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Post Category: Blog

Improving Payment Gateway Integration: Real-World Experience

Posted on by Layana Chandran

Executive Summary

Scalable payment gateway integration for SaaS & marketplaces with secure APIs, split payouts, real-time webhooks & PCI compliance for seamless user experience.

In today’s digital-first world, payment processing is not just a back-end function but a vital part of building user trust, scalability, and operational efficiency. Whether creating a SaaS product, marketplace, or on-demand service platform, integrating a payment gateway effectively can significantly influence customer experience and business success.

In one of our recent projects, we were tasked with integrating a secure, scalable, and intelligent payment solution into a multi-user platform. The system required real-time payments, automated vendor payouts, recurring billing, and full compliance with modern financial regulations.

Benefits of Thoughtful Payment Gateway Integration

Our solution improved both the vendor and user experience by enabling features like next-day payouts, automated fund splitting, and real-time transaction notifications. Users enjoyed a smooth checkout process while vendors received quicker access to their earnings. Through the use of webhooks, we were able to achieve real-time visibility of key events such as transaction success, failure, refund initiation, or payout status. This kept our system up to date and ensured users always saw accurate payment statuses.

For multi-vendor platforms, managing individual accounts, tracking commissions, and ensuring compliance can be complex. By integrating sub-account features through the gateway’s API, we automated vendor onboarding and eliminated manual overhead, streamlining the process.

The payment provider’s well-documented API allowed us to integrate quickly and efficiently. Its clarity reduced trial-and-error in the development process, helping us deliver the solution on time.

Real-World Use Case: Marketplace with Split Payments

In this project, we developed a service platform connecting individual vendors with consumers. The payment logic had to handle several processes, such as direct customer payments to the platform, automated commission deductions, payout distribution to vendors, recurring billing for subscriptions, and refund handling.

The payment gateway’s API enabled us to manage payment intents, set dynamic split rules for each transaction, verify vendors programmatically, and track every transaction lifecycle using webhook events. For customers, it meant a fast and simple checkout experience. For admins, the process was automated and scalable, providing effortless backend management.

Challenges We Encountered

One major challenge was ensuring the system adhered to security and compliance standards. We followed PCI-DSS guidelines, ensured encrypted communication with SSL/TLS, and managed tokenised storage to avoid handling raw card data directly.

Additionally, we faced some challenges with webhook reliability. During initial tests, we encountered missed events due to network timeouts or server errors. To resolve this, we implemented signed webhook validation, retry mechanisms using Laravel job queues, and logging and alert systems to identify and resolve delivery issues.

Another challenge was mapping our business logic to the payment flow. Bridging the gap between commission models, conditional subscriptions, and the payment gateway’s API structures required careful planning. We modelled edge cases, such as full and partial refunds, subscription upgrades or downgrades, and delayed payouts based on account verification status.

Our Integration Process – Step-by-Step

Our first step was to define the objectives and map out the payment flow. We documented the entire process from user sign-up to payment confirmation, payout, refund, and subscription renewal. This roadmap helped us understand how each part would interact with the payment system.

Next, we explored the API documentation, flow diagrams, and webhook payloads before beginning the coding process. This preparation allowed us to build secure endpoints and data models early on.

For the implementation, we created secure server-side handlers using Laravel to handle all critical functions like transaction creation, vendor balance updates, and webhook listening. This approach ensured we never handled sensitive data on the client side.

Testing followed with the gateway’s sandbox mode, simulating real payment flows like successful and failed transactions, refunds, and subscription renewals.

Finally, we monitored every request and response, logging the activity between our system and the gateway to ensure auditability and facilitate troubleshooting.

Key Lessons Learned

From our experience, we learned the importance of understanding the data model before diving into the integration. Knowing what data to store, what can be retrieved from the gateway, and how to link transactions to internal records is crucial for smooth implementation. We also realised the importance of treating webhooks as first-class citizens, as they are key to maintaining a real-time system.

We designed for edge cases, ensuring we had mechanisms in place for retries, timeouts, double payments, and webhook failures. Above all, we prioritised security by using secrets, signature verification, and HTTPS across all endpoints.

Conclusion

A modern, thoughtfully integrated payment gateway is not just about processing payments—it can be the backbone of financial operations, reducing manual work, enhancing vendor relationships, and enabling seamless scaling. By focusing on API clarity, security, webhook reliability, and aligning with business logic, we delivered a robust and scalable payment experience for the platform.

If you are building a marketplace, SaaS product, or custom service platform, a well-integrated payment system is key to earning business trust and driving growth.

Scalable payment gateway integration for SaaS & marketplaces with secure APIs, split payouts, real-time webhooks & PCI compliance. Contact us to get started.

WhatsApp Messaging: How UltraMsg Streamlines Automation

Posted on by Layana Chandran

Introduction

UltraMsg automates WhatsApp messaging for sailing bookings, sending personalised updates, reminders, and real-time notifications to guests, crew, and staff.

We help people book unforgettable sailing holidays across Europe and the Mediterranean. Whether it’s a romantic getaway in Greece or a large group trip in Croatia, we ensure a smooth experience from start to finish.

Communication plays a key role in making a trip successful. To address this, we built a custom WhatsApp messaging automation system that has transformed how we interact with customers and streamline our operations.

Now, we send timely, personalised WhatsApp messages to everyone involved in a booking: guests, skippers, hostesses, base staff, and transfer drivers—all from one system.

Why WhatsApp Works for Global Customers

Our customers come from diverse backgrounds, speaking languages such as English, Italian, German, French, and Croatian. Despite this diversity, they all use WhatsApp. This platform is fast, universal, and mobile-friendly, making it perfect for sending important documents, location pins, check-in instructions, crew details, and real-time updates.

Instead of relying on email, which can often be ignored or lost, we meet our customers where they are—right in their pocket.

UltraMsg API Integration for Seamless Messaging

We integrated UltraMsg’s API into our internal admin dashboard. For every booking, our system generates a timeline of WhatsApp messages tailored to key stages of the trip.

Our system automatically schedules each message based on the charter date, such as five days before departure. The “Send” button lets us trigger last-minute updates or resend messages if needed.

We also customise messages based on the recipient. For example, guests, skippers, hostesses, admins, and drivers receive the most relevant communication. We use dynamic placeholders like {user_name}, {check_in_day}, and {company_name}, which our system fills with actual booking data when sending the message.

Combining Automation with Manual Flexibility

While most WhatsApp messaging is automated, we’ve built in manual overrides for added flexibility. Time-based automation handles routine communication after a booking is confirmed, ensuring the right messages are sent at the right times without human input.

However, if necessary, our team can intervene with the “Send WhatsApp Message” button to deliver a message instantly. This combination of automation and flexibility ensures we never forget to send important information, can respond quickly when plans change, and always know what’s been sent and to whom.

Enhancing Customer Experience with Automated Messages

UltraMsg provides flexible tools for sending automated WhatsApp messages in a variety of situations. Before an event or booking, we schedule welcome messages, reminders, and check-in instructions in advance, using the Scheduled Messaging API or integrating with our booking system for automatic triggers.

On the event day, we trigger real-time updates like arrival confirmations and check-in prompts based on system events such as status changes or dates. During the service, we send mid-service check-ins, photo requests, and upselling offers to specific customer groups based on their current status or location.

As departure nears, our system automatically sends checkout reminders and final instructions. After service completion, we follow up with thank-you messages, feedback requests, and promo codes, triggered by event-based logic or scheduled sends.

Using UltraMsg for Staff and Partner Communication

UltraMsg also helps us communicate with internal teams. For staff, we send schedules, shift reminders, training updates, and urgent alerts. For suppliers and partners, we send delivery updates, confirmations, and special instructions. Logistics updates drivers about pickup times, shares live location links, and informs passengers about delays.

For customer support, we automate ticket updates, appointment confirmations, and responses to frequently asked questions.

Why UltraMsg is the Best Choice

UltraMsg offers a straightforward API that integrates easily with our PHP-based backend. It’s affordable, cost-effective compared to Twilio or official Meta partners, and delivers messages reliably without throttling or missed connections. We started sending live messages within hours of integrating the system, ensuring the entire process was smooth and efficient.

Ready to enhance your communication with automated WhatsApp messaging? Contact us today to learn how UltraMsg can streamline your operations and improve customer engagement. We’re here to help!

Yacht Charter Search: Boosting Efficiency with Refactoring

Posted on by Layana Chandran

Boost your yacht charter search speed by 50% with efficient database restructuring and Laravel optimisation. Improve performance without scaling up.

When it comes to improving website performance, most people think the solution lies in scaling up — more servers, larger databases, and expensive infrastructure. But sometimes, the greatest gains come from a simpler approach. We recently restructured our yacht charter search platform — without changing the design, upgrading hardware, or adding any flashy frontend gimmicks. The result? A 50% increase in search speed.

So, what actually made the difference? It had nothing to do with the usual suspects.

The Same Yacht Platform, Rebuilt Differently

We manage two versions of the same yacht charter site. One was originally built on FuelPHP with manually written raw SQL queries, while the other was rebuilt on Laravel using structured application logic and modern tools. The data, filters, and user interface were the same, but the new version was much faster — even while displaying over 100 live yacht listings on the same page, without pagination. Search speed improved significantly.

What Changed Behind the Scenes?

The old system provided full control over the database with raw SQL queries. It worked, but as time went on, it became hard to maintain, prone to inefficient joins, and sluggish as the yacht count and filters grew.

With the Laravel rebuild, we focused on structured relationships, modern PHP practices, and smart data-loading techniques. It wasn’t just about rewriting code; it was about rethinking how the site fetched and managed data.

What Actually Made It So Much Faster

Instead of writing dozens of individual queries for each yacht and its related info (images, availability, pricing), we utilised eager loading to fetch everything in fewer calls. Laravel made this process seamless.

We restructured how yachts, companies, and seasonal availability were linked, leading to cleaner filters, leaner results, and no duplicate data being processed on the fly. Laravel’s built-in caching tools allowed us to cache filtered results and API responses more effectively. This meant when users searched for yachts in Greece or Croatia, those results were ready in milliseconds, rather than being regenerated from scratch each time.

FuelPHP required more manual management of filters and joins, but in Laravel, reusable filters and scopes made the logic easier to understand, debug, and improve — naturally leading to faster response times.

The Real-World Result

With over 100 yachts displayed live on a single page and third-party APIs integrated in real-time, the load time was reduced by more than half. No additional hardware was required to handle the increased performance. The impact was immediate: lower bounce rates, faster bookings, and an improved user experience.

So, What’s the Takeaway?

Speed improvements don’t always require scaling up. Sometimes, it’s more about how intelligently your application handles data — not how much muscle you throw at it. By rethinking our structure and employing modern, well-designed tools, we made our yacht search dramatically faster, leaner, and easier to maintain.

Thinking of Rebuilding or Optimising Your Own Platform?

If your current system feels slower than it should — especially under the weight of large datasets or API calls — the solution might not be to add more resources. It could be about rethinking how the system works beneath the surface.

Ready to optimise your platform for better performance? Contact us now to learn how we can help improve efficiency and enhance your user experience.

GitHub Pull Request Reviews with MCP & Claude Desktop

Posted on by Layana Chandran

Introduction

Automate GitHub pull request reviews using MCP Server and Claude Desktop for faster, consistent, and scalable code reviews with improved code quality.

In fast-paced development teams, GitHub pull request reviews play a crucial role in maintaining code quality. However, as codebases grow and teams expand, relying solely on manual reviews becomes increasingly inefficient. To solve this, I integrated GitHub MCP Server with Claude Desktop, introducing structured automation and intelligence into the review process. As a result, we experienced faster feedback loops, reduced manual effort, and significantly improved code integrity.

Why Manual Pull Request Reviews Don’t Scale

Manual GitHub pull request reviews often struggle to keep up with modern development demands. For instance, reviewers may miss critical issues due to a lack of project-wide context. Additionally, when deadlines approach, reviews are often rushed, leading to inconsistent or superficial feedback. Moreover, developers waste valuable time repeatedly correcting formatting or structural issues.

Therefore, it’s clear that traditional reviews create bottlenecks, especially for growing teams managing multiple repositories.

Introducing GitHub MCP Server for Automated Reviews

To streamline this process, I implemented the GitHub MCP Server—a tool designed to automate and enhance pull request reviews. It listens to events on GitHub, collects metadata such as commit messages and file changes, and converts this data into MCP documents. These structured documents enable intelligent tools to provide feedback that is both fast and highly contextual.

In essence, the MCP Server bridges the gap between raw code changes and meaningful automated review.

How Claude Desktop Enhances PR Review Quality

Once I set up the MCP Server, I connected it to Claude Desktop, a tool capable of understanding and responding to structured context. By defining prompts and including metadata like file types, team ownership, and architecture patterns, I enabled Claude to generate review comments that aligned with our project standards.

As a result, each pull request received actionable feedback within seconds, significantly accelerating our review cycles.

Benefits of Automated GitHub Pull Request Reviews

The integration delivered multiple advantages. First and foremost, it removed the burden of repetitive checks. Claude automatically handled formatting issues, style enforcement, and minor bugs. Consequently, human reviewers were free to focus on high-level architecture, logic, and design consistency.

Furthermore, Claude’s reviews were context-aware. It understood which parts of the codebase were affected, whether the changes respected modular design principles, and if they introduced any risks in areas like security or observability.

Most importantly, we ensured that every PR received a consistent baseline review—regardless of the reviewer—improving team-wide trust and code reliability.

Scaling PR Review Across Projects

Beyond the immediate gains, this solution also proved highly scalable. It worked seamlessly across multiple repositories, and it allowed us to add new tools into the workflow with minimal effort. For example, we could extend it to support test generation, documentation validation, or pre-commit hooks.

In short, this approach offers long-term sustainability and adaptability for development teams looking to modernise their processes.

Conclusion: Smarter GitHub Pull Request Reviews at Scale

To conclude, combining GitHub MCP Server with Claude Desktop revolutionised our pull request review workflow. It replaced repetitive manual tasks with intelligent automation, delivered fast and meaningful feedback, and ensured consistent code quality across the board.

If you’re looking to improve efficiency and scale your GitHub pull request reviews without compromising quality, this structured, protocol-driven setup is a powerful place to start.

If you’re looking to speed up development cycles, improve code quality, and scale your review process intelligently, we’re here to help. Contact us now to learn how MCP Server and Claude Desktop can be tailored to your workflow. Let’s build smarter, together.

Postman API Testing: Scalable and Reusable Test Strategy

Posted on by Layana Chandran

Introduction: Smarter Postman API Testing Starts Here

Optimise Postman API testing with smart scripts, reusable logic, and dynamic variables for efficient, scalable, and reliable test automation.

Postman is a widely adopted tool for software API testing, known for its intuitive interface and robust capabilities. Although it is simple to begin with, its potential extends far beyond basic manual tests. When used strategically, Postman becomes an essential part of a reliable testing and automation strategy for web applications, mobile website testing, and broader API testiranje practices.

Rather than treating each test as a standalone task, organisations can embrace test-driven testing approaches that promote consistency and scalability. By incorporating Postman API testing with dynamic scripting, reusable logic, and smart data handling, teams can build a powerful testing framework. These enhancements not only improve accuracy but also prepare teams to integrate with AI testing and AI for automation platforms.

Adding Smart Checks with Scripts

Postman lets you use JavaScript scripts during different stages of the request process. This helps automate tasks and validate responses. Pre-request scripts run before the request is sent. Use them to generate timestamps, create tokens, or set dynamic variables. Test scripts run after the response arrives. They check things like status codes, response time, or the presence of key data.

For example, a test script can check if the status code is 200 and if the response contains the expected value. These checks reduce manual effort and improve test accuracy. They reflect modern AI in testing practices and support efficient test automation.

Reusing Test Logic to Save Time

As test suites grow in size and complexity, repeatedly writing the same test logic becomes inefficient. Postman allows testers to reuse scripts across collections and requests, supporting a modular and maintainable approach to driven testing.

Shared scripts applied at the collection level ensure that all tests under that group adhere to the same standards. This is beneficial when managing hundreds of API requests or when working on complex web application testing or mobile testing scenarios. Reusable snippets, such as authentication token checks or standard response validations, simplify test management.

Moreover, using variables to store these functions allows teams to update logic in one place and automatically reflect those changes across all relevant tests. This aligns with industry trends in software automated testing, where consistency, speed, and scalability are paramount.

Using Variables for Flexible Testing

One of Postman’s most powerful features is its support for variables, which help eliminate hard-coded values and improve test flexibility. This is especially relevant when switching between different test environments or adapting to dynamic user data.

Environment variables allow easy transitions between development, staging, and production servers. Global variables provide cross-project access, while collection variables are specific to a single set of tests. Local variables are scoped to individual requests and are useful for temporary overrides.

For instance, instead of manually updating each test with a new endpoint, testers can use a placeholder such as {{base_url}}. When the server address changes, only the variable needs updating. This method is widely used in Selenium automation testing, AI automation, and intelligent platform for AI workflows where dynamic data handling is crucial.

This practice not only minimises human error but also enhances productivity across large-scale testing website initiatives or AI site integrations.

Best Practices for Enhanced API Testing

To optimise your use of Postman, it is important to adopt strategies that reflect both automation and scalability. Structuring requests into logical folders, naming variables clearly, and using version control systems such as Git ensures your test strategy remains manageable and future-proof.

Additionally, always prioritise secure data handling by avoiding hard-coded tokens or credentials. Using environment variables with encrypted storage is essential, especially when integrating with AI-powered testing platforms or when managing sensitive web API interactions.

These practices ensure your Postman testing is not only functional but also professional, secure, and adaptable to changes over time.

Conclusion

Postman has evolved into more than just a manual API testing tool. It is a sophisticated environment that supports advanced test-driven development, web automation testing, and seamless integration with tools such as Selenium testing and other AI in testing platforms.

By mastering the use of scripts, reusable logic, and dynamic variables, teams can build maintainable test suites that reduce errors, accelerate delivery, and enhance quality. Whether you’re aiming to create an API, manage tests across a website API, or automate complex web mobile testing, Postman offers the flexibility and intelligence needed to succeed in modern development.

Incorporating these practices will not only improve test coverage and accuracy but will also position your team to embrace AI testing, test AI tools, and the future of testing automation—across websites, mobile platforms, and beyond.

Need help improving your API testing strategy in Postman? Whether you’re after expert guidance, hands-on training, or a tailored framework review, our team is ready to support you. Contact us today and let’s build smarter, faster, and more reliable tests together.

API Testing with Postman & Newman: A Complete Guide

Posted on by Layana Chandran

Introduction

Streamline API testing with Postman and Newman for automation, CI/CD integration, and scalable test execution. Boost performance, reliability, and speed.

In modern software development, effective API testing ensures that systems communicate smoothly and reliably. APIs (Application Programming Interfaces) allow various components to exchange data and execute services efficiently. Postman, a leading tool for API testing, helps teams design, manage, and validate test cases with ease. For large-scale automation, Newman—the command-line companion to Postman—extends functionality and integrates well with CI/CD pipelines.

By using both tools together, teams improve the speed, accuracy, and reliability of their testing software.

Understanding API Testing

Teams use API testing to confirm that interfaces work correctly, respond quickly, and remain secure. Unlike UI testing, which depends on frontend elements, API testing works directly with the backend. This method improves test speed and provides better stability during web software development.

When developers use test driven and integration testing methods, they quickly identify issues, reduce bugs, and deliver better results. These strategies make testing more consistent and predictable.

Why Use Postman for API Testing?

Postman offers a clear and user-friendly interface for designing and sending API requests. Developers and testers can group requests into collections, apply variables, and automate tests using JavaScript. These features simplify testing functionality and help manage different environments, such as development, staging, and production.

Testers use Postman to validate status codes, response times, and data formats. The tool includes built-in reporting tools to help users measure results effectively. With these features, teams follow test driven practices and build reliable testing plans for applications, including development apps and public APIs such as the YouTube API or LinkedIn API.

The Role of Newman in API Testing

While Postman is ideal for manual and semi-automated testing, Newman enhances scalability by enabling tests to run from the command line. This makes Newman particularly valuable in continuous integration and CI/CD pipelines, where tests must be triggered automatically on code changes or deployments.

Newman supports execution of Postman collections across various environments, ensuring consistent results irrespective of the testing platform. It can be easily integrated with popular CI/CD tools such as Jenkins, GitHub Actions, and GitLab. By automating API testing in these pipelines, teams can detect issues earlier and deliver updates faster and more reliably.

Because Newman runs from the terminal, it also allows for customised execution using command-line options and scripting. This flexibility supports advanced test scenarios, including performance test loops, multiple environment runs, and conditional executions.

Benefits of Using Newman

With Newman, teams scale API testing without manual effort. They schedule tests, monitor performance, and verify changes across different systems. Developers integrate Newman into their CI/CD pipelines to trigger tests on each commit, which ensures rapid feedback and prevents bugs from reaching production.

Using external data sources in Newman enables data-driven testing. This practice increases test coverage and adapts well to AI-related workflows. Teams exploring AI in testing, AI automation, or API AI benefit from this adaptability. Newman also works well with automation testing test setups that demand repeatability and consistency.

Implementing an API Testing Strategy with Postman and Newman

To build a successful strategy, teams first define the key API endpoints and scenarios to test. They group related requests into Postman collections, add validations, and prepare environments using variables. This setup allows flexible execution across stages of deployment.

Testers then automate the execution process with Newman. By integrating it with their CI/CD pipeline, they ensure that tests run automatically with every change. This setup allows fast, continuous feedback and helps maintain quality in both internal and public API integration.

Best Practices for Effective API Testing

Teams improve test effectiveness by keeping test collections well-organised and reusable. They use variables to avoid hardcoded values and store their test collections in repositories such as GitHub to track changes and support collaboration.

They regularly monitor response times, adjust for performance, and update test scripts as APIs evolve. Including security checks for authentication and authorisation improves test depth. When teams apply these practices, they enhance both speed and accuracy across all their testing software testing processes.

Conclusion

Teams use API testing to ensure applications perform reliably and integrate with other systems. Postman helps create and manage these tests, while Newman automates them at scale. Together, they offer a complete solution for testing and automation, suitable for both small apps and large enterprise systems.

By following test driven approaches and integrating testing into CI/CD workflows, teams can quickly detect and resolve issues. These tools also support emerging trends like AI testing, testing AI, and smart platform for AI integrations. A well-structured approach to Postman API and Newman usage enables better collaboration, shorter release cycles, and higher-quality software.

Ready to enhance your API testing strategy with Postman and Newman? Whether you’re looking to streamline manual testing, implement automation, or integrate testing into your CI/CD pipeline, our team is here to help. Contact us today to learn how we can help streamline your testing process with Postman and Newman.

Behaviour Driven Development Testing with Cucumber

Posted on by Layana Chandran

Executive Summary

Enhance mobile app automation with Cucumber. Use behaviour driven development testing to improve readability, collaboration, and results over TestNG.

In today’s fast-paced mobile application development world, ensuring quality and performance through automation is essential. While TestNG remains a common tool for unit testing, Cucumber introduces a behaviour driven development testing approach that improves collaboration and test clarity. This article explores how Cucumber enhances mobile automation with Selenium and why it’s often a better choice than TestNG for writing scalable and maintainable tests in Java.

Why Choose Cucumber Over TestNG for Mobile Automation Testing?

Readable Test Cases with Gherkin Syntax in Behaviour Driven Development Testing

One of the standout strengths of Cucumber lies in its ability to improve readability and collaboration. Through Gherkin syntax, testers write test cases in plain English. This allows non-technical stakeholders—like business analysts and product managers—to easily review and even contribute to test coverage.

TestNG, however, relies on Java annotations that create a barrier between development and business teams. In fast-moving mobile development apps, aligning technical work with business goals is vital—and behaviour driven development testing supports this alignment effectively.

Test Development Driven by Real User Behaviour in Mobile Automation

Cucumber promotes a test development driven process that keeps test scenarios close to real-world user behaviour. Tests are aligned with user stories and acceptance criteria, ensuring the features under development meet actual user needs. In contrast, TestNG follows a traditional unit testing model that may overlook high-level user goals.

Reusable Step Definitions for Scalable Test Automation

Cucumber encourages modularity. Its step definitions can be reused across multiple feature files, helping teams avoid duplication and maintain clean automation scripts. In contrast, TestNG demands distinct methods for each test case, often leading to more repetitive code and greater maintenance overhead.

Advanced Reporting for User Testing and AI Testing Insights

Reporting is another area where Cucumber excels. It offers detailed, scenario-based HTML and JSON reports, ideal for sharing with stakeholders during user testing or application creation phases. These visually structured reports contrast with TestNG’s default XML reports, which typically require third-party tools to gain similar clarity.

Addressing the Challenges of Behaviour Driven Development Testing with Cucumber

Despite its advantages, teams adopting behaviour driven development testing with Cucumber may face a few initial hurdles:

Learning Curve When Transitioning to Behaviour Driven Testing Tools

For teams unfamiliar with BDD in automation, adapting to Gherkin syntax and learning the Cucumber automation step-by-step workflow can be challenging. However, with proper onboarding and training, most testers adapt quickly and begin writing tests that align with business logic.

Performance Considerations in Mobile App Testing Using Appium

Cucumber introduces an abstraction layer through step definitions, which can slightly slow down execution when compared to TestNG’s direct calls. Still, optimising step definitions and avoiding redundant logic can significantly minimise this performance impact—especially in mobile app testing using Appium.

Integration Complexity with Legacy TestNG Frameworks in Mobile Automation

Teams migrating from a legacy TestNG-based framework may need to restructure their test suite to support Cucumber’s test driven testing model. A hybrid approach is useful here: continue using TestNG for unit-level testing, and adopt Cucumber for high-level functional and behavioural scenarios.

Implementing Behaviour Driven Development Testing with Cucumber and Appium

To implement Cucumber in mobile automation testing using Appium, begin by setting up a Maven-based project and installing required dependencies, including Selenium, Appium, Cucumber, and JUnit or TestNG.

Once the project is ready, write feature files using Gherkin syntax. These feature files describe user scenarios in plain language, which helps connect the automation effort to real-world usage. Next, implement step definitions in Java to map each scenario step to automation code. This mapping process is crucial for developing a robust and reusable automation testing test framework.

Run the tests using Cucumber’s test runner, which can be based on either JUnit or TestNG. With this setup, your mobile testing using Appium becomes more structured and easier to maintain. You can run the same tests across native, hybrid, or web-based mobile apps, supporting a wide range of tools in mobile automation.

Workflow and Reporting Comparison

Cucumber enhances collaboration through a clear workflow. Teams define features, create reusable steps, and link them with automation code. The resulting reports provide scenario-based execution logs, screenshots, and timestamps. These insights help testers identify failures quickly and report outcomes to the wider team.

In contrast, TestNG provides basic XML-based reports with standard test logs. While they suit technical audiences, they lack readability for business stakeholders. When working in cross-functional teams or aiming for ai driven development, this lack of visibility becomes a barrier.

Cucumber’s reporting fits well with test automation with AI, ai testing, and even selenium ai testing, as it supports structured logs that AI-based analytics tools can consume. This compatibility makes Cucumber future-ready for platform for AI workflows.

What We Learned

Cucumber improves communication, test design, and reporting in mobile app automation. It allows teams to align with business goals and embrace a test driven methodology based on user stories. While TestNG may offer faster execution, it lacks the readability and collaboration benefits that Cucumber provides.

By combining testing with Selenium Java, native app automation, and mobile app testing using Appium, Cucumber delivers a complete solution for modern testing automation. With training and optimisation, teams can maximise its potential and integrate it into their existing testing and automation pipelines.

Feature Cucumber Report TestNG Report 
Readability High (scenario-based) Moderate (XML-based) 
Customisation Easy (built-in HTML & JSON) Requires third-party tools 
Execution Insights Detailed logs with screenshots Standard test method logs 
Non-Technical Friendly Yes No  

Cucumber enhances test readability, collaboration, and alignment with business goals. While TestNG offers faster execution, Cucumber provides a structured and reusable framework for BDD-based testing. Integrating Cucumber with Selenium and Appium improves test maintainability and reporting. Overcoming initial learning challenges and optimising implementation can maximise the benefits of using Cucumber.

Conclusion

Cucumber support for behaviour driven development transforms how teams write and execute automated tests for mobile applications. It enhances test clarity, improves collaboration, and aligns more closely with business requirements compared to traditional tools like TestNG.

By understanding its advantages, addressing the challenges, and following a structured implementation approach, teams can adopt Cucumber confidently. Whether you are building AI tools for testing, integrating AI with Selenium, or exploring testing using AI, Cucumber provides a strong foundation for the future of mobile automation and it test automation in agile teams.

Looking to implement Cucumber BDD for your mobile application testing? Our experts can help you streamline your automation framework and improve testing efficiency. Get in touch with us today to discuss how we can support your testing needs!

Event Streaming with Kafka and FastAPI

Posted on by Layana Chandran

Introduction to Event Streaming and Real-Time Data

Learn to integrate Apache Kafka with FastAPI for scalable, real-time data streaming using Confluent Kafka in modern event-driven Python applications.

Event streaming has become a core approach in building modern, data-driven systems. Apache Kafka is a powerful, open-source platform designed for handling real-time data. It allows organisations to manage high-volume data feeds, process events efficiently, and facilitate seamless data sharing.

Originally developed by LinkedIn and later donated to the Apache Software Foundation, Kafka software now powers many leading platforms. In this guide, you will learn how to integrate Kafka Confluent with FastAPI, a high-performance Python framework, to create scalable pipelines for data streaming.

Why Use Kafka and FastAPI for Event Streaming?

Using Kafka with FastAPI provides a fast and reliable environment for event streaming. Kafka can handle millions of messages per second. It also supports horizontal scaling through Kafka clusters, making it ideal for microservice-based systems.

FastAPI, on the other hand, offers asynchronous features and built-in data validation. Therefore, it becomes a suitable match for systems requiring speed and precision. When combined, Kafka and FastAPI form a powerful duo for developing systems based on real-time AI, web data, and continuous data sharing.

Understanding the Architecture of Kafka for Data Streaming

Kafka’s architecture consists of several key components:

  • Producer: Publishes messages to Kafka topics.
  • Broker: Kafka servers that store and deliver messages.
  • Topic: A logical channel where producers send messages and consumers retrieve them.
  • Partition: Subdivisions of a topic that enable parallel message processing and improve throughput.
  • Consumer: Reads messages from topics, either individually or as part of a consumer group.
  • Zookeeper: Manages metadata and coordinates leader elections within Kafka clusters.

Setting Up a Kafka Producer for Event Streaming in FastAPI

Installing Dependencies

To integrate Kafka with FastAPI, install the required packages:

pip install fastapi uvicorn confluent-kafka

Setting Up Kafka with FastAPI

Kafka Producer in FastAPI

The Kafka producer sends messages to a specified topic. In a FastAPI application, you can implement a producer as follows:

from fastapi import FastAPI
from confluent_kafka import Producer

app = FastAPI()

producer_config = {
    'bootstrap.servers': 'localhost:9092'
}
producer = Producer(producer_config)

@app.post("/produce/{message}")
async def produce_message(message: str):
    producer.produce("test-topic", message.encode("utf-8"))
    producer.flush()
    return {"status": "Message sent"}

This pattern supports continuous data streaming, enabling your application to function as a real-time pipeline for driven data and AI real time decision-making.

Kafka Consumer in FastAPI

The Kafka consumer reads messages from a topic. In FastAPI, you can run a consumer in a background thread to listen continuously for new messages:

from confluent_kafka import Consumer
import threading

consumer_config = {
    'bootstrap.servers': 'localhost:9092',
    'group.id': 'fastapi-group',
    'auto.offset.reset': 'earliest'
}
consumer = Consumer(consumer_config)
consumer.subscribe(["test-topic"])

def consume():
    while True:
        msg = consumer.poll(1.0)
        if msg is not None and msg.value() is not None:
            print(f"Consumed: {msg.value().decode('utf-8')}")

thread = threading.Thread(target=consume, daemon=True)
thread.start()

This code initializes a Kafka consumer that subscribes to the “test-topic” topic. The consume function polls Kafka for new messages and prints them when they arrive. Running the consumer in a separate thread allows it to operate concurrently with FastAPI’s main event loop.

Future Enhancements: Live Streaming with WebSockets

While the integration above supports real-time processing, further enhancements are possible. For instance, you can use FastAPI’s WebSocket support to stream Kafka data directly to clients. As a result, you can build live dashboards, notifications, or monitoring tools without the need for polling.

Moreover, this enhancement is ideal for systems focused on AI real-time interactions, enabling seamless flow of data on web for end-users.

Conclusion

In summary, integrating Kafka software with FastAPI allows developers to build fast and resilient systems. Kafka ensures durable and scalable data processing, while FastAPI brings simplicity and performance.

Together, these tools support a range of needs—from data management and data categorisation, to building real-time data and apps. Whether you’re working with Python and Kafka, deploying Apache Kafka consumers, or designing systems to automate data, this integration is future-ready.

Therefore, if you are looking to build high-throughput, low-latency applications with efficient event streaming, combining FastAPI and Kafka is a smart and scalable choice.

Our team of experts is ready to assist you in designing and implementing scalable, real-time data streaming solutions with Kafka and FastAPI. Contact us today to learn how we can help bring your vision to life.

Selenium Java Automation: Getting Started with TestNG

Posted on by Layana Chandran

Introduction

Boost Selenium Java automation with TestNG! Learn annotations, parallel execution, reporting & advanced features for efficient Java test automation.

In modern web software development, automation testing has become a vital part of ensuring consistent, efficient, and reliable software delivery. As development cycles get shorter, testing needs to be faster and smarter. This is where frameworks like TestNG shine, especially when combined with Selenium Java automation for web applications.

This guide is for anyone getting started with automation testing. We’ll walk through the basics of TestNG, its benefits, and how it enhances test automation with AI, Selenium automation Java, and other automation testing tools for web applications.

What is TestNG?

TestNG, short for “Test Next Generation”, is a testing framework inspired by JUnit and NUnit. It offers more flexibility and power in testing software, particularly for Java to Java test environments. It simplifies automation testing using AI or traditional scripting and supports multiple test features.

Among its core features are:

  • Annotations – Helps define test methods clearly (e.g., @Test, @BeforeMethod, @AfterMethod).
  • Parallel Execution – Allows running multiple test cases simultaneously.
  • Data-Driven Testing – Supports parameterization with @DataProvider.
  • Flexible Execution – Enables grouping, dependency, and priority-based execution.
  • Advanced Reporting – Automatically generates detailed test execution reports.

Understanding Selenium for Web Application Testing

Selenium is a widely-used, open-source automation testing tool for web applications. It simulates user interactions such as clicks, form submissions, and navigation in browsers. Selenium supports various programming languages like Java, Python, and C#, but it’s most commonly used in automation selenium with Java projects.

When combined with TestNG, Selenium allows test cases to be structured in a logical, reusable manner that supports modern testing and automation practices—especially useful in AI automation testing tools ecosystems.

Why Use TestNG in Selenium Java Automation?

TestNG significantly enhances Selenium Java automation by improving test structure, reliability, and execution control. It supports driven testing, where tests are built around real user interactions and business logic.

Here’s why TestNG is preferred in automated testing in software testing:

  • Better Test Structure – Organizes test execution efficiently.
  • Assertions for Validation – Ensures test accuracy using Assert statements. 
  • Retry and Failure Handling – Allows rerunning failed tests. 
  • Test Execution Control – Provides options for dependencies and priorities.
  • Comprehensive Reporting – Generates detailed execution reports automatically.

TestNG Annotations in Automation Testing Frameworks

TestNG follows a defined order of annotation execution:

@BeforeSuite

@BeforeTest

@BeforeClass

@BeforeMethod

@Test

@AfterMethod

@AfterClass

@AfterTest

@AfterSuite

This order ensures clean setup and teardown, which is especially important in AI for automation testing, where data and environments must be controlled.

Step-by-Step Setup of Selenium Java Automation with TestNG

Step 1: Add TestNG to Your Project

  • For Maven Users: Add the following dependency in pom.xml
  • For Non-Maven Users: Download TestNG and add it to your project’s libraries manually.

Step 2: Create a Basic Test Class

Create a new Java class and add a basic TestNG test

Step 3: Running Your First Selenium Java Automation Test

  • Right-click on the class → Select Run As → TestNG Test.
  • You should see TestNG executing your test in the console output. 

Step 4: Using Annotations for Test Driven Automation Testing

TestNG provides various annotations to control test execution flow. Here’s an example

Explanation:

  • @BeforeClass – Runs once before all test methods in the class. 
  • @Test – Defines test cases.
  • @AfterClass – Runs once after all test methods.

Step 5: Generating Reports in Selenium Java Automation

After executing tests, automatically generates reports in the test-output folder. These reports help in analyzing test results and debugging failures.

Benefits of TestNG Over Manual Testing

Manual testing is prone to human error and consumes valuable time. In contrast, TestNG enables automation AI tools to run complex tests automatically. This increases test coverage, improves reliability, and accelerates release cycles.

Additionally, TestNG supports features like parameterisation, retry logic, and test grouping—all impossible with manual tests. For large-scale systems, automation testing with AI becomes necessary, and TestNG fits seamlessly into that process.

AI Automation Tools and Future TestNG Reporting Use

TestNG reports provide structured logs of test execution, categorizing passed, failed, and skipped test cases. These reports are valuable for debugging and tracking issues. Over time, they help in analyzing trends in test failures, optimizing test strategies, and ensuring continuous quality improvements. Integrating these reports with CI/CD tools like Jenkins enhances automated test tracking and reporting.

Advanced Selenium Java Automation with TestNG Features

As you gain experience, explore these advanced features to enhance your automation framework:

  • Data Providers (@DataProvider) – Allows running the same test with multiple data sets.
  • Listeners (@Listeners) – Helps customize test execution behavior. 
  • Grouping & Dependencies – Organizes test cases efficiently.
  • Retry Mechanism (IRetryAnalyzer) – Automatically re-executes failed tests.
  • Parallel Execution – Runs tests faster by executing them concurrently.

Final Thoughts on Test Automation Using AI and Selenium Java

Implementing TestNG in web automation structures execution and enhances efficiency. Beginners should start with simple test cases and gradually explore advanced features like parallel execution and data-driven testing. With its robust functionality, TestNG remains a preferred choice for Java-based automation, ensuring reliable and effective test execution.

If you want to enhance your automation testing strategy with TestNG and Selenium, our experts are here to provide comprehensive support, from implementation and troubleshooting to optimizing your test automation framework. Get in touch with us today to streamline your testing process and achieve efficient, reliable automation results.

Web Application Penetration Testing: CSP Fix Guide

Posted on by Layana Chandran

Introduction

Strengthen web application penetration testing with a robust Content Security Policy (CSP). Learn to detect, fix, and monitor CSP issues to prevent XSS attacks.

In modern web application penetration testing, one of the most common findings is a missing or misconfigured Content Security Policy (CSP). A CSP acts as a browser-enforced security policy that helps prevent XSS script injection, clickjacking, and data leaks. Therefore, it’s a key area of focus in any penetration testing report.

During a pen test, security teams assess whether CSP is present, correctly configured, and resilient against bypass attempts. Improper CSP configuration can lead to cyber security vulnerabilities, allowing attackers to steal sensitive data, hijack sessions, or manipulate page behaviour. For organisations offering pen testing services, evaluating CSP implementation is a critical component of web application security testing.

Common CSP Vulnerabilities Found During Web App Security Testing

  • No Content Security Policy header: The web application lacks a CSP altogether, leaving it exposed.
  • Overly permissive directives: CSP includes unsafe-inline or unsafe-eval, which defeat its purpose.
  • Third-party trust issues: External scripts from untrusted sources pose a security and penetration testing risk.

Understanding CSP Security in Web Application Penetration Testing

CSP is defined through an HTTP response header that specifies the allowed sources for various types of resources. For example, a basic CSP configuration might look like:

add_header Content-Security-Policy "default-src 'self'; script-src 'self';";

Essential CSP Directives for Strengthening Web Application Security

  • default-src 'self' which restricts all resources to the same origin unless specifically overridden.
  • script-src 'self' which allows JavaScript execution only from the same domain, blocking inline scripts.

When a web browser detects a CSP violation, it blocks the content and logs the issue. This control is especially effective against XSS script attacks, a top vulnerability in web pen testing and security audit procedures.

How to Evaluate CSP During Web Application Penetration Testing

Checking for Missing CSP Headers in Security Testing

The first step is to check if CSP is implemented. This can be done using browser developer tools by navigating to the Network tab and checking response headers or by using the command:

curl -I https://target-website.com | grep Content-Security-Policy

If the CSP header is missing, this becomes a critical issue in the penetration testing report.

Detecting Weak CSP Policies in Web Pen Testing

A common misconfiguration:

add_header Content-Security-Policy "script-src 'self' 'unsafe-inline' 'unsafe-eval';";
  • 'unsafe-inline': Allows inline JavaScript, enabling XSS script execution.
  • 'unsafe-eval': Permits execution via eval()—a security risk often highlighted in IT security penetration testing.

Testing for CSP Bypass in Web Application Vulnerability Assessments

Try injecting malicious code into input fields or URL parameters:

<script>alert('XSS Attack!')</script>

If it executes, the CSP security control is ineffective. If blocked, browser dev tools will log a violation—valuable feedback in cyber security testing.

Fixing CSP Misconfigurations in Web App Security Testing

Using Report-Only Mode in Pen Testing Before Full CSP Deployment

Before enforcing a strict CSP, test using a Content-Security-Policy-Report-Only header. This helps prevent accidental breakage of legitimate functionality during implementation.

add_header Content-Security-Policy-Report-Only "default-src 'self'; report-uri /csp-report;";

Deploying a Strong CSP in Nginx for Web Application Security

Once tested, a stricter CSP policy should be enforced:

add_header Content-Security-Policy "
  default-src 'self';
  script-src 'self' https://trusted-cdn.com;
  style-src 'self' 'nonce-randomNonce';
  object-src 'none';
  base-uri 'self';
  form-action 'self';
  frame-ancestors 'none';
";

This policy ensures that all resources are loaded from the same origin unless specified, JavaScript is only allowed from the site itself and a trusted CDN, inline styles are controlled using a nonce, Flash and other outdated technologies are blocked, and protections against clickjacking and unauthorized form submissions are in place.

Breakdown of CSP Directives for Penetration Testing Compliance

  • default-src 'self': Baseline for all content—safe by default.
  • script-src: Whitelist only known, trusted sources to avoid security threats.
  • style-src with nonce: Prevents unauthorised CSS injection.
  • object-src 'none': Blocks outdated plugin-based attacks.
  • form-action and frame-ancestors: Prevent clickjacking and data theft via form manipulation or iframe embedding.

This level of control significantly reduces the attack surface and is widely recommended by security companies performing cyber security penetration testing.

Monitoring and Validating CSP in Cyber Security Testing

How to Verify Effective CSP Implementation During Site Security Testing

After enforcement:

  • Use curl or browser dev tools to verify CSP.
  • Attempt to inject test scripts and observe browser blocks.

Monitoring logs ensures you’re not breaking legitimate features, which is essential in both IT security policy enforcement and website pen testing workflows.

Setting Up Violation Reports for Continuous Web Security Monitoring

Set up a report-uri endpoint or use services like Report URI for logging:

curl -I https://yourwebsite.com | grep Content-Security-Policy
add_header Content-Security-Policy "default-src 'self'; report-uri /csp-report;";

This allows continuous feedback—important for organisations focused on data and security, web application testing, and security AI integrations.

Conclusion: Role of CSP in Web Application Penetration Testing

In cyber security and penetration testing on websites, CSP acts as a foundational client-side defence. It helps prevent XSS, injection attacks, and data leakage—all common in web application penetration testing and mobile app pen testing.

Key Takeaways for Improving CSP Security During Pen Testing

  • Start with Report-Only: Safely identify issues without breaking functionality.
  • Never Use unsafe-inline or eval(): These directives nullify your CSP.
  • Monitor Violations: Use CSP logs for proactive security auditing.
  • Adapt with Time: As web content changes, so should your IT security policy.

By implementing a strong CSP, you significantly improve your site security test score and reduce exposure to cyber security attacks. This is not just about compliance—it’s about resilience.

For any organisation concerned with cyber threats, web penetration testing, or cyber security AI solutions, enforcing a well-structured CSP content security policy is essential.

Ensuring your web application has a robust CSP policy is crucial for protecting against modern threats. If you need help with penetration testing or strengthening your CSP implementation, our security experts are ready to assist. Contact us now to schedule a consultation and safeguard your digital assets against cyber attacks.