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How is Automation Testing Effective in Defect-Free Delivery?

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Testing is a method to validate if the delivered product is developed as per the requirement and if the expected functionality is achieved. There are two types of testing methods namely Manual and Automation.

Manual testing is validating manually for defects in the developed product. This requires time and more resources and delays the testing process as well. 

Automation Testing is a process where the product is tested using scripts, testing tools, or any framework to minimize manual intervention, human errors, and time. This is the best way to deliver the developed product in a short duration. But how is automation testing effective in Defect-Free Delivery? 

In this article, we will talk about the pros and cons of automation testing and delivering the developed product defect-free.

Automation Testing could be utilized to carry out Regression Testing, Load Testing, Performance Testing, and Repeated Execution for faster results.

It does not serve as a substitute for manual testing since some testing types, such as exploratory testing, usability testing, and ad-hoc testing, require manual verification to get the best results.

Why Automation Testing?

  • It is less time-consuming.
  • A list of consecutive sets of test cases called suites can be developed and executed any number of times.
  • On Regression testing, human error is eliminated.
  • Automation testing is best for Load and performance testing and repeated testing.
  • It is best for optimized use of the test scripts for different versions of the application.
  • Can be done even when a small modification is done to code on test suite execution.

Automation Testing Vs. Manual Testing

Automation testing is not required in all places, the decision has to be taken when to use manual or automation. When there is repeated testing of the scenarios to reduce repeated manual effort on execution, automation testing is required and when there is less repetition and the scripting takes a huge effort, then manual testing is the best.

Pros of Automation

  • Can be done to run repeated testing
  • Execution can be performed for the same scenario but with different inputs
  • Execution can be performed in various triggering points at the same time
  • To increase the accuracy and for quick test results.

Cons of Automation

  • Automation takes more effort in the beginning
  • There are some factors like visual appearances that cannot be automated
  • Maintenance of scripts is required when any updation takes place

Pros of Manual

  • Team interaction improvises between developers and testers.
  • Best suited for Ad-hoc testing

Cons of Manual

  • Requires more human resources
  • Delayed results in case of repeated testing
  • More occurrences of human errors
  • Depends on the resources’ presence while executing. 

Types of Automation Testing

  • Keyword-driven testing.
  • Integration testing.
  • Unit testing.
  • Smoke testing.
  • Regression testing.
  • Performance testing.
  • Security testing.
  • Data-driven testing.

Test automation life cycle

There are many phases/steps involved in the automation test life cycle:

  • Test planning
  • Analyse application under test
  • Setup test environment
  • Develop test scripts
  • Enhance test scripts
  • Debug the tests
  • Execute the tests
  • Analyze the test results
  • Defects/Reports

Implementing A Test Automation Strategy 

  • Define the Scope Of Automation
  • Decide On Testing Approach
  • Select A Test Automation Framework
  • Choose The Automation Tool To Use
  • Test Execution
  • Test Automation Maintenance 

Conclusion

Automation testing reduces time, and resources and also provides accurate results.

While it may help organizations deliver a great product defect-free and stay competitive, it has its own challenges. It can be difficult at first, but with the appropriate procedures and actions, it could be implemented successfully.

About The Author: 

Saranya N S is currently working in Mantra Labs as a QA manager. She has experience in multiple domains like telecom, IVR, and BFSI and is passionate about creating automation testing frameworks.

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Why Netflix Broke Itself: Was It Success Rewritten Through Platform Engineering?

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Let’s take a trip back in time—2008. Netflix was nothing like the media juggernaut it is today. Back then, they were a DVD-rental-by-mail service trying to go digital. But here’s the kicker: they hit a major pitfall. The internet was booming, and people were binge-watching shows like never before, but Netflix’s infrastructure couldn’t handle the load. Their single, massive system—what techies call a “monolith”—was creaking under pressure. Slow load times and buffering wheels plagued the experience, a nightmare for any platform or app development company trying to scale

That’s when Netflix decided to do something wild—they broke their monolith into smaller pieces. It was microservices, the tech equivalent of turning one giant pizza into bite-sized slices. Instead of one colossal system doing everything from streaming to recommendations, each piece of Netflix’s architecture became a specialist—one service handled streaming, another handled recommendations, another managed user data, and so on.

But microservices alone weren’t enough. What if one slice of pizza burns? Would the rest of the meal be ruined? Netflix wasn’t about to let a burnt crust take down the whole operation. That’s when they introduced the Circuit Breaker Pattern—just like a home electrical circuit that prevents a total blackout when one fuse blows. Their famous Hystrix tool allowed services to fail without taking down the entire platform. 

Fast-forward to today: Netflix isn’t just serving you movie marathons, it’s a digital powerhouse, an icon in platform engineering; it’s deploying new code thousands of times per day without breaking a sweat. They handle 208 million subscribers streaming over 1 billion hours of content every week. Trends in Platform engineering transformed Netflix into an application dev platform with self-service capabilities, supporting app developers and fostering a culture of continuous deployment.

Did Netflix bring order to chaos?

Netflix didn’t just solve its own problem. They blazed the trail for a movement: platform engineering. Now, every company wants a piece of that action. What Netflix did was essentially build an internal platform that developers could innovate without dealing with infrastructure headaches, a dream scenario for any application developer or app development company seeking seamless workflows.

And it’s not just for the big players like Netflix anymore. Across industries, companies are using platform engineering to create Internal Developer Platforms (IDPs)—one-stop shops for mobile application developers to create, test, and deploy apps without waiting on traditional IT. According to Gartner, 80% of organizations will adopt platform engineering by 2025 because it makes everything faster and more efficient, a game-changer for any mobile app developer or development software firm.

All anybody has to do is to make sure the tools are actually connected and working together. To make the most of it. That’s where modern trends like self-service platforms and composable architectures come in. You build, you scale, you innovate.achieving what mobile app dev and web-based development needs And all without breaking a sweat.

Source: getport.io

Is Mantra Labs Redefining Platform Engineering?

We didn’t just learn from Netflix’s playbook; we’re writing our own chapters in platform engineering. One example of this? Our work with one of India’s leading private-sector general insurance companies.

Their existing DevOps system was like Netflix’s old monolith: complex, clunky, and slowing them down. Multiple teams, diverse workflows, and a lack of standardization were crippling their ability to innovate. Worse yet, they were stuck in a ticket-driven approach, which led to reactive fixes rather than proactive growth. Observability gaps meant they were often solving the wrong problems, without any real insight into what was happening under the hood.

That’s where Mantra Labs stepped in. Mantra Labs brought in the pillars of platform engineering:

Standardization: We unified their workflows, creating a single source of truth for teams across the board.

Customization:  Our tailored platform engineering approach addressed the unique demands of their various application development teams.

Traceability: With better observability tools, they could now track their workflows, giving them real-time insights into system health and potential bottlenecks—an essential feature for web and app development and agile software development.

We didn’t just slap a band-aid on the problem; we overhauled their entire infrastructure. By centralizing infrastructure management and removing the ticket-driven chaos, we gave them a self-service platform—where teams could deploy new code without waiting in line. The results? Faster workflows, better adoption of tools, and an infrastructure ready for future growth.

But we didn’t stop there. We solved the critical observability gaps—providing real-time data that helped the insurance giant avoid potential pitfalls before they happened. With our approach, they no longer had to “hope” that things would go right. They could see it happening in real-time which is a major advantage in cross-platform mobile application development and cloud-based web hosting.

The Future of Platform Engineering: What’s Next?

As we look forward, platform engineering will continue to drive innovation, enabling companies to build scalable, resilient systems that adapt to future challenges—whether it’s AI-driven automation or self-healing platforms.

If you’re ready to make the leap into platform engineering, Mantra Labs is here to guide you. Whether you’re aiming for smoother workflows, enhanced observability, or scalable infrastructure, we’ve got the tools and expertise to get you there.

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