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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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Platform Engineering: Accelerating Development and Deployment

The software development landscape is evolving rapidly, demanding unprecedented levels of speed, quality, and efficiency. To keep pace, organizations are turning to platform engineering. This innovative approach empowers development teams by providing a self-service platform that automates and streamlines infrastructure provisioning, deployment pipelines, and security. By bridging the gap between development and operations, platform engineering fosters standardization, and collaboration, accelerates time-to-market, and ensures the delivery of secure and high-quality software products. Let’s dive into how platform engineering can revolutionize your software delivery lifecycle.

The Rise of Platform Engineering

The rise of DevOps marked a significant shift in software development, bringing together development and operations teams for faster and more reliable deployments. As the complexity of applications and infrastructure grew, DevOps teams often found themselves overwhelmed with managing both code and infrastructure.

Platform engineering offers a solution by creating a dedicated team focused on building and maintaining a self-service platform for application development. By standardizing tools and processes, it reduces cognitive overload, improves efficiency, and accelerates time-to-market.  

Platform engineers are the architects of the developer experience. They curate a set of tools and best practices, such as Kubernetes, Jenkins, Terraform, and cloud platforms, to create a self-service environment. This empowers developers to innovate while ensuring adherence to security and compliance standards.

Role of DevOps and Cloud Engineers

Platform engineering reshapes the traditional development landscape. While platform teams focus on building and managing self-service infrastructure, application teams handle the development of software. To bridge this gap and optimize workflows, DevOps engineers become essential on both sides.

Platform and cloud engineering are distinct but complementary disciplines. Cloud engineers are the architects of cloud infrastructure, managing services, migrations, and cost optimization. On the other hand, platform engineers build upon this foundation, crafting internal developer platforms that abstract away cloud complexity.

Key Features of Platform Engineering:

Let’s dissect the core features that make platform engineering a game-changer for software development:

Abstraction and User-Friendly Platforms: 

An internal developer platform (IDP) is a one-stop shop for developers. This platform provides a user-friendly interface that abstracts away the complexities of the underlying infrastructure. Developers can focus on their core strength – building great applications – instead of wrestling with arcane tools. 

But it gets better. Platform engineering empowers teams through self-service capabilities.This not only reduces dependency on other teams but also accelerates workflows and boosts overall developer productivity.

Collaboration and Standardization

Close collaboration with application teams helps identify bottlenecks and smooth integration and fosters a trust-based environment where communication flows freely.

Standardization takes center stage here. Equipping teams with a consistent set of tools for automation, deployment, and secret management ensures consistency and security. 

Identifying the Current State

Before building a platform, it’s crucial to understand the existing technology landscape used by product teams. This involves performing a thorough audit of the tools currently in use, analyzing how teams leverage them, and identifying gaps where new solutions are needed. This ensures the platform we build addresses real-world needs effectively.

Security

Platform engineering prioritizes security by implementing mechanisms for managing secrets such as encrypted storage solutions. The platform adheres to industry best practices, including regular security audits, continuous vulnerability monitoring, and enforcing strict access controls. This relentless vigilance ensures all tools and processes are secure and compliant.

The Platform Engineer’s Toolkit For Building Better Software Delivery Pipelines

Platform engineering is all about streamlining and automating critical processes to empower your development teams. But how exactly does it achieve this? Let’s explore the essential tools that platform engineers rely on:

Building Automation Powerhouses:

Infrastructure as Code (IaC):

CI/CD Pipelines:

Tools like Jenkins and GitLab CI/CD are essential for automating testing and deployment processes, ensuring applications are built, tested, and delivered with speed and reliability.

Maintaining Observability:

Monitoring and Alerting:

Prometheus and Grafana is a powerful duo that provides comprehensive monitoring capabilities. Prometheus scrapes applications for valuable metrics, while Grafana transforms this data into easy-to-understand visualizations for troubleshooting and performance analysis.

All-in-one Monitoring Solutions:

Tools like New Relic and Datadog offer a broader feature set, including application performance monitoring (APM), log management, and real-time analytics. These platforms help teams to identify and resolve issues before they impact users proactively.

Site Reliability Tools To Ensure High Availability and Scalability:

Container Orchestration:

Kubernetes orchestrates and manages container deployments, guaranteeing high availability and seamless scaling for your applications.

Log Management and Analysis:

The ELK Stack (Elasticsearch, Logstash, Kibana) is the go-to tool for log aggregation and analysis. It provides valuable insights into system behavior and performance, allowing teams to maintain consistent and reliable operations.

Managing Infrastructure

Secret Management:

HashiCorp Vault protects secretes, centralizes, and manages sensitive data like passwords and API keys, ensuring security and compliance within your infrastructure.

Cloud Resource Management:

Tools like AWS CloudFormation and Azure Resource Manager streamline cloud deployments. They automate the creation and management of cloud resources, keeping your infrastructure scalable, secure, and easy to manage. These tools collectively ensure that platform engineering can handle automation scripts, monitor applications, maintain site reliability, and manage infrastructure smoothly.

The Future is AI-Powered:

The platform engineering landscape is constantly evolving, and AI is rapidly transforming how we build and manage software delivery pipelines. The tools like Terraform, Kubecost, Jenkins X, and New Relic AI facilitate AI capabilities like:

  • Enhance security
  • Predict infrastructure requirements
  • Optimize resource security 
  • Predictive maintenance
  • Optimize monitoring process and cost

Conclusion

Platform engineering is becoming the cornerstone of modern software development. Gartner estimates that by 2026, 80% of development companies will have internal platform services and teams to improve development efficiency. This surge underscores the critical role platform engineering plays in accelerating software delivery and gaining a competitive edge.

With a strong foundation in platform engineering, organizations can achieve greater agility, scalability, and efficiency in the ever-changing software landscape. Are you ready to embark on your platform engineering journey?

Building a robust platform requires careful planning, collaboration, and a deep understanding of your team’s needs. At Mantra Labs, we can help you accelerate your software delivery. Connect with us to know more. 

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