activities that can be summed into five major headings:
Planning Deployment: Adequate planning is the primary driver of successful software deployment. This article explains that.
Verifying service components
Verifying target environments: Depending on your operating system and the size of your project, there are different ways to verify target environments. No matter the operating system, you must configure and create a target connection between your local machine and your target environment before deploying the software package to the target to carry out your planned functions.
For instance, on Linux, you can configure and set up a target connection using a real-world NFS target networking environment, an emulated target environment, or a flash development environment. To ensure that the software functions correctly in the target environment, dependencies are also installed during this phase.
Executing deployment: For DevOps, this is the phase of implementation of DevOps’ principles like all-around automation, CI/CD, etc.
Confirming deployment: More than deployment is required. Confirmation is essential to ensure that the software package has been successfully deployed.
Adequate planning facilitates the convergence of all parties involved in the software deployment process into a single source of truth and improves communication. Good planning has implementation-based advantages as well as corporate or organizational advantages.
In this article, I divided the planning process into two main functions: managerial and engineering activities.
The engineering team generated the code, versioned it in the most practical format, and prepared the package for distribution because they are the software's backbone. The technical department must cater to six components: frontend, backend, monitoring, CI/CD, data storage, and security.
Prepare your software package for deployment by doing the following:
Minify CSS and JavaScript files, and compress images to reduce the number and size of files your software has to load when deployed.
Configure a content delivery network (CDN) to reduce network latency. When a user initially requests access to your software, a CDN server guarantees that the files are transferred from the origin server, a copy of the assets is cached on the edge server, and the data is reused for subsequent requests.
Users may get your application more quickly in this fashion, and your deployment host won't become overloaded with requests.
Configure cache busting by versioning your files when they’re updated. Cache busting guarantees that the most recent updates to your software are generated and immediately made publicly available. Three techniques exist for performing cache busting:
While the first two techniques are hitch-free, cache busting using a query string may present a number of issues, especially when used with a CDN.
On the backend, ensure the following:
To ensure that your software has sufficient resources, configure your virtual machines, HDD, CPU, and RAM.
If your software is running on EC2, ensure to build an Amazon machine image (AMI). An AMI enables you to create virtual servers — e.g., EC2 instances — inside the AWS infra. You can easily create an AMI from an EC2 instance, register the machine image, and search for it when you need to launch new instances.
If containerization is employed, prepare and push your images to the container registry. You can simply do this using the `$ docker push` command. The docker documentation portal contains comprehensive details on
If your software is packaged as microservices, configure a container orchestrator.
Set up relational databases.
Set up queue systems to reduce the server and data volume.
Run schema migration. Schema migration auto-updates your database scheme per every change in your codebase.
Set up file storage: Where will files generated during app usage be stored? Configure tools, like
For the security of your software,
To encrypt your server connection, obtain and configure SSL certificates.
Configure static code analyzers to uncover security risks in your codebase or dependencies.
CI/CD is the cornerstone of the DevOps methodology. Ensure the following:
Create a deployment pipeline using a version control system (VCS) like
Write test scripts and run automated tests. The cornerstone of DevOps is automated testing, and technologies like Lambdatest, TestSigma, and others that are available right out of the box let you execute automated tests in parallel across several environments.
There are three ways to construct a test script: using data scripting, using a programming language, or using the record/playback approach. Scripts often include a set of instructions that detail the software functionalities that must be tested as well as the direction in which you want the automated testing to go.
Set up static code analyzers. Based on pre-established principles, static code analysis tools analyze your code, format, and lint. This makes it possible to guarantee that the code adheres to current standards.
Set up deployment environments. Depending on the purpose of your deployment, you could either set up an ephemeral or permanent environment. Aptible’s hosting platform automates the work of provisioning, managing, and scaling infrastructure, so I recommend Aptible here.
Use a load balancer to create a zero-downtime deployment strategy. A load balancer serves as the "traffic cop" in front of your servers, distributing client requests across all servers equipped to handle them in a way that maximizes speed and capacity utilization. The load balancer routes traffic to the active servers in case one server goes offline.
The load balancer initiates requests to a new server when it is added to the server group. By distributing requests only to servers that are active, a load balancer assures high availability and dependability and offers the flexibility to add or remove servers as needed. Your future scaling problems are made easier by this.
Set up log management systems to gain first-hand access to information useful in improving the deployment process. Gathering and utilizing the reports generated by the log management systems is a core component of observability, which makes your pipeline more intelligent and fool-proof.
Using tools like
Along with the engineering operations, a number of other essential activities include:
Setting key performance indicators (KPIs): Team members should be familiar with both successful and unsuccessful deployment processes before deployment. The modern implementation of the DevOps deployment methodology requires that team members track the performance of the deployed software using different KPIs.
These KPIs enable the team to assess the progress or failure of the deployment. However, despite their importance, only a few teams monitor their deployment through KPIs.
These KPIs include deployment frequency, failed deployment rate, change volume, memory use, CPU utilization, downtime during deployment, page load time, mean time to recovery (MTTR), error frequency, and many others.
Preparing a task list: The deployment must be carried out step-by-step and under control, allowing you to decide whether to move forward at each checkpoint. Therefore, activities set to our current checkpoint can be worked on using resources, but tasks that come after the checkpoint cannot. Hence, the next set of functions is released when the checkpoint has been passed OK. Below is an example of a task list:
The success of software deployment depends on how well the planning stage, which comes before actual deployment, is executed. Planning, therefore, requires a lot of thought and attention to detail.
The intricate details of the software deployment planning phase have been covered in full in this article. You are prepared to deploy if you have it in your arsenal!