Top business benefits enterprises can achieve by implementing CI/CD pipeline

Top business benefits enterprises can achieve by implementing CI/CD pipeline

In conventional software development processes, releases recur at regular intervals for every small feature update.  The chances of integration at the time of deployment increases in these approaches. Eventually, the problem starts to grow, leaving more challenges for the whole team because of the manual processes. It becomes more prone to human error. CI/CD solves all these issues and makes the entire process more efficient and manageable.

Continuous Integration/Continuous Deployment (CI/CD) is the pillar of developing, testing, and implementing applications to production in present-day software development practices. CI/CD plays a vital role in assisting development and many other teams. CI reduces the risks and allows production consistency by automating multiple code changes from different project developers. And also, CD enables developers to provide the integrated code to production smoothly. It delivers a fast and efficient automated process to release new features and updates to clients without hurdles.

CI/CD has now become an essential part of modern software development approaches. This article analyses the top benefits of the CI/CD pipeline.

Easy Code Integration

One of the technical benefits of continuous integration and continuous delivery is that it enables you to integrate small pieces of code quickly. These code modifications are easier to manage. Also, it contains fewer issues that may require a fix at a later date.

 As soon as the code is pushed into the code repository, the testing starts using continuous testing. This allows developers to understand the problem before the completion of so much work. The communication between the teams gets improvised by this methodology. It is suitable for larger development teams who work remotely and those who work in-house.

Reduced Changes & Review Time

Code modifications done in such an environment minimizes the risk of unexpected consequences.  The changes are easy to manage and fix if any issues pop up.  Once integration takes place, using CI/CD, one can test these code changes rapidly. This methodology is very beneficial when direct communication is not possible or when teams work across remote locations.

Faster Bug Detection and Easier Implementation

Fault isolation defines the practice of designing systems. When an error occurs, the negative results are limited in scope. Limiting the range of issues minimizes the potential for damage and makes systems more comfortable to maintain.

 CI/CD ensures faster fault isolation to detect and easier implementation. Fault isolations comprise monitoring the system, finding when the fault occurred, and triggering its location.  Thereby, it reduces the bugs occurring in the application.

Improves Test Quality

CI/CD enhances the test reliability and quality because of the bite-size and specific changes implemented to the system. It allows teams to perform more accurate positive and negative tests. CI/CD produces continuous reliability through test reliability. 

Rapid Release Rate 

It detects failures quicker and repairs faster, which leads to increased release rates. But, frequent releases are possible only if the code is generated in a continuous operational system.

CI/CD often merges codes, continuously deploys them to production after complete testing, and keeps the code in a release-ready state. It’s crucial to have an environment set up that is used by the end-users. Containerization is one of the best methods to test the code in a production environment. 

Reduces Defects

Incorporating CI/CD into your company’s development process minimizes the number of critical and non-critical defects in your backlog. These small defects are identified before production and fixed before the release.

There are several advantages to solve non-critical problems. For instance, your developers have sufficient time to focus on huge issues and enhancing the system. Testers can concentrate less on small issues so they can identify big problems before the release.

Keeps Your Product Up-To-Date

Focus on the first impressions as they are vital to turning new customers into happy customers. Make your clients happy with new features and bug fixes. Using a CI/CD methodology also keeps your product up-to-date with modern technology and enables you to get new customers with positive reviews.

 Adding new features and modifications into your CI/CD pipeline based on how your customers use the product will allow you to retain existing users and gain new customers.

Continuous Feedbacks

CI/CD is the best way to get continuous feedback from your clients and your team. This improves the transparency of any problems in the team and encourages responsibility. CI concentrates on the development team. This part of the pipeline’s response impacts build failures, design issues, merging problems, etc. CD focuses more on releasing the product quickly to the end-users.

Cost-effective

Automation in the CI/CD pipeline minimizes the number of defects or bugs that occur in CI and CD steps. This reduces the developer’s time and effort and also minimizes the cost. The other benefit is, it increases the code quality with automation and increases your ROI.

Conclusion

Upon knowing the top benefits of implementing a CI/CD pipeline, it is time to make a move. If you are thinking about executing a CI/CD pipeline, you can move forward. It automatically increases the speed and the quality of your releases. These benefits lead to minimized costs and better ROI. Enterprises can spend more time building better products when implementing Selenium test automation with CI/CD.

Share on facebook
Facebook
Share on twitter
Twitter
Share on linkedin
LinkedIn

AI and Digital Transformation: 4 Ways to Greater Automation

AI and Digital Transformation: 4 Ways to Greater Automation

The initial phase of digital transformation is still an ongoing process for many enterprises, centering around the digitalization of products, services, and business processes. The second phase uses AI to enhance the quality of decision-making, strengthen the relationships with customers, and optimize organizational productivity. 

While various enterprises are at various stages of maturity of digital transformation, many companies have already been experimenting with AI separately to discover how it could benefit the business in the second phase of digital transformation.

One of the crucial reasons for the second phase of digital transformation’s unsymmetrical results is the understanding or lack of knowledge of what Artificial Intelligence can do. There has been a general illusion that artificial general intelligence (AGI) can solve any issue when truly artificial narrow intelligence (ANI) is the ultra-modern.

AI in Digital Transformation

The digital transformation journey has crossed from digitization to digitalization. It also covers different data technologies across various industry verticals. To the extent that data-driven innovations are helping to manifest several advances in digital technologies as actionable, the next boundary in re-molding enterprises is AI transformation. Progression in AI is forcing digital enterprises toward becoming intelligent enterprises. AI technologies are already revolutionizing not just how we recognize and do business, but also the business environment and its’ overall landscape.

1.Augmented Analytics

Business intelligence is going far beyond dashboards. AI and machine learning are becoming a much more user-friendly process for inexperienced workers as augmented analytics are embedded into platforms.

Organizations are struggling to get their data management and machine learning practices up. This is where augmented analytics are arriving at the rescue. What’s more, it could also help with utilizing machine learning for production purposes, which has been a problem for many enterprises.

The benefits of this have the potential to extend far beyond business intelligence. The passion for implementing AI in enterprises was high at the initial stage. By adding automation to parts of business operations, such as data pipelines and data management, augmented analytics can be one of the elements of the solution to acquiring AI into enterprise production.

2.Automation

Automation has moved past the workforce to white-collar tasks that are repetitive. Just like with some robotic process automation (RPA) tools and chatbots, several automated systems are not necessarily “intelligent” because they are inevitably programmed. i.e., a given input produces a given output. AI enlarges the scope of what automated systems can do and moves enterprises to the second phase of digital transformation.

3.Customer Engagement and Resources

More than half of organizations acknowledge not having a formal customer engagement program established. Because of this, those organizations had no grasp on the number of customers they’d actually lost in a one year period. On the other hand, most customers expect a consistent experience wherever they engage. Digital transformation using AI can help optimize customer engagement by dynamically aligning the website content with the customer’s preferences.

4.AI-Digitized supply chains

AI solutions and tools help analyze large datasets in real-time, plan production efficiently, balance supply and demand gaps, schedule factory activities effectively, and develop error-free SCM plans and strategy. AI can also help estimate the market requirement and manage production accordingly to avoid overproduction or shortage of products, either of which would result in loss.

Conclusion

The future of connected digital transformation includes more IoT and industrial IoT devices and the coordination of AI.

IoT and IoT devices are already offering businesses the clarity at the edge, which they lacked before. When combined with AI, the sensors are helping to change the ways companies operate to yield optimization.

Enterprises with and without AI-enabled digital transformation models may adopt some AI by default because it has been embedded in the software tools, applications, and platforms they already utilize. Data scientists should aim to solve complex issues and bring more value from AI in the second phase of digital transformation. Simultaneously, citizen developers (power users) can tackle easier problems, such as optimizing business processes and tasks within their department.

Share on facebook
Facebook
Share on twitter
Twitter
Share on linkedin
LinkedIn

Automation testing for a Leading Finance/Insurance company operating across USA

Case Study

Automation testing for a Leading Finance/Insurance company operating across USA

Whom we worked with

A top-tier insurance company that offers financial products and services including life insurance, annuities, mutual funds, disability income insurance, credit union products, retirement planning, and more.

Our Solution

  • Developed a framework to integrate with Test Management tool ALM
  • Created a completely new documented business process
  • Designed test plan and roadmap with milestones and estimates

Challenges

  • Lack of dedicated QA team with the client to support the automation script development
  • Integration of Selenium Framework with ALM/QC
  • Automating mainframe applications

Impact

  • Replaced 90% of manual validation with Test Automation
  • With one button click, they are able to validate applications after monthly patches deployed
  • After Test execution test results were reported in HTML files and these reports are emailed to all asset owners automatically
  • Reduced 70% of maintenance effort for Test automation scripts and provided 100% customizable test report
  • Saved Millions of Dollars in Testing costs by eliminating all manual effort

How we helped

  • Sun Technologies designed a high-level test plan which provided visibility on effort estimation, deliverables, and test approach
  • We developed a Robust Automation framework using Selenium which would allow triggering test execution from ALM which reduced 80% of manual effort
  • Automated the complex scenarios of 20 Mainframe applications
  • Accomplished an optimal level of automation for their 300+ applications in Production and Test environments
  • Test Automation replaced 90% of manual validation during monthly patch releases this helped the client in saving millions of dollars of testing costs by eliminating manual efforts.
  • Test automation scripts are used in daily batch executions to ensure all the 300+ applications are up and running
  • We have taken additional responsibilities with Release Management to assist the process to become more robust