Modern Software Development Lifecycle Techniques

When I started my web development business, (Bensoft) years ago, we used a software methodology called 4D. We divided each project into Discovery, Design, Development, and Deployment. It was great for breaking down billing and closing small development projects. While this was a good methodology for those smaller projects with a known end date, it doesn’t translate well to on-going projects with larger teams and larger scopes of work. A lot of smart minds have been focused on advancing software development techniques. This article will serve as an overview. I will dive into each component of the SDLC in separate articles.

The software development lifecycle (SDLC) has come a long way over the years, with numerous methodologies and tools emerging to streamline the process. This article explores the various stages of the modern SDLC and popular techniques used at each stage. We will also discuss popular methodologies such as “Given When Then,” DevOps, CI/CD, source code management, automated testing, Gitflow versus trunk code management, Kubernetes, and system reliability engineering.

  1. Planning

The planning stage involves gathering business requirements, defining objectives, user interface design, and outlining the scope of the project. Most of the project tickets are created in this phase. Using some form of Agile methodology to track the work from planning is the current de facto standard for modern SDLCs. Agile emphasizes iterative development and customer collaboration. Jira, Trello, and Asana are widely used project management tools that aid in organizing tasks, assigning responsibilities, and tracking progress.

  1. Coding

At the coding stage, developers write and modify the source code. Source code management (SCM) tools like Git, Mercurial, and Bazaar help developers manage code revisions and collaborate effectively. Two popular branching strategies are Gitflow and trunk-based development. Gitflow uses multiple branches to maintain feature development, releases, and hotfixes, while trunk-based development emphasizes a single branch with short-lived feature branches. trunk-based development is simpler and requires less maintenance and is quickly becoming the standard in many dev environments.

  1. Building

The building stage involves compiling the source code into a runnable application. Build automation tools like Apache Maven, Gradle, and Jenkins help automate the process and ensure a smooth transition from coding to testing. Continuous Integration (CI) is a practice where developers frequently integrate their code into a shared repository, allowing for early detection of integration issues.

  1. Testing

Testing is crucial to ensure the software meets quality standards and requirements. Automated testing tools such as Selenium, JUnit, and TestNG help developers create and execute test cases efficiently. The “Given When Then” methodology is a popular approach for writing acceptance tests, clearly defining preconditions, actions, and expected outcomes.

  1. Releasing

Releasing is the process of preparing the software for deployment. Continuous Delivery (CD) is a practice that ensures the software is always in a releasable state. Tools such as Jenkins, Bamboo, Github CI/CD, and GitLab CI/CD help manage the release process, automating tasks like packaging, testing, and deployment.

  1. Deploying

Deployment involves making the software available to users. Containerization tools like Docker and orchestration platforms like Kubernetes simplify the deployment process, enabling efficient scaling and management of application instances. System Reliability Engineering (SRE) is a discipline that focuses on ensuring high availability, performance, and resilience of deployed software.

  1. Operating

Operating is the stage where the software is actively used and maintained. DevOps is a popular methodology that brings together development and operations teams, ensuring efficient collaboration in managing, scaling, and maintaining the software. Tools like Ansible, Puppet, and Chef help automate various aspects of software operation.

  1. Monitoring

Monitoring is essential to track the software’s performance, identify issues, and ensure optimal user experience. Monitoring tools such as Prometheus, Grafana, and Elasticsearch help collect, visualize, and analyze performance metrics, enabling teams to identify and resolve issues proactively. Monitoring also involves customer feedback and requests which feed back into the planning phase as the software matures and evolves.

Modern software development lifecycle techniques have greatly improved the efficiency and quality of software projects. Embracing these methodologies and tools will help organizations stay competitive and deliver high-quality software at a faster pace. As the software development landscape continues to evolve, it is essential for professionals to keep up with the latest trends and best practices.

The advantages of Kubernetes

I had first heard about Kubernetes while working at Percona in 2015.  Raghu, one of the engineers on my team, was pretty excited about the technology and couldn’t stop talking about it.   Containerization being relatively then, it took some time for me to really grasp what the big deal was about.  Understanding its genesis from Google’s Borg and the paradigms it introduced into the world of containerized cluster management is very beneficial to grasping its advantages.

Kubernetes, also known as “K8s,” is a container orchestration platform that has taken the world by storm in recent years. It was first developed by Google, but it is now maintained by the Cloud Native Computing Foundation (CNCF), a nonprofit organization that focuses on open-source software for cloud computing.

In this article, we’ll explore the many benefits of Kubernetes and why it has become the de facto standard for managing containers in production environments.


One of the primary benefits of Kubernetes is its ability to scale applications easily. Kubernetes can quickly and automatically scale up or down based on the demand for resources. This makes it an ideal platform for applications that experience fluctuations in traffic or demand.

Kubernetes accomplishes this through the use of “pods,” which are the smallest deployable units in the platform. Pods can be replicated and scaled up or down as needed, and Kubernetes can manage the load balancing and traffic routing between them.


Kubernetes was designed to ensure high availability and reliability of applications. It achieves this through the use of “replication controllers” and “services.” Replication controllers ensure that a specified number of identical pods are running at all times. If a pod fails, the replication controller will automatically create a new one to replace it.

Services provide a stable IP address and DNS name for a set of pods, which allows them to be easily accessed by other pods or services within the cluster. This ensures that applications are always available and can be accessed reliably.


Kubernetes is a platform-agnostic tool, meaning it can be run on any cloud provider or on-premise infrastructure. This makes it easy to move applications between different environments without having to modify the underlying infrastructure or application code.

Kubernetes accomplishes this through the use of “abstractions” that hide the underlying infrastructure details from the applications. This allows applications to be deployed in a consistent manner across different environments, which makes it easier to manage them.


Kubernetes has several built-in security features that help ensure the security of applications running on the platform. For example, Kubernetes can isolate containers from each other and from the underlying host system, which helps prevent unauthorized access to sensitive data or resources.

Kubernetes also provides fine-grained access controls and role-based access control (RBAC) to help administrators manage user access to resources within the cluster. This helps ensure that only authorized users have access to sensitive data or resources.


Kubernetes is highly extensible, meaning it can be customized to meet the needs of different applications or environments. Kubernetes provides a robust API and a plug-in architecture that allows developers to extend the platform with new features or integrations.

Kubernetes also has a large ecosystem of third-party tools and services that can be used to enhance the platform. This includes tools for monitoring, logging, and debugging applications running on Kubernetes.


While not a silver bullet that solves all cluster scalability concerns, Kubernetes has become the de facto standard for managing containers in production environments due to its many benefits, including scalability, reliability, portability, security, and extensibility. With its rich feature set, Kubernetes provides a powerful platform for managing containerized applications in a variety of environments, making it an essential tool for any organization that is serious about cloud computing.