5 Ways Cloud DevOps Can Transform the SDLC

SDLC or the Software Development Life Cycle defines the stages software projects go through, from planning and design to build, test and deployment. The more popular SDLC models include the waterfall model, the spiral model, and the Agile model.

In this article we’ll cover the common SDLC stages and how to automate them using modern CI and cloud computing technology.

Understand SDLC Basics - The stages of SDLC and Cloud Best Practices

Following are some of the best practices and stages of SDLC that ensures that the process works in an efficient, smooth, and productive manner.

Identifying current problems

This stage of SDLC involves constructive input from stakeholders including customers, industry experts, salespeople, and programmers. Understand the strengths and weaknesses of the existing system with the goal of being an improvement.

Planning

Here the team lays down the requirements of the new software and identifies the resources and cost required. It also lists down the risks and provides methods for softening of those risks. A Software Requirement Specification document is created at this stage. The Cloud DevOps team should have a say in the discussion because getting the cloud architecture right will help you save a lot of time in the future.

Design

This phase of SDLC is initiated by converting the software specifications into a design plan known as the Design Specification. Each stakeholder reviews this plan and offers suggestions and feedback. A failure at this stage will most certainly result in added cost at best and complete collapse of the project at worst.

Build

During this stage of SDLC, software is developed by generating all of the actual code. In case the previous steps have been closely followed, this can prove to be the least complicated step. The build should cover all the costs and other stuff. Developers are now responsible for adding the entire development & build process.

We also see the value of shifting left. When development and Ops teams use the same toolset to track performance and pin down defects from inception to the retirement of an application, this provides a common language and faster handoffs between teams.

Test

During this stage, developers can test for defects as well as deficiencies. These issues are fixed until the product is in line with the original specifications. Testing shouldn’t just be limited to functional bugs and unit testing. You should also focus on non-functional testing like API testing, load testing and security testing.

Organizations are adopting a DevSecOps mentality, realizing that a secure SDLC is an effective SDLC. Since applications built today rely on lots of open source dependencies, it’s a good idea to verify that the dependencies are stable and bug free. You can add a plugin that scans your codebase against vulnerability databases like NVD/CVE etc to ensure that open source components are secure.

With the cloud, you can run your tests on a universal testing server. This keeps everyone using the same test toolset across the entire test lifecycle.

Deploy

A widespread occurrence is that this part of the SDLC process takes place in a limited way to start with. Based on user feedback, additional adjustments can be implemented. Deploying to the cloud is usually easy and can be automated. For example, cloud vendors offer CLI support for creating and deploying server instances.

Maintain

When the plan meets reality, it almost never turns out to be perfect. As conditions change in the real world, developers are required to update and advance their software to keep pace with the change.

Easy and Efficient Automation

The effort of automating processes by leveraging the cloud assists in enhancing the pace of automation and results in the process is more reliable, robust, error-free, and efficient. This ultimately leads to a reduction in time to market.

Let’s take the case of a modern web application. You can automate most of the tasks using a combination of a source version control tool and a distributed CI app. Since the data is hosted on the cloud, you can set up your CI in the cloud rather than running it the traditional on-premise way. Furthermore, you can deploy development, test and production builds with ease. When new tagged commits are made, the tests can be executed on a build running on a cloud instance.

Cloud Server Replication

Each cloud provider contains some form of backup mechanism. Despite this, there is a requirement to launch servers manually while restoring the backup in a completely different environment. DevOps allows this process to be quickly and efficiently automated.

If you’re using an object storage like Amazon S3, Amazon automatically creates redundant copies. Objects are redundantly stored on multiple devices across multiple facilities in an Amazon S3 region. This is true for object storage across all other vendors including Azure and GCP.

For virtual machines and compute instances, you can automatically create snapshots of your data so that you can retrieve it back any time.

Orchestration & Effective Monitoring

The orchestration is a specialized method of automation. Orchestration comes with complete coordination as well as control in automation that can cover the entire hierarchy in a particular infrastructure.

Orchestration tools like Chef, Puppet, and Ansible are few of the creative tools available in the market. These are independent of cloud providers and have inbuilt, pre-defined standards, but can also be quickly integrated with all leading cloud providers in the market today.

Cloud providers have an aim to provide all cloud services tools at a centralized place. These services can be categorized as monitoring services, backup services, automation services, acknowledgment services or infrastructural services.

Rapid Deployment

Cloud providers can assist users with rapid deployment; however, customization is challenging if DevOps is missing. DevOps is focused on finding solutions to infrastructural problems using the latest tools and building custom logic and writing capabilities.

DevOps assists in the automation of the complete process using single-click build tools that can interact with the relevant cloud services and complete tasks without any errors.

To take an example, continuous integration tools like Bamboo and Jenkins can help in the building of the following flow:

• Trigger the build when the new code is pushed and available to the version control system
• Pull the latest code from the version control system
• Execute automation test cases to check for code sanity
• Design and build deployable artifacts just in case the test cases passed
• Triggering deployment on staging environments
• Automating the testing execution on the staging environment
• Promoting well-tested code to the production environment

Conclusion

Each of the SDLC steps we described can be automated to minimize human intervention. The cloud, together with the DevOps paradigm, is making it possible to automate development pipelines in ways never thought possible. This is making the SDLC faster, more efficient, and supportive of the Agile holy grail of continuous product improvement.