We will explore the reasons why the traditional testing pyramid may not work for testing microservices and provide the modified testing pyramid as the ultimate solution. 22 May 2023 07 Min. Read Testing Pyramid: Why won’t it work for microservices testing? WhatsApp LinkedIn X (Twitter) Copy link Get a Demo Microservices architecture has been gaining popularity due to its ability to enhance the agility, scalability, and resiliency of applications. However, testing microservices can be challenging because of their distributed and independent nature. In traditional monolithic applications, the testing pyramid is a widely used framework for testing applications. This framework emphasizes the importance of unit testing, integration testing, and end-to-end testing in ensuring software quality. However, this testing pyramid may not work effectively for testing microservices architecture. In this blog post, we will explore the reasons why the traditional testing pyramid may not work for testing microservices and provide the modified testing pyramid as the ultimate solution. The Traditional Testing Pyramid The traditional testing pyramid is a framework that emphasizes the importance of unit tests, integration tests, and end-to-end tests in ensuring software quality. The pyramid is shaped like a triangle, with unit tests at the bottom, followed by integration tests in the middle, and end-to-end tests at the top. Unit tests are used to test the smallest units of code, typically at the function or class level. Integration tests are used to test how different modules of the application interact with each other. End-to-end tests are used to test the entire application from a user perspective. The traditional " Test Pyramid " suggests balancing unit, integration, and end-to-end tests . This pyramid is designed to provide a framework for testing software applications. However, with the rise of microservices, the traditional testing pyramid has become less useful. Where the Traditional Testing Pyramid Lacks? Microservices architecture is more complex than monolithic architecture. In a microservices architecture, services are distributed and independent, and each service may have its own database, making testing more challenging . This test pyramid approach needs to be modified for testing microservices . E2E tests need to be completely dropped. Aside from being time-consuming to build and maintain, E2E tests execute complete user-flows on the entire application with each test. This requires all services under the hood to be simultaneously brought up (including upstream), even when it is possible to catch the same kind and the same number of failures by testing only a selected group of services; only the ones that have undergone a change. 1. Microservices are highly distributed: Microservices architecture is based on breaking down an application into smaller, independently deployable services that communicate with each other over a network. This distributed nature makes it difficult to test the system as a whole using end-to-end tests. 2. Service boundaries are constantly evolving: Microservices architecture allows for rapid iteration and deployment, which means that the boundaries between services can be constantly changing. This serves as a challenge in maintaining end-to-end tests and integration tests as the system evolves. 3. Testing one service in isolation may not provide enough coverage: Because microservices are highly distributed and rely heavily on communication between services, testing one service in isolation may not be sufficient to ensure the overall quality of the system. 4. Independent Releases: In a microservices architecture, services are independently deployable and release cycles are faster. This makes it challenging to test each service thoroughly before release, and end-to-end testing is more critical than in traditional monolithic applications. The Modified Testing Pyramid for Microservices Microservices have a consumer-provider relationship between them. In a consumer-provider, one microservice (the consumer) relies on another microservice (the provider) to perform a specific task or provide a specific piece of data. The consumer and provider communicate with each other over a network, typically using a well-defined API to exchange information. This means the consumer service could break irreversibly if the downstream service (provider) changes its response that the consumer is dependent on. Since APIs are the key to run microservices-based system, testing them via the contracts they exchange while communicating would be an effective strategy to test them. This approach of selecting and testing only one service at a time is faster, cheaper, and more effective, and can be easily achieved by testing contracts [+data] for each service independently. Test every service independently for contracts [+data], by checking the API response of the service. Service level isolation is the most effective, manageable and scalable strategy for testing a multi-repo system. How HyperTest can help you achieve Contract[+data] testing? HyperTest is a no-code test automation tool for API testing. It is tailor-made to cater the challenges that microservices come with. It helps in running integration tests for all services deployed with HyperTest. If teams find it difficult to build tests that generate response from a service with pre-defined inputs, there is a simple way to test services one at a time using HyperTest Record and Replay mode. HyperTest sits on top of each service and monitors all the incoming traffic for the service under test [SUT]. HyperTest will capture all the incoming requests coming to a particular service and all of its upstream, creating a record for each request. This happens 24x7 and helps HyperTest builds context of the possible API requests or inputs that can be made to the service under test. This recorded traffic is curated into contracts tests by HyperTest. These contracts tests perfectly mimic any actual interaction between the consumer service and the provider service. These contract tests that capture incoming traffic, are then run on the SUT to generate response from 2 branches which are then compared and validated for contracts [+data]. Benefits of Testing Microservices The HyperTest Way Service level contract tests are easy to build and maintain. HyperTest builds or generates these tests in a completely autonomous way. The provider can make changes to their APIs without breaking upstream services. Reduces the need for developers to talk to each other and coordinate, saving time and unnecessary communication. HyperTest localizes the root cause of the breaking change to the right service very quickly, saving debugging time. Very easy to execute, since contract[+data] tests can be triggered from the CI/CD pipelines . Conclusion The traditional testing pyramid is no longer suitable for testing microservices. Microservices architecture requires new testing strategies that can address the challenges that come with this architecture. The contract[+data] is the best alternative testing strategy that can be used to test microservices effectively. This testing strategy focus on testing the API and the interactions between services rather than testing the application as a whole. Adopting this testing strategy will help organizations achieve the scalability, flexibility, and agility that come with microservices architecture. Schedule a demo today to let HyperTest help you in achieving your contract[+data] testing. Related to Integration Testing Frequently Asked Questions 1. What is Testing Pyramid? The Testing Pyramid is a concept in software testing that represents the ideal distribution of different types of tests. It forms a pyramid with a broad base of unit tests (low-level), followed by integration tests (middle-level), and topped by a smaller number of end-to-end tests (high-level). This pyramid emphasizes the importance of testing at lower levels to ensure a stable foundation before conducting higher-level, more complex tests. 2. What kind of tests are performed in the test pyramid? The Testing Pyramid includes Unit Tests, which check individual parts, Integration Tests that validate component interactions, and End-to-End Tests to ensure the entire system works as expected. It emphasizes testing comprehensively while prioritizing efficiency and early issue detection. 3. Does inverting the test pyramid make sense? Inverting the test pyramid, with more end-to-end tests and fewer unit tests, can be justified in some cases based on project needs, but it has trade-offs in terms of speed and maintainability. Adding contract tests and removing or reducing the end-to-end tests can significantly help get the microservices testing right in place. For your next read Dive deeper with these related posts! 10 Min. Read What is Microservices Testing? Learn More 05 Min. Read Testing Microservices: Faster Releases, Fewer Bugs Learn More 07 Min. Read Scaling Microservices: A Comprehensive Guide Learn More

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Contract testing focuses on the interactions between services rather than the entire system. This type of testing helps to reduce the complexity and dependencies of E2E testing, leading to faster feedback loops and more cost-effective testing. 11 April 2023 04 Min. Read Contract Testing: Microservices Ultimate Test Approach Implement Contract Testing for Free WhatsApp LinkedIn X (Twitter) Copy link Microservices enable developers to work with greater autonomy, allowing for the development and deployment of individual services independently. This is often viewed as a critical component of a successful microservice strategy, providing flexibility to teams. However, this autonomy comes at the cost of increased uncertainty. Autonomous execution=Independent deployments The freedom to make changes to one service can result in breaking changes to other dependent services. This rapid pace of change can introduce new failures at an accelerated rate, making multi-repo systems more susceptible to unintended errors. Given the inherent rapid development associated with microservices, teams must thoroughly test each service separately and in conjunction with others to evaluate the overall stability and quality of these distributed systems. Where E2E Testing Approach Lacks? End-to-end tests are positioned at the top of the testing pyramid , a concept introduced by Martin Fowler. Their primary purpose is to verify the functionality of all services operating together as a cohesive system in a production-like environment. Despite their potential benefits, e2e tests have several limitations and drawbacks. End-to-end (E2E) testing is costly because of the complex and expensive resources that are required during the test execution coupled with the long execution times required. This becomes even more challenging when E2E test suites are integrated into a continuous integration (CI/CD) environment, where they are executed with each repository change. One major concern is their tendency to be unreliable and prone to unexpected failures. Factors such as environmental changes or third-party integrations can impact their execution, leading to false positives. Additionally, given their broad scope, end-to-end tests can uncover a range of issues, including: One of the most significant issues is creating simulations and shadow environments that accurately reflect the production environment . This can be both expensive and resource-intensive, especially for systems with multiple microservices. Furthermore, all the services involved in a system need to be kept up and running, increasing the complexity and time required to maintain the tests. In addition, testing every aspect of a system may not always be feasible, and end-to-end testing may not provide insight into the root cause of a problem, making it difficult to isolate and resolve issues. Another challenge with e2e testing is that it may not detect errors or problems that occur at the component level, particularly when components are tested in isolation. This can result in compatibility and integration issues when the components are combined. When contrasted with other test varieties, these tests undeniably exhibit the slowest performance. Developers can anticipate a substantial waiting period before receiving feedback regarding the status of their modifications. The broader the scope of a test, the more challenging it becomes to create, run, and maintain it. Agile teams worship speed and don't want their release velocity to be slowed down by their testing approach. So, clearly, end-to-end testing is out of the question when it comes to microservices; they will only cause your system to fail. What’s the right approach, then? In the context of microservices, a consumer-provider model is utilized, where one microservice depends on another to complete specific tasks or provide data. Communication between these microservices is facilitated via a well-defined API over a network. The integration and communication between various services are the backbone of the entire system, and ensuring that this integration remains functional and up-to-date can effectively address the challenge of testing microservices . A specialized approach is required that concentrates on verifying the interaction points between different services, which is precisely the opposite of what E2E (end-to-end) tests aim to accomplish. Contract Testing to the Rescue Contract testing is a testing technique that focuses on the interactions between two or more services in a microservices architecture . Contract testing focuses on the interactions between services rather than the entire system. This type of testing helps to reduce the complexity and dependencies of E2E testing, leading to faster feedback loops and more cost-effective testing. The goal of contract testing is to ensure that each service meets the contract requirements specified by the other services it interacts with. This helps to identify issues that may arise due to changes in the behavior of the service without having to perform end-to-end testing. Contract testing is one of the most frequently used testing techniques in microservices architectures, according to a survey by the Continuous Delivery Foundation. As per one survey, 36% of respondents reported utilizing contract testing. Contract testing is considered the most effective and efficient way to test interservice integration, eliminating the need for expensive end-to-end (E2E) tests and the hassle of maintaining all services. These tests help identify and prevent issues and bugs that can arise when multiple components are integrated together, speeding up the development process and providing fast feedback loops to developers. Contract testing also reduces infrastructure costs by reducing the number of tests required to be run in a deployed environment. It supports the scalability of microservices by accelerating the testing process, making it easier to develop at scale. Additionally, contract testing empowers developers to take ownership of their code by ensuring comprehensive and detailed contracts. How can HyperTest help your microservices? The hardest thing about testing microservices is having the ability to test the different communication between these services. Our suggested approach to counteracting this issue is to use unit testing with smart mocks. HyperTest sits right on top of each of your microservice, recording and monitoring every little interaction that your services have with each other. Once it is done recording, it will create mocks of the communication that takes place between two services. So that, the next time, the test will run against the mocks and the need to keep the dependent services vanishes. If you make any changes in any of the services, all the dependent services will be notified via Slack about the change. Once you approve of the change, all the mocks will be updated automatically without you having to write the tests manually. HyperTest will run the auto-generated integration tests for each of your services, so that the mocks will never become out-of-sync and are always updated whenever you make changes. Not only this, but once HyperTest's SDK is initialized on each of your service, it generates an observability chart that reports all upstream-downstream pairs i.e. relationship between all services . Get Your Microservices Dependency For Free Coming up next, we'll delve into the intricacies of unit testing by demonstrating the clever utilization of updated mocks, accompanied by a comprehensive overview of all the cutting-edge tools at your disposal. Stay tuned! Meanwhile, be sure to peruse our all-encompassing white paper devoted entirely to scrutinizing microservices integration . Discover the obstacles that the ride-hailing titan, Uber, encountered with their microservices infrastructure, and explore the effective measures they implemented to overcome them. For more information, visit the HyperTest website now ! Here's a Tailored Approach To Test Microservices: Check out our other contract testing resources for a smooth adoption of this highly agile and proactive practice in your development flow: Tailored Approach to Test Microservices Comparing Pact Contract Testing and Hypertest Checklist For Implementing Contract Testing Related to Integration Testing Frequently Asked Questions 1. What is Contract Testing? Contract testing is a quality assurance technique used in microservices architecture. It verifies that communication between microservices adheres to predefined contracts, ensuring compatibility and preventing integration issues when services change. 2. What is Contract Testing for Microservices? Contract testing for microservices is a method of verifying that communication between individual microservices complies with predefined contracts or specifications. It ensures that the services understand and interact with each other correctly. By validating contracts, contract testing helps prevent integration issues and maintains compatibility as services evolve independently, supporting the robustness and reliability of a microservices-based system. 3. What is contract Testing vs unit testing? Contract testing verifies interactions between different software components, like microservices, to ensure they conform to predefined contracts. Unit testing, on the other hand, tests individual units or functions in isolation to validate their correctness. While unit testing focuses on isolated components, contract testing emphasizes the integration and collaboration between components, especially in distributed systems like microservices. For your next read Dive deeper with these related posts! 07 Min. Read Contract Testing for Microservices: A Complete Guide Learn More 14 Min. Read PACT Contract Testing: A Step-by-Step Guide Learn More 09 Min. Read Top Contract Testing Tools Every Developer Should Know in 2025 Learn More

Discover the digital frontier with our Top 10 API Examples blog, spotlighting interfaces like Facebook Graph and Google Maps for seamless integration! 11 December 2023 08 Min. Read Top 10 Popular API Examples You Should Know WhatsApp LinkedIn X (Twitter) Copy link Download the 101 Guide In the digital era we live in today, APIs have emerged as pivotal elements in the software development landscape. Imagine a bustling city where each building represents a different software application. Just as a city's infrastructure connects these buildings through roads, bridges, and public transportation, APIs interlink these software applications, allowing them to communicate and share data seamlessly. APIs define the rules for how software components should interact, much like how traffic signals regulate the flow of vehicles on the roads. This set of rules ensures that even if the internal workings of a software application are complex and intricate, the way it communicates with the outside world remains standardized and straightforward. This article is all about explaining the meaning of an API in the simplest manner, following which we’ll explore the ten most widely used APIs and their usage, providing insightful API examples. What is an API? An API, or Application Programming Interface, is a crucial component in the world of software development. To understand what an API is, let's explore both technical and non-technical perspectives. Technical Perspective: From a technical standpoint, an API is a set of protocols, routines, and tools for building software applications. It specifies how software components should interact, including the kinds of calls or requests that can be made, how to make them, the data formats that should be used, and the conventions to follow. Essentially, it's a contract between different software components on how to communicate with each other, where the "terms" of the contract are defined by the functions and methods that developers can call. APIs are often used to enable the integration between different systems. For instance, a web API can allow a web server to interact with third-party services or clients like browsers. It plays a crucial role in the development of applications that leverage services like cloud computing, mobile app development, and platform as a service. Non-Technical Perspective: To understand APIs in a non-technical way, think of an API as a waiter in a restaurant. When you sit down to eat, you have a menu with choices of what to order. The kitchen is the system that will prepare your order. What's missing is the link to communicate your order to the kitchen and then to deliver your food back to your table. That's where the waiter, or the API, comes in. The waiter takes your order, communicates it to the kitchen, and then brings your food back to you. In this analogy, the menu is the documentation of the API, telling you what requests you can make. In this sense, an API simplifies complex processes by providing a ready-to-use interface. You don't need to know how the kitchen works to get your meal, just as you don't need to know the inner workings of a software component to use its functionalities. The API handles all the behind-the-scenes work. Read more - What is API Testing? A Complete Guide How To Make Use Of An API? Using an API might sound complex, but it can be quite straightforward. Here’s a simple, step-by-step guide to help you understand how to make use of an API, accompanied by practical API examples to demonstrate each step. Step 1: Choose the Right API for Your Needs Identify Your Requirement: What do you want to achieve? For example, do you want to add weather information to your website, or are you looking to process payments? Look for an API that fits your requirement. There are many public APIs available for different purposes, like Google Maps for location services or Stripe for payment processing. Step 2: Understand the API Documentation Read the Documentation: Once you've chosen an API, read its documentation. This is like reading the instruction manual. It will tell you how to connect to the API, what requests you can make, and the format of responses you will receive. Look for the base URL of the API, authorization requirements, request format, and the structure of responses. Step 3: Get the Necessary Credentials Register or Sign Up: Many APIs require you to create an account and get an API key. This key is like a unique ID that identifies your requests to the API. Treat your API key like a password. Don’t share it publicly. Step 4: Make a Test API Call Use API Tools: You can use tools like Postman or even a simple code snippet in a language like Python to make a test API call. Follow the examples in the API documentation to make a basic request. This could be something like fetching current weather data from a weather API. Step 5: Handle the API Response Check the Response: When you make a request, the API will respond with data. This is usually in a format like JSON or XML. Use the data in your application. For instance, you might display the weather data on your website or use payment information to confirm a purchase. Step 6: Integrate the API into Your Application Coding: Use your programming skills to integrate the API into your application. This means writing code that sends requests to the API and handles responses. Test thoroughly to ensure that the API is integrated properly and works as expected within your application. Step 7: Monitor and Maintain Keep an Eye on API Usage: Monitor how your application is using the API. Ensure you're not exceeding usage limits. APIs can change. Keep an eye on any updates or changes to the API and update your application as needed. What are APIs Used For? APIs are like the versatile tools in a digital toolbox, each designed for specific tasks but collectively transforming the way we interact with technology. Their uses are as varied as the needs of the users and developers who employ them. We'll explore some common scenarios and provide real-world API examples to illustrate their applications. Data Sharing and Connectivity Enhancing User Experience E-commerce and Online Payments Social Media Integration Automation of Tasks Personalization of Content Healthcare and Telemedicine 10 API Examples of Popular Apps APIs have revolutionized how software applications communicate and function, offering diverse capabilities and conveniences. Here, we delve deeper into some of the most prominent APIs in the tech world, highlighting their unique features and the trends they are setting in the industry. For this section of API examples, we will use a mix of all time most popular APIs along with the widely used APIs of 2023. Let’s dive deep and have a better understanding of these APIs showcasing practical API examples to highlight their functionalities and significance in the tech ecosystem. 1. Notion API Fork: 50k+ Notion API is a gateway to integrating with Notion's all-in-one workspace. It provides endpoints for reading, updating, creating, and deleting data, allowing developers to build custom workflows and connect Notion with other apps. It stands out for its flexibility in handling various data types — from text and images to databases. It's particularly popular for automating content management and enhancing collaborative workspaces. The rise in remote work and digital collaboration has led to a surge in demand for tools like Notion, and its API plays a critical role in this ecosystem. 2. ChatGPT API This API provides access to advanced language models capable of understanding and generating human-like text, making it ideal for chatbots, content creation, and language analysis tasks. The API is at the forefront of leveraging deep learning for natural language processing, offering unprecedented accuracy in understanding context and nuances in language. As businesses seek to improve customer engagement and automate communication, ChatGPT’s API is becoming a go-to solution for its versatility and advanced capabilities. 3. WhatsApp API Fork: 50k+ This API allows businesses to automate, sort, and quickly respond to messages. It’s designed for medium and large businesses to provide customer support and deliver notifications. The API enables businesses to reach customers on a platform they use daily, making interactions more personal and efficient. With the growing emphasis on personalized customer service, WhatsApp API is increasingly being adopted for its convenience and wide reach. 4. Google Maps API Fork: 20k+ It offers extensive capabilities in mapping, location, and route planning. Developers can embed maps, create custom overlays, and extract location data for their applications. The API has evolved to include features like real-time traffic updates, street view, and detailed location data, making it indispensable for location-based services. The API is crucial for businesses focusing on delivery services, travel, and real estate, where accurate geographical information is key. 5. Stripe API Fork: 20k+ Stripe’s API stands out for its robust, secure, and easy-to-integrate payment processing capabilities. It supports a wide range of payment methods and currencies. It continuously adds new features like machine learning-based fraud detection, making online transactions safer and more reliable. The growth of e-commerce and online marketplaces has made APIs like Stripe more critical than ever, offering businesses a scalable payment solution. 6. GitHub API This API allows programmatic access to GitHub’s vast repository platform. It enables automation of workflows, repository management, and integration of GitHub with other tools. It supports a collaborative development environment, making it easier for developers to contribute to projects, track issues, and manage changes. With the rise of open-source and collaborative projects, the GitHub API has become a staple in the developer community for streamlining software development processes. 7. Slack API Fork: 50k+ Slack's API lets developers build custom integrations and bots, enhancing communication within teams. It can automate tasks, send notifications, and sync with other business tools. The API has been instrumental in creating more interactive and productive workplace environments, allowing for seamless integrations with various business tools. As remote work becomes more prevalent, APIs like Slack’s are vital in creating an interconnected digital workplace. 8. PayPal API Fork: 50k+ It offers a broad range of functionalities for processing online payments, including direct payments, recurring payments, and payment tracking. The API provides a secure and user-friendly way to handle transactions, vital for building trust in e-commerce platforms. With the global increase in online shopping, the PayPal API plays a crucial role in facilitating secure and convenient transactions across borders. 9. Discord API It enables the creation of custom bots and integrations to enhance user interaction on the Discord platform, popular in gaming and community-building. The API allows for a high degree of customization, fostering a diverse range of community-driven features and integrations. As community-driven platforms gain popularity, APIs like Discord’s are crucial in providing the necessary tools for community engagement and management. 10. Twilio API Fork: 2k+ Twilio’s API specializes in embedding communication services like voice, SMS, and video into applications. It is known for its scalability and reliability. The API has been pioneering in making communication more programmable and versatile, adapting to various business needs. In a world where timely and multi-channel communication is key, Twilio’s API has become indispensable for businesses looking to connect with customers in personalized ways. Need of API Testing API testing is not just about checking if an API works; it's about ensuring that it works correctly, securely, reliably, and quickly. As the use of APIs continues to grow in software development, the importance of thorough API testing becomes increasingly paramount. It's a fundamental process that supports the creation of high-quality, robust, and secure software applications. 👉 Early Problem Detection 👉 Ensure Contract Compliance 👉 Security Assurance 👉 Performance Verification 👉 Reliability and Stability 👉 Integration and End-to-End System Testing 👉 Compliance with Regulations Simplifying API Testing with HyperTest HyperTest makes API testing incredibly straightforward and effective. It's a popular choice among various companies, such as Nykaa, PayU, Porter, Urban Company, and Fyers, thanks to its user-friendly, codeless approach to test automation. This innovative tool diligently tracks down bugs and errors, ensuring they are addressed before your software goes live. 👉The way HyperTest works is by keeping an eye on your network traffic. This method is highly efficient because it automatically covers a wide range of testing scenarios that might otherwise be missed. 👉One of the standout features of HyperTest is its 'record and replay' technique. This approach is not only easy to set up but also exceptionally effective, especially for regression testing of apps. For the Quality Assurance (QA) team, this means a significant reduction in workload, as the tool does most of the heavy lifting, ensuring thorough testing with minimal effort. Interested to see how HyperTest catches bugs in your software too? See it live here . Frequently Asked Questions 1. What are APIs used for? APIs serve as bridges between different software, allowing them to exchange data and functionality. They enable developers to integrate services, access features, and build upon existing applications, fostering connectivity and innovation in the digital realm. 2. Why are APIs important? APIs are crucial because they facilitate seamless communication between diverse software systems. They enable developers to access and leverage functionalities from various applications, fostering integration and interoperability. APIs play a pivotal role in driving innovation, allowing the creation of diverse and interconnected digital experiences across platforms and services. 3. What are common APIs? Common API examples include social media APIs like Facebook Graph API, payment gateways like Stripe API, and mapping APIs like Google Maps API. Additionally, web development often involves RESTful APIs, such as those provided by GitHub. These interfaces empower developers to integrate functionalities like social sharing, online payments, and mapping services into their applications. For your next read Dive deeper with these related posts! 07 Min. Read What is API Testing? Types and Best Practices Learn More 10 Min. Read Top 10 API Testing Tools in 2025: A Complete Guide Learn More 07 Min. Read Top 6 API Testing Challenges To Address Now Learn More

This Guide delves right into the transition journey of MAANG from monoliths to microservices, providing the underlying approaches they used to successfully run more than 1000 microservices as of today. Scaling with Microservices MAANG'S Experience This Guide delves right into the transition journey of MAANG from monoliths to microservices, providing the underlying approaches they used to successfully run more than 1000 microservices as of today. Download now Prevent Logical bugs in your database calls, queues and external APIs or services Book a Demo

Explore the essentials of smoke testing in software development, its role in early bug detection, and how it ensures software quality and efficiency. 12 January 2024 09 Min. Read What is Smoke Testing? and Why Is It Important? WhatsApp LinkedIn X (Twitter) Copy link Checklist for best practices Smoke testing, in the world of software development and quality assurance, is a bit like checking if a newly constructed chimney can handle smoke without leaking. It's a preliminary test to ensure the basic functionality of a software application before it undergoes more rigorous testing. The term "smoke testing" is borrowed from a similar test in plumbing, where smoke is blown through pipes to find leaks. What is Smoke Testing? Imagine you've just baked a cake (your software application) and you want to make sure it's not a complete disaster before serving it to guests (end-users). Smoke testing is like quickly checking if the cake looks okay, smells right, and isn't burnt to a crisp. It's not about tasting every layer and decoration (that's more detailed testing), but making sure it's not an outright flop. Smoke testing is a sanity check for software. It's about making sure the basic, critical functions work before you dive deeper. It's like checking if a car starts and moves before you test its top speed and fuel efficiency. This approach helps in catching big, obvious issues early, saving time and effort in the development process. Let's say you've built a new email application. A smoke test would involve basic tasks like ensuring the app opens, you can compose an email, add recipients, and send the email. If the app crashes when you try to open it, or if the 'send' button doesn't work, it fails the smoke test. This quick check can save you and your team a lot of time because you identify major problems before you get into the nitty-gritty of testing every single feature in depth. What’s the need of Smoke Testing? Smoke Testing plays a crucial role in the software development lifecycle, serving as a frontline defense in identifying critical issues early. Its necessity can be understood through a blend of technical and pragmatic perspectives. 1. Early Bug Identification: It quickly reveals glaring defects or system breakdowns post a new build or update. This early detection is vital, as fixing bugs in later stages of development becomes exponentially more complex and costly. 2. Verifying Build Stability: Smoke Testing checks the stability of a software build. If the fundamental components are malfunctioning, it's a signal that the build is unstable and not ready for further, more detailed testing. 3. Continuous Integration and Deployment (CI/CD) Support: In the world of CI/CD, where software updates are frequent and rapid, Smoke Testing acts like a quick health check-up, ensuring that each new release doesn't disrupt basic functionalities. 4. Resource Optimization: Smoke Testing helps in efficiently allocating resources. By catching major flaws early, it prevents wastage of time and effort on a faulty build. 5. Customer Confidence: In the competitive software market, user trust is a valuable currency. Regular smoke tests ensure that the most visible parts of the software are always functional, thereby maintaining user confidence and satisfaction. 6. Foundation for Further Testing: Smoke Testing lays the groundwork for more comprehensive testing methods like functional testing , regression testing , and performance testing. It ensures that these subsequent testing phases are built on a solid, error-free foundation. 7. Agile and DevOps Environments: In Agile and DevOps methodologies, where quick product iterations and updates are the norms, Smoke Testing aligns perfectly by offering rapid feedback on the health of the software. Who performs Smoke Testing? Smoke testing is primarily conducted by Quality Assurance (QA) Testers, who specialize in identifying critical functionalities for initial testing. In Agile and DevOps environments, Software Developers often perform these tests to ensure their recent changes haven't disrupted the software's core functions. This collaborative approach ensures early detection of major issues, maintaining software quality and stability. How to perform a Smoke Test? Smoke testing is a straightforward but essential process in the software development cycle. It's like a quick health check for your application. Here's a general breakdown on how you can effectively conduct smoke testing: Choose Your Testing Approach : Initially, you might opt for manual testing, especially when your application is in its early stages. As it grows and becomes more complex, automating your smoke tests can save time and effort. For instance, you can use tools like Selenium for web applications to automate repetitive tasks. Develop Test Scenarios : Identify the key functionalities of your software that are critical for its operation. For example, if you're testing a web application, your scenarios might include launching the application, logging in, creating a new account, and performing a basic search. Define clear pass/fail criteria for each test case, aligned with your software's requirements and organizational standards. Craft the Smoke Tests : Depending on your approach (manual or automated), write the test cases. For automated tests, you'll write scripts that perform the required actions and check for expected outcomes. For instance, in a Python-based testing framework, you might have a script that navigates to a login page, enters user credentials, and verifies that login is successful. # Example Python script for a simple login smoke test from selenium import webdriver driver = webdriver.Chrome() driver.get("") driver.find_element_by_id("username").send_keys("testuser") driver.find_element_by_id("password").send_keys("password") driver.find_element_by_id("login-button").click() assert "Dashboard" in driver.title driver.quit() Execute and Document the Tests : Run the smoke tests and record the outcomes. This can be done manually by testers or automatically by the test scripts. Ensure you have a system in place for logging test results, which could be as simple as a spreadsheet or as complex as an integrated part of your CI/CD pipeline. Evaluate the Results : Analyze the outcomes of the smoke tests. If there are failures, the software needs to go back to the development team for fixes. A pass in smoke testing doesn't mean the software is perfect, but it's ready for more detailed functional and performance testing. Types of Smoke Testing Smoke Testing can be categorized into several types, each serving a specific purpose in the software development lifecycle. Manual Smoke Testing: Who Performs It: QA Testers or Developers. Use Case: Ideal for initial development stages or smaller projects. Process: Execute a series of basic tests manually on key functionalities. Pros: Flexible, requires no additional setup. Cons: Time-consuming, prone to human error. Automated Smoke Testing: Who Performs It: Automation Engineers. Use Case: Best for large, complex, or frequently updated projects. Process: Automated scripts run predefined tests on software builds. Pros: Fast, consistent, ideal for continuous integration. Cons: Requires initial setup and maintenance of test scripts. Hybrid Smoke Testing: Who Performs It: A combination of QA Testers, Developers, and Automation Engineers. Use Case: Useful for projects that need both the thoroughness of manual testing and the efficiency of automation. Process: Mix of manual and automated testing approaches. Pros: Balances flexibility and speed. Cons: Requires coordination between manual and automated processes. Cloud-based Smoke Testing: Who Performs It: QA Testers with cloud proficiency. Use Case: For applications deployed in cloud environments. Process: Smoke tests are executed in the cloud, leveraging cloud resources. Pros: Scalable, accessible from anywhere. Cons: Depends on cloud infrastructure and connectivity. Build Verification Test (BVT): Who Performs It: Typically Automated, by CI/CD tools. Use Case: Integral in CI/CD pipelines to verify each new build. Process: A subset of tests that run automatically after every build to verify its integrity. Pros: Quick identification of build issues. Cons: Limited to basic functionalities, not in-depth. Each type of smoke testing has its unique advantages and fits different scenarios in software development. The choice depends on project size, complexity, development methodology, and available resources. The common goal, however, remains the same across all types: to quickly identify major issues early in the development process. Advantages of Smoke Testing Quickly uncovers major defects at the outset, preventing them from escalating into more complex problems. Reduces time and effort spent on fixing bugs in later stages of development. Acts as a first check to ensure that the basic build of the software is stable and functional. Allows for rapid validation of builds in CI/CD practices, ensuring continuous updates do not break core functionalities. Gives a preliminary assurance that the software is ready for more detailed testing and eventual deployment. Helps in prioritizing testing efforts by identifying areas that need immediate attention, making the overall testing process more efficient. What’s the cycle of Smoke Tests? The cycle of smoke testing in software development can be visualized as a continuous loop, integral to the iterative process of software creation and improvement. Here's a breakdown of its stages: Preparation: This is where the groundwork is laid. It involves identifying the key functionalities of the software that are critical to its operation. These are the features that will be tested in the smoke test. Build Deployment: Once a new build of the software is ready - be it a minor update or a major release - it's deployed in a testing environment. This is where the smoke test will be conducted. Execution of Smoke Tests: The identified functionalities are then tested. This could be through manual testing, automated scripts, or a combination of both, depending on the project's needs. Analysis of Results: The outcomes of the smoke tests are analyzed. If issues are found, they're flagged for attention. The goal here is to determine if the build is stable enough for further testing or if it needs immediate fixes. Feedback Loop: The results of the smoke test are communicated back to the development team. If the build passes the smoke test, it moves on to more comprehensive testing phases. If it fails, it goes back to the developers for bug fixes. Iteration: After the necessary fixes are made, a new build is created, and the cycle repeats. This continuous loop ensures that each iteration of the software is as error-free as possible before it moves into more detailed testing or release. The cycle of smoke testing is a critical component of a robust software development process. It acts as an early checkpoint, ensuring that the most fundamental aspects of the software are working correctly before more resources are invested in in-depth testing or release. Disadvantages of Smoke Testing While smoke testing is valuable, it does have certain limitations: Smoke testing focuses only on core functionalities, potentially overlooking issues in less critical areas of the software. It's not designed to catch every bug, meaning some problems might only surface in later stages of development. For larger projects, conducting smoke tests manually can be a slow process. It's a preliminary check and cannot replace detailed functional or performance testing. When automated, there's a risk of missing new or unexpected issues not covered by the test scripts. Setting up and maintaining smoke tests, especially automated ones, requires additional resources and effort. Conclusion Integrating smoke testing into your development cycle is a strategic move. It's like having a first line of defense, ensuring that your software's vital operations are sound before moving on to more comprehensive and rigorous testing phases. This not only conserves valuable resources but also upholds a standard of excellence in software quality, contributing significantly to end-user satisfaction. Remember, the essence of smoke testing isn't about exhaustive coverage but about verifying the operational integrity of key functionalities. It's this focus that makes it a wise investment in your software development toolkit, steering your project towards success with efficiency and reliability. Related to Integration Testing Frequently Asked Questions 1. What is called smoke testing? Smoke testing is a preliminary software testing technique where a minimal set of tests are executed to ensure that basic functionality works without critical errors, allowing more comprehensive testing to proceed if the software passes this initial check. 2. Why is Shift-Left Testing important? A smoke test works by running a minimal set of essential tests on software to quickly check if it can perform basic functions without major errors, providing an initial indication of its stability. 3. What are the disadvantages of smoke testing? The disadvantages of smoke testing include limited coverage as it only tests basic functionality, false confidence can arise as passing smoke tests doesn't guarantee overall software quality, and it requires time-consuming setup and ongoing maintenance, potentially missing edge cases and rare issues. For your next read Dive deeper with these related posts! 11 Min. Read What is Software Testing? A Complete Guide Learn More 09 Min. Read What is System Testing? Types & Definition with Examples Learn More Add a Title What is Integration Testing? A complete guide Learn More

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Explore API testing with our comprehensive guide. Learn the basics, best practices, and tools for effective API testing. Elevate your software quality assurance. 11 January 2024 07 Min. Read What is API Testing? Types and Best Practices WhatsApp LinkedIn X (Twitter) Copy link Access the 101 Guide API testing, or Application Programming Interface testing, is a type of software testing that verifies and validates the functionality, performance and security of an API. An API is all the rules and protocols that enable different software applications to communicate with each other along with the integration of software systems to exchange data and functionality with one another. API testing can help identify software issues early in the development cycle, which allows timely fixes thereby preventing more significant problems down the line. Also, it ensures that APIs integrate smoothly with other software components, promoting efficient data exchange and system integration. And lastly, API testing enhances the overall quality and structure of the software by validating the API's functionality and performance. Basics of APIs Now that we understand the meaning of an API, let’s explore more on APIs and API testing. Starting out with how to use an API. Acts as an intermediary : APIs define the methods and data formats that applications use to communicate, thereby acting as an intermediary that allows developers and testers to leverage the capabilities of existing software without involving itself in internal workings. Data transmission: APIs use HTTP requests to transmit data, and responses are often in JSON or XML format. API keys and tokens : To use an API, developers need to obtain an API key or token, authenticate their requests, and then send specific HTTP requests to the API endpoint. The API responds with the requested data or performs the specified action. The basics of API usage requires understanding from developers and testers as it facilitates integration between applications seamlessly. This enhances functionality in harmony in software development. Why API Testing is Essential API testing is essential for ensuring smooth and problem-free functioning of software applications. APIs are the digital backbone of today’s software that enables communication between different components and systems. The testing of these APIs validates the functionality and security of these interfaces ensuring that data is exchanged efficiently, accurately and in a reliable manner. Downstream errors are prevented by developers when evaluating API endpoints, input parameters and responses as they can identify issues early in the software development lifecycle. API testing enables the detection of performance errors, scalability issues and security scares which strengthens the overall health of the software. Systems today are complex and interconnected in this modern digital era and API testing is a practice that is so important because it enhances the quality, stability and interoperability of software applications. This not only delivers a better user experience, it also reduces the risk of critical failures in the production stage. Common Challenges in API Testing Organisations today are reliant on APIs to help facilitate seamless communication between different software components. The complexity of testing interfaces grows exponentially and this comes with its own set of challenges. Let us have a look at some common API testing challenges faced by organisations. API testing, while indispensable, comes with its own set of challenges. Comprehensive test coverage : Testing all possible scenarios, edge cases, and data variations demands meticulous planning and execution and one big hurdle in this step is ensuring comprehensive test coverage because of the number of inputs and outputs that APIs handle. Maintaining test environments : API testing involves multiple endpoints, versions, and integrations, making it difficult to simulate varying scenarios accurately. Maintaining test environments that replicate today’s real-world conditions poses another challenge. Evolving nature of APIs : Another common hurdle is the evolving nature of APIs. Constant and frequent updates, changes in versions and code modifications lead to compatibility problems that break existing functionalities. Synchronisation : Synchronisation between development and testing teams is of utmost importance as understanding specifications, documentation or changes in requirements can lead to disagreements from both ends and this can affect testing processes. The key to handling challenges like these is to create reliable testing strategies, stronger understanding between teams and the determined commitment to learning and adapting to current needs of API development and testing. Types of API Testing API testing involves various approaches to ensure the reliability, security and functionality of APIs. Below are the fundamental types of API testing: Unit Testing : Unit Testing is focused on testing individual components or functions of the API but in isolation. This is done to ensure that each unit performs as intended as this helps identify and fix bugs early in the software development process. Functional Testing : Here, the primary focus is on validating the functionality of different API endpoints to detect inconsistencies and deviations from the expected behaviour. This process involves the testing of inputs, outputs and the overall behaviour of the API so that it functions as intended and in accordance with the specified requirements. Load Testing : When an API’s performance is assessed under varying levels of load or stress, it called Load Testing. This is primarily done to determine how well an API can handle different amounts of concurrent requests and data which, in turn, ensures optimal performance even during peak usage. Load testing can identify performance issues, assess response times and tweak the API to make it scalable. Performance Testing : To evaluate the API’s responsiveness, speed and scalability under varying conditions, performance testing is conducted. This includes stress testing to assess the stability of the API under heavy loads. Reliability Testing : To assess the API’s ability to deliver consistently accurate results over time, testers scrutinise the API’s response under differing conditions to ensure its dependability in real-time scenarios and this is known as Reliability Testing. Interoperability Testing : Modern applications are interconnected and interoperability testing becomes necessary in this regard. This type of testing involves evaluating the API’s compatibility with different systems and this thereby promotes smooth communication between software components. Fuzz Testing : To test API resilience and identify potential vulnerabilities, the API is subjected to unexpected and invalid inputs. This is known as Fuzz Testing and it helps unravel issues that arise due to unforeseen user inputs and data anomalies. Regression Testing : Modifications and updates to the API sometimes adversely affect existing functionalities. To avoid this outcome, regression testing is undertaken. This involves re-testing the API after changes to guarantee that it continues to work smoothly without unintended consequences. Here’s a quick guide on how you can perform regression testing of fintech apps with zero hassle, achieving results like faster development velocity and near to zero rollbacks or hotfixes . Tools for API Testing To validate the interactions between software components, API testing tools are used. These tools are essential for ensuring the reliability and security of software applications. These tools help remedy issues early in the development lifecycle. Developers greatly benefit from the use of API testing tools as it helps them to streamline testing and achieve comprehensive test coverage. Here are some API testing tools for you to consider. Assess and choose the most suitable API testing tool for your specific industry. 1.HyperTest : HyperTest is an API test automation platform that helps teams generate and run integration tests for their microservices without ever writing a single line of code. It auto-generates integration tests from production traffic, saving you time while providing maximum coverage. HyperTest helps team implement a true shift-left testing approach for their releases, which means you can catch all the failures as close to the development phase as possible. This has shown to save up to 25 hours per week per engineer on testing. Download this comparison chart between the best testing tools, and be the judge yourself. 👉 Try HyperTest Now 2. Postman : Postman is an API testing tool with an interface that is easy to grasp and perfect for creating, managing and executing API tests. It supports test automation capabilities, various request types and assertions. 3. SoapUI : SoapUI is an API testing tool that is specific to testing SOAP and REST web services. It supports data-driven testing, load testing and security testing. 4. Katalon Studio : Katalon Studio is a test automation solution that also does API testing with a very simple interface. 5. Apigee : Apigee is a full-featured API platform that has built-in API testing capabilities. It has tools for building, designing and testing APIs which is ideal for end-to-end API lifecycle management. 6. JMeter : JMeter is a load testing platform that also supports API testing. It supports HTTP, SOAP and REST and can simulate high loads to test API performance. Know more - Top 10 API Testing Tools API Testing at Netflix A pioneer in the web streaming industry, Netflix depicts successful API testing regularly. But this is also met with constant challenges. Their API testing practices play a pivotal role in delivering a hassle-free user experience. By rigorously testing APIs that handle content delivery, user authentication, and recommendation algorithms, Netflix ensures that its service functions reliably across various devices and platforms. Regular API testing allows them to quickly identify and rectify potential issues, maintaining the high standards of performance and usability expected by millions of subscribers worldwide. This approach not only safeguards the platform's functionality but also facilitates continuous innovation and adaptation to evolving user needs. Challenge: Netflix’s biggest challenge is to ensure that its APIs provide a smooth user experience across all connected devices. Solution: Netflix incorporated thorough API testing to validate the functionality, security, performance, and compatibility of its APIs across different platforms and devices. Result: Successful API testing played a crucial role in delivering a consistent streaming experience, contributing to Netflix's reputation for high-quality service. Conclusion API testing is a critical pillar in software development that allows for the smooth communication and functionality of applications. From unit testing to functional, load, and security testing, a comprehensive approach to API testing is essential for developers and QA professionals. Adopting effective testing strategies is necessary due to applications becoming interconnected and reliant on APIs. To deliver high-performing applications that meets expectations of both developers and end-users, do visit us here . Frequently Asked Questions 1. What is API full form? API Full Form is an Application Programming Interface 2. Which tool is used for API testing? Several tools are used for API testing, with some popular ones including: HyperTest, Postman, SoapUI, Insomnia. 3. What are the 3 types of testing in API? Unit Testing, Integration Testing, End-to-End Testing For your next read Dive deeper with these related posts! 10 Min. Read Top 10 API Testing Tools in 2025: A Complete Guide Learn More 09 Min. Read Best Back End Automation Testing Tools In 2024 Learn More 08 Min. Read What is API Test Automation?: Tools and Best Practices Learn More

Software testing automation tools -The surge in APIs means a respective demand for efficient API software testing to ensure they meet the required standards for functionality. 24 May 2023 10 Min. Read Efficient API Software Testing: Your Handy Guide WhatsApp LinkedIn X (Twitter) Copy link Access the 101 Guide The astounding market growth in API testing resonates with the boom in cloud applications and interconnected platforms that call for application programming interfaces (APIs). APIs work more like a contract where two parties agree about sending, receiving and responding to communication according to a set of predefined protocols. The surge in APIs means a respective demand for efficient testing to ensure that they meet the required standards for functionality, reliability, performance, and security. Without effective testing, the APIs could collapse or fail to perform impacting applications, services and business processes. Before we get into the nuances of API testing, let’s get a deeper understanding of what an API is, how it works and the context for API testing. What is (API) Application Programming Interface? API is a set of routine protocols and tools for creating software applications that are effectively synced together. It acts as a powerful intermediary between the application and the web server, seamlessly coordinating the ways the two systems interact by paying heed to the set of instructions. In other words, APIs are a simplified way to link your own infrastructure through cloud-centric app development, simultaneously permitting you to share your data with external users or clients. Public APIs are fundamental to businesses as they can simplify and build your connections and interactions with your partners. APIs give you flexibility while designing new products or tools. They open the door for innovation and simplify design. This makes administration and use easy, helping businesses and IT teams to collaborate efficiently. What causes API failures? At times, APIs do not work the way as expected due to technical or operational glitches like slow servers or connectivity, curbs by the API service vendor on subscriptions, area etc, security issues or DDoS attacks. API failures refer to the gaps that thus arise in the communication between two servers or teams. They can fail for multiple reasons. Some of the most common reasons for API failures are: ➢ Unexpected or unrecorded software changes, ➢ Communication hiccups between teams, ➢ Bad data that is incompatible with an API As software updates may not immediately register in the documentation, it can cause API glitches. An API call that worked in one version of the other program may not be compatible with the new version. An API call can be a link in a series, navigating data from upstream to downstream, and then passing the response on, either as a reply to the upstream data or sending it in a new direction. Since the origin of data is not always traceable, APIs could fail if the received data is not in the required format or in the format that the third party expects - for instance, in unacceptable characters. Also, backward compatibility may be accessible only for a limited grace period and after that non-updated API calls will not work. And if the API calls have been integrated in your code for a while, the sudden change in status may not be recorded. You will come to know only when they suddenly fail. API testing for enhanced business processes Effective API testing helps in: Checking the functioning of the software An API Testing sees that the software systems work uniformly during the unit testing phase of the development cycle. It is done to check the reliability, performance and functioning of the software. Resolving the errors In addition to this, the API testing organises the API endpoints. It helps the software programmer choose between the automation tool and the verification methods. The procedure detects the bugs at an early stage. API tests involve the entire software system and verify that all the components function as expected while other categories of testing, like unit tests verify the functionality of individual components within a single application. The broader test span of API makes it easier to identify any bugs in the unit, database, and server levels. API tests are also faster to run and more isolated than UI tests. According to data from Andersen Lab , a UI test runs for approximately seven minutes while an API test runs for 12 seconds. API Testing is important to assess that the API functions properly and can process the requests that are made. It should analyze the responses that include data quality, confirmation of authorization and reply time. API Testing is done consistently at appropriate times to make the systems run meticulously. ● Is highly effective It requires the use of fewer codes and can provide a better test coverage. Most systems have APIs and services with some specifications with the help of which one can create automated tests easily. ● Has a remarkable performance A common UI regression test suite can take 8-10 hours to operate. But an API testing system takes 1-2 hours. It is more reliable than the ordinary testing procedures and does not take hours to work. ● Does not have any language issues Any language can be used to develop the application. As the data is exchanged using XML and JSON, the language does not matter. ● Integrates with the GUI testing One can test the API without an interface. However, the GUI tests can be conducted after the API testing is done. It would allow new users to get familiarised with the programme before the test. Essentially, the API integration testing is the evaluation of the API interfaces to see if these are functioning optimally. Some of the most-popular API integration testing tools are Postman, jmeter, assertible and rest-assured. ● Reduces the testing cost The API testing can detect bugs, technical issues and teething problems at an early stage. This helps save time and money in the long run. As the errors are rectified during the initial stages, there is no scope of excessive spending. Types of API Testing API Testing must be done at the earliest stages. These ensure that the software works impeccably well and allows access to the stored data. Different tests evaluate the aspects of the API procedure and are necessary to guarantee a hassle-free digital interaction. 1. Load Testing The API load testing is done to ensure that the software applications can take on the load that the user wants them to. The API load testing tools place load on the real apps, software and websites in a controlled environment. 2. Performance testing Similarly, the API performance testing tools evaluate the ways in which API performs under a set of conditions. It is important as it identifies any issues in the API during the early stages. For instance, the nodejs API Testing is a toolkit that acts as an intermediary between C/C++ code and Node Java Script Engine. For example, the jmeter performance testing is used for web applications. With a user-friendly interface, it works on a multi-threaded framework. 3. Security Testing In this, the programmers see that the API is secure from all the external threats that might jeopardize its efficiency. If the data falls into wrong hands and is misused, the program might go haywire. The security testing sees whether the basic security requirements have been fulfilled that include access to the users, authentication concerns and the encryption. 4. Unit Testing This checks the functioning of the individual operations. It includes testing the codes, checking if the units perform well individually and is sometimes referred to as the White Box Testing . Also, it is the first step in assessing the API and helps determine the quality control process. The individual parts are tested so that these work uniformly when put together. 5. Functional Testing It includes testing different functions in the code-base. API functional testing is done with some procedures that require attention to detail. The software developers can check the data accuracy and the response time along with the authorization issues. The error codes and the HTTP status codes must be tested accurately. Practices/Methods of API Testing ● Segregate API Test cases into test categories. ● Prioritise API function calls to facilitate fast testing. ● Include the declarations of the APIs called at the top of each test. ● Provide accurate parameters in the test case. ● Keep the test cases self-contained and independent. ● Avoid test chaining in your development ● Send a series of API load tests to check the expected results and assess the efficiency of the system. ● Give attention while dealing with single call functions such as CloseWindow, Delete etc. ● Plan and perform call sequencing meticulously ● Ensure impeccable test coverage by creating API test cases for all possible API input combinations. Challenges in API Testing ● The most challenging aspects of Web API testing are parameter combination, parameter selection, and call sequencing. ● There is no graphical user interface to test the application, making it impossible to provide input values. ● For testers, validating and verifying output in a different system is a little complicated. ● The testers must be familiar with parameter selection and classification. ● You must test the exception handling function. Coding knowledge is a must for testers. Types of Bugs that API testing detects ● Functionalities that are duplicated or missing ● Unused flags. ● Security concerns. ● Issues related to multi-threading. ● False alerts errors/warnings to a caller. ● Improper dealing of valid argument values. ● Performance issues ● Dependability issues like difficulty in connection and receiving responses from the API. HyperTest & API TESTING HyperTest is a tool that eliminates the bugs and errors by integrating the applications and providing an exemplary software development. It ensures an outstanding quality and covers all forms of testing such as regression, API and integration. It can be set up in less than five minutes and provide results within a jiffy. The tool is extremely reliable and does away with the traditional methods of manual testing. It does not require an external set-up and seamlessly integrates with all the applications and interfaces. It detects and resolves all the errors before release and can increase the testing coverage. Why HyperTest Tool for API Testing? The HyperTest is suitable for the API testing procedures as it nips all the evils in the bud and provides a worthwhile digital experience. Businesses rely on the tool to assist them in the process of developing testing scripts and codes for a seamless online transaction. ● Provides complete coverage The HyperTest provides more than 95% of the app in less than 5 minutes. It is superior to other tools as it does away with the manual effort of writing scripts. Also, it helps the Devops pass on cleaner builds to the QA guys. This lessens the time taken to test an application. It auto-generates the tests by providing reliable results. It does not require manual testing that makes the teams work endlessly and develop the test scripts. Moreover, it is an API management tool that ensures security and performance. It solves the problems of API regression and makes the team focus on developing the software. It resolves the errors at the source by checking for the API issues during the nascent stages. ● Builds dynamic assertion The auto-generated tests run on the stable version of the application to effectively generate assertions. This does not allow the business owners to reveal sensitive information about their company or let the data fall be misused. It reports any anomalies that could occur and the breaking changes that might be resolved at a later stage. It makes use of real-world scenarios to build tests. ● Is Unique and highly effective Numerous companies prefer the HyperTest API testing tool because it has a unique approach. It monitors the actual traffic on the application and makes use of real-world scenarios to build the tests. Also, the teams can get access to the complete coverage reports that highlight the flow of things in the automation process. ● Can quickly detect and resolve all the errors The tool provides solutions for the applications. It removes all the bugs, helps the businesses develop worthwhile strategies and safeguard the sensitive information. Some of the software engineers fail to detect the source of the errors and how to mitigate them. Traditional tools miss more errors than these detect. The HyperTest tool detected 91% more bugs and technical issues in the systems. ● Integrates with the services The tool follows an asynchronous mirroring process with no change in the application code or configuration. It has no impact on the function and the performance. As it is cloud-operated, all the data is present in the client’s environment and never gets leaked. It is never misused and hardly lands up in the wrong hands. ● Can efficiently manage the API testing procedures The HyperTest monitors the API 24/7 and reports all the failures. It is one of the best API testing tools that solves the problem of API regression . Moreover, it eliminates the redundant test cases by maximising the coverage. By creating real-time dynamic assertions, it reports the breaking changes. It saves the time of the developers and provides the Devops team ways to speed up their processes. It reports all the errors in an effective way and helps the Devops introduce some significant changes. According to a recent survey, HyperTest saves about 40% of the man hours that developers invest in figuring out the algorithms. ● Provides useful information The HyperTest provides all the data about the API artefacts and documents the details creating a reliable repository of information. Through the regression feature, it delivers accurate results. It brings to light all the API failures and monitors the entire application process. By mirroring the TCP requests, it does not impact the application code or the function. The cloud-based environment does not let any data escape from within. It examines all the minor code changes and reports the data accurately to the system. Apart from this the HYPERTest monitors the micro-services and provides sure-shot analysis. ● Manages the authentication process The HyperTest can manage the multi-factor authentication processes really well. It can easily write the customized requests and look into the data constraints. Summing it up, the API checks the malfunctioning or the errors that might surface during the exchange of information between the computer systems. The API testing ensures that the systems run smoothly and have no technical issues. The HyperTest tool develops efficient API testing procedures and manages the authentication process. It builds a dynamic assertion and effortlessly integrated with all the services. By providing complete test coverage and closely examining the software, it has become the most-sought after API testing tool by the businesses. Takeaway You may not be able to prevent APIs from failing, but you can contain the damage, and prevent an API failure from bringing down your application as well. With the HyperTest tool, you needn’t vex over API failures anymore. Ensuring round-the-clock monitoring, the platform provides effective solutions to the API regression. With the use of upgraded testing procedures, your data can be secure and free of any anomalies that might jeopardise your reputation. To browse through the features that make the testing platform stand out in functionality and reliability and acquaint yourself with the wide array of testing procedures visit our website . Frequently Asked Questions 1. What is API Software testing? API software testing involves evaluating the functionality, reliability, and security of application programming interfaces (APIs). It verifies that APIs perform as expected, handle data correctly, and interact seamlessly with other software components, ensuring their reliability and functionality. 2. Why is API testing important? API testing is vital because it ensures that software components communicate correctly. It validates functionality, data accuracy, and security, preventing errors and vulnerabilities, ultimately ensuring reliable and efficient interactions between different parts of a software system. 3. How to approach API testing? Approaching API testing involves several key steps. Begin by thoroughly understanding the API documentation to grasp its endpoints, inputs, and expected outputs. Next, identify various test scenarios, considering different data inputs and edge cases. Utilize dedicated API testing tools or libraries to create and execute test cases, sending requests and analyzing responses. Verify that the API functions as intended and handles errors gracefully. For efficiency, automate repetitive tests and establish a robust monitoring and maintenance system to adapt to ongoing API changes, ensuring continuous reliability and performance. For your next read Dive deeper with these related posts! 07 Min. Read What is API Testing? Types and Best Practices Learn More 08 Min. 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Nykaa wanted to improve how well their app is tested by adding more test case scenarios that closely simulate real-world usage. This way, they can quickly find and fix issues, aiming for a improved customer experience. Customer Success Processing 1.5 Million Orders, Zero Downtime: How Nykaa Optimizes with HyperTest Nykaa wanted to improve how well their app is tested by adding more test case scenarios that closely simulate real-world usage. This way, they can quickly find and fix issues, aiming for a improved customer experience. Pain Points: Inefficient automation introduced defects into the production environment. Extended release cycles constrained timely deployments. Insufficient code coverage resulted in undetected vulnerabilities. Results: Achieved 90% reduction in regression testing time. Improved release velocity by 2x. 90% lesser integration defects or incidents in production. About: Founded: 2012 Employees: 4168+ Industry: Beauty and Fashion E-commerce Users: 17 million+ Nykaa is India's premier lifestyle and fashion retail destination, providing a comprehensive array of products across cosmetics, skincare, haircare, fragrances, personal care, and wellness categories for both women and men. Nykaa made an impressive stock market debut, reaching a valuation of over $13 billion. The company's shares initially listed at an 82% premium and have climbed to approximately 96%. Listed on the BSE since November 2021, Nykaa now boasts a market capitalization of $8.3 billion, underlining its significant impact and strategic presence in the beauty and lifestyle market. Nykaa's Requirements: High fidelity integration testing for a service oriented architecture. Refined automation processes to deliver tangible outcomes. Improved code coverage to minimize production defects. Challenge: Operating a dynamic e-commerce platform with daily orders exceeding 70,000, Nykaa recognized the need for a sophisticated testing approach suitable for their rapidly growing microservices. They had implemented an automation suite to safeguard their revenue and prevent defects from reaching production. Despite the deployment of a new automated system, occasional defects still appeared production. Initial automation efforts were inadequate, not fully preventing defects and causing the team to shift focus toward managing disruptive changes linked to microservice expansion. Integration testing was excessively time-consuming, with many defects originating from backend systems, affecting release velocity and product quality. Low code coverage in earlier stages meant that many potential issues went undetected until later in the development cycle, increasing risk and remediation costs. Solution: Nykaa adopted HyperTest to enhance automation and effectively test their services expansion , aiming to prevent potential disruptions. This solution streamlined their feature release process, allowing for comprehensive testing without separate test setups. HyperTest facilitated rapid integration testing for microservices, reducing the testing time from several days to mere minutes—a 70% increase in testing efficiency. This transformation boosted speed of feature releases by substantially shortened testing times. Additionally, with HyperTest, Nykaa achieved up to 90% code coverage, drastically reducing the incidence of critical bugs and vulnerabilities reaching the production environment. I have been using Hypertest for the past 2.5 years. It has made the QA cycle reliable providing the best quality, reducing a lot of manual effort, and thus saving functional bandwidth. The bugs which can be missed in automation can be easily caught with Hypertest. -Atul Arora, SDET Lead, Nykaa Read it now How Yellow.ai Employs HyperTest to Achieve 95% API Coverage and Ensure a Flawless Production Environment Read it now Airmeet and HyperTest: A Partnership to Erase 70% Outdated Mocks and Enhance Testing Speed By 80% View all Customers Catch regressions in code, databases calls, queues and external APIs or services Take a Live Tour Book a Demo

HyperTest generates integration tests that achieve over 90% coverage, ensuring fast and bug-free deployment of distributed services. WEBINAR | On-Demand | "No More Writing Mocks: The Future of Unit & Integration Testing" >> HyperTest enables developers to fix integration issues quickly Use AI agents that tests every possible scenario pre-release so that developers release on-time, without worrying about failures Request a Demo Product Live Tour Developers at the most innovative companies trust HyperTest for confident releases Why we built HyperTest? Unit tests are useful for checking the logic within a service but fail to test the dependencies between services. Integration testing comes to the rescue, but as opposed to the well-standardized unit testing frameworks, there was no off-the-shelf integration testing framework that we could use for our back-end services. Paul Marinescu Research Scientist View Source How it Works For Developers For Engineering Leaders Why Should Developers Use it? Get Powerful Integration Tests Test code, APIs, data layer and message queues end to end at the same time Automate Testing with Self-healing Mocks Use mocks that mimic external interfaces to test user behavior not just code Shift left like it needs to be Run tests locally with pre-commit hooks or at CI to catch issues early and fast Why Should Engineering Managers Consider it? Missing Delivery Deadlines Ineffective automated testing # 1 reason for slow releases High Technical Debt Complex codebase that is becoming hard to maintain with high risk for failures and downtimes Low Developer Productivity Developers spending all their time fixing issues risking burnout and no time for innovation Learn how it works 100% Autonomous Record and Replay. Generates integration tests automatically from real user traffic. Fully autonomous with Zero maintenance. 2 min. Setup Add 2-line SDK in your application code. Records tests from any environment to cover >90% lines of code in a few hours. Catch Bugs Early Run tests as automated checks pre-commit or with a PR. Release new changes bug-free in minutes, not days or weeks. Hear from our Customers HyperTest has been a game-changer for us in Integration testing. It has significantly saved time and effort by green-lighting changes before they go live with our weekly releases. Vinay Jaasti Chief Technology Officer We have recently upgraded our code framework. And by running one instance of Hypertest, we got the first-cut errors in less than an hour , which could have taken us a few days. Vibhor G VP of Engineering Hypertest unique selling point is its ability to generate tests by capturing network traffic, they have reduced the overhead of writing test cases, and its reports and integrations have helped us smoke out bugs very quickly with very little manual intervention. Ajay Srinivasan Senior Technical Lead Trace failing requests across microservices Test Service Mesh with Distributed Tracing HyperTest context propagation provides traces across multiple microservices, helping developers debug root causes in a single view. It cuts debugging time and tracks data flow between services, showing the entire chain of events leading to failure. Read More Test code, APIs, data, queues without writing tests Power of foundational models with Record and Replay Test workflows, data and schema across APIs, database calls and message queues. Generate tests from real userflows to uncover problems that only appear in production like environments Read More Shift-left with your CI pipeline Release with High Coverage without writing tests Forget writing unit tests and measure all tested and untested parts of your code. Cover legacy to new code in days. Read More Top Use Cases From APIs to Queues, Databases to Microservices: Master Your Integrations High Unit Test Coverage HyperTest can help you achieve high >90% of code coverage autonomously and at scale. We can write 365 days of effort in less than a few hours. Database Integrations It can test the integration between your application and its databases, ensuring data consistency, accuracy, and proper handling of database transactions. API Testing HyperTest can validate the interactions between different components of your application through API testing. It ensures that APIs are functioning correctly and communicate seamlessly. Message Queue Testing If your application relies on message queues for communication, HyperTest can verify the correct sending, receiving, and processing of messages. Microservices Testing HyperTest is designed to handle the complexities of testing microservices, ensuring that these independently deployable services work harmoniously together. 3rd-Party Service Testing It can test the integration with external services and APIs, ensuring that your application can effectively communicate with third-party providers. HyperTest in Numbers 2023 Year 8,547 Test Runs 8 million+ Regressions 100+ Product Teams Prevent Logical bugs in your database calls, queues and external APIs or services Book a Demo