You might be wondering how DevOps fits into the standard software development life cycle (SDLC) if you’re utilizing one. Are there too many tensions for the two to coexist?
This article discusses how the two methods differ from one another.
What Exactly Is The SDLC?
To provide an organized and systematic approach to developing and managing an information system, the life cycle idea first surfaced in the 1960s. Early systems development initiatives, like Project LINCOLN and the SAGE program, comprised software and hardware development and the introduction of new computer memory technology.
Analysis, design, and development are only a few phases of the systems development life cycle, which describes stages and control actions. The entire life cycle encompassed all phases, starting from the system’s genesis and ending with its retirement.
Initially, the software development life cycle utilized the systems development life cycle for software initiatives. Many early software delivery models had a distinct phase-by-phase order, but the general idea remained unchanged.
The term “SdLC” is now broadly used to describe any software development process. We will adhere to the formal definition of the SDLC, which is a conventional staged method of software delivery since we cannot compare DevOps to every conceivable process, of which it is one. Looking to advance your career? Explore our DevOps Online Training and elevate your skills for success in today’s competitive landscape.
Why was The Software Development Lifecycle (SDLC) Established?
To comprehend the purpose of the SDLC, you must take a historical tour. Our software delivery history traces the advancement of development procedures starting in 1950. We discovered that a big part of what has changed is technology. Just as scientists are restricted by the tools at their disposal for their research, early coders were also constrained by the scarcity of machines, which were costly to operate, took a long time to build, and had few code editing capabilities.
Ad hoc code and repair methodology was used to construct systems before introducing the SDLC. The phased model addressed many of the issues that businesses faced at the time while developing huge applications despite the lack of established processes or controls and several technological constraints.
The SDLC resolved two different kinds of issues:
- Problems with the code’s scaling and the solution for large-scale systems
- particular time-related technical limitations
The Lincoln Laboratories at MIT produced the first phased model. Their methodology consisted of nine phases designed to directly address the issues that software teams were facing in the 1950s. This allowed them to share information about the system, scale their development efforts, and record mistakes so that current and potential contributors might learn from them.
Lincoln Labs employed the following phases:
- Plan of operations
- Specifications for the machine and its operations
- Program details
- Coding guidelines
- Coding
- Testing parameters
- Testing of assemblies
- Shakedown
- System assessment
There are numerous versions of the SDLC with distinct phases that evolved with the advancement of technology and business. Enroll now for DevOps Training in Pune and kickstart your journey to success.
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Why did SDLC Become A Problem?
Two reasons led to issues that surfaced during the SDLC:
- Phases of the SDLC have grown in terms of quantity and complexity for organizations.
- Better tools had not kept up with the SDLC.
When a set of phases and control steps is your primary tool for troubleshooting software delivery issues, you usually add more to fix most problems. Transaction costs increase for each software version as your process gets bigger. The cost of heavyweight procedures was rising as machines became more affordable and could compile data more quickly.
The original goals of the SDLC’s introduction were to address two issues:
- Increasing the size of software development to manage complex systems
- Particular time-related technical limitations
The technological constraints in 1990 were very different from those in 1960, even if the initial issue persisted. As technology progressed, the software development life cycle (SDLC) turned into a limitation on software delivery. When a company viewed the SDLC as a means of achieving process goals rather than organizational outcomes, it became an even bigger issue.
We learned from the SDLC that there might be too much process.
The interactions among risk, deployment frequency, and batch size are intricate. Until you release the software version to consumers, market risks persist regardless of how thoroughly you evaluate the system’s functional and quality attributes. A feature is only considered valuable when users are making use of it.
In automation economics, large batches also lead to a common error. Most people would have you either automate the jobs you perform most frequently or figure out how much work each task requires by multiplying its frequency with your manual labor.
This leads to a paradox because the labor-intensive and costly nature of the work is why you don’t do it frequently. While automation does cut down on manual labor, it also allows you to do things more often. Any automation economic model should take into consideration the following:
- A rise in frequency
- Better quality
- Reduced human error
- Lowering of the cost of delay
Apart from the change in technology limitations, a new competitive environment also arose, where sluggish businesses in responding to market demands lost out to quicker and smaller competitors.
At the moment, the SDLC was the best course of action. This software delivery method is no longer appropriate because of how much has changed.Update your skills with DevOps With AWS Training
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Traditional Software Development Life Cycle Challenges:
Every business need or story (in extreme programming) has an intriguing journey from requirements to production deployment, involving many human participation at various phases.
Even with risks recognized and minimized, predicting where a software project may go wrong is difficult. The general idea is to code it and then release it to the Operations team for installation after system and integration testing are complete.
If the Development team and Operations team are in perfect sync, everything can go smoothly, but more often than not, there are problems:
- When the operations team delivers it, there’s a chance that anything that worked in the development environment won’t function in the production setting. “It works just fine in development” is the typical reaction from the development team. Due to their differences or lack of periodic synchronization, these two environments cause the failure.
- Although new development tools speed up the coding process, the operations team may not always be able to keep up with the frequent releases and changes.
- Production servers may require specific OS or database adjustments. The deployment is in danger if knowledge or experience is deficient.
- Since developers typically cannot access production servers to monitor how an application is doing, they must rely on end-user input, which they rarely receive for apparent reasons.
- There may not always be explicit instructions or deployment information. The operations team has to adjust based on their expertise and experience—poor transition.
Companies may regret the difficulties of bridging the gap between the Operations team and the Developers when using standard SDLC methodologies; after all, production systems are always at risk.
These difficulties have a more significant effect on the organization’s budget, timeline, and reputation.
Lori MacVittie uses the butterfly effect to highlight the consequences of ignoring problems related to danger, money, and time to assist in explaining this complexity.Stand out with DevOps Foundation Certification
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DevOps Offers A Solution to Traditional Software Development
It appeared as though these difficulties would always be a part of the development process until Patrick Debios decided to address them.
The combination of Dev(elopers) and Op(erations)s resulted in the name “DevOps,” which was born out of this endeavor.
DevOps : It is a philosophy that seeks to introduce cultural change while delivering features more quickly and with more excellent quality. For regular deployments, it serves as a means of bridging the gap between the Operations team and the developers. You may refer to it as an “Elastic” deployment cycle or “Near Real-Time” development cycle because it allows you to deploy automatically once a developer commits a modification. When possible, as little human interference occurs. Adopting DevOps requires continual feedback, process improvement, and automation across the development life cycle.
The DevOps principles include the following:
- Provide systems for testing and development that are similar to those in production.
- Iterative and frequent deployments are required. Ascertain a dependable and replicable procedure.
- Maintain constant observation of and verification of operational quality attributes.
- Enhance the feedback loop.
Businesses are adopting DevOps with the use of automation tools. GitHub, Jenkins, Chef, Puppet, SaltStack, New Relic, Nagios, Ganglia, Munin, Splunk, Rundeck, and so forth are some examples of these tools.
Returning to our initial queries: Development Operations What has changed in it? Is it just a ploy for marketing? Is sledgehammering a fly to death?
Our releases are usually scheduled and released using a toolset; some may be automated, but they still require instructions to be entered. A tool alone would be meaningless, but DevOps can use it and integrate all automated technologies, from check-in to deployment.
Deployments that are frequent or continuous (e.g., ten a day) require dedication and discipline at all levels to be successful. Before deployment, the operations team and developers can hold war room sessions before deployment. What happens if the teams responsible for development and operations are located in different parts of the world, thousands of miles apart, making it challenging to hold phone conversations due to time differences? Some significant faults are either ignored or not resolved promptly as part of the operations team’s goal to keep the system down for the least time. Once implemented, DevOps can eliminate all of these issues and ensure a flawless deployment process.
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Does DevOps have A Software Development Lifecycle (SDLC)?
The traditional SDLC is no longer regarded as best practice. Large batches that are transferred between specialist teams are the usual outcome of traditional phased techniques. However, they can be avoided with caution. This doesn’t align with the DevOps methodology, which aims to decrease batch sizes and foster greater cross-disciplinary cooperation.
To work on stages like analysis, design, development, testing, and operations, you would divide 20 workers into 5 specialized teams using an SDLC. Similar to the baton in a relay race, these horizontal teams would carry out their specialized tasks by passing work from team to team.
DevOps would divide workers into four cross-functional teams to provide software without handoffs. Like the line of players in a rugby match advancing the ball towards the score line, each member of your vertical teams might provide and run an individual component.
Delivering software still requires completing several activities under DevOps and Continuous Delivery. You emphasized automating your deployment pipeline, forming independent vertical teams, and lowering batch sizes more than following an organized SDLC. It is possible to create a procedure that enhances the capabilities and culture of DevOps.
The Legacy of The SDLC
Some businesses view the SDLC as a cumbersome collection of stages and procedures that restrict software delivery and raise market risk. This is a regrettable unfavorable outcome of years of research.
The lessons we took away from the first forty years of software delivery should be the true legacy of the SDLC:
- It is best to work in small batches.
- You ought to deploy often.
- Create a modest, functional prototype first, then refine it.
- It’s feasible to overprocess something.
If you have the proper culture and capabilities and an automated deployment process, you should be able to release high-quality software versions on a regular basis. Do visit 3Ri Technologies
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The Bottom Line
Simply extend your current DevOps process to include the ideation phase when thinking about the software development life cycle. You should also consider software retirement a potential option when it becomes too valuable to maintain. Most of your work and resources will go toward the most crucial portion—the section in the middle where you continuously raise the software’s worth and enhance its functionality.
With changes to the underlying restrictions and competition, the conventional formal method based on the systems development life cycle is no longer suitable for software delivery.
