How can Cloud Testing bring Digital Transformation?

With the increase in digital and technological advancements, there has been a surge in cloud testing services. Cloud computing facilitates easy data accessibility, efficiency, and consistency in reducing management efforts and much more. It ultimately, in this way, helps to accelerate digital transformation. By leveraging Cloud computing services, companies can ensure high-quality product delivery on time. 

This is where testing cloud applications becomes crucial. This is why delivering quality outcomes with the help of the Cloud is the way for businesses to sustain the hyper-active, technology-driven, and competitive business landscape. It is essential for companies to know that DevOps, Quality assurance, and testing strategies are basic components of digital transformation.  

In this blog, we will learn about what is cloud testing and how cloud testing accelerates digital transformation activities with efficient testing and digital quality assurance strategies. 

Let’s begin!!  

Cloud Testing: The Definition 

Also termed Cloud-based Testing, cloud testing is a kind of software testing wherein the web, or mobile-based applications leverage Cloud Computing environments so as to create real-world user traffic and environment. Cloud testing is being widely considered and used for its specific strength areas, specifically for Digital Transformation. 

How can Cloud Testing bring Digital Transformation?  

Digital Transformation, in the true sense, involves anything and everything! Software testing involves right from building applications to launching them in the market and getting feedback to further update the applications in real-time. Cloud testing, with its numerous benefits, accelerates and enhances various levels of Digital Transformation, helping companies to reduce the time to deliver in-market and ensure quality in the overall process. 

  • Seamlessness 

With a seamless and hassle-free Internet connection, the devices and applications can be accessed at any time and from anywhere. This further allows one to make changes and update applications in real-time. Meanwhile, we can say that there is no need for investment in hardware which makes the testing and development activity more flexible. Business Agility requires making strategic moves like LIVE updates, making LIVE changes within the user environment, and much more. This all again is facilitated with cloud-based testing.  

  • Access To Infrastructure 

Today, most businesses run on such strategies, mindsets, and procedures that are highly cost-effective.   In fact, companies expect the QA testers to practice methods and approaches that would ensure effectiveness in terms of the cost of testing.  Cloud testing, in this case, enables teams to access infrastructure and testing tools from any place and time, therefore, allowing them to upgrade the software or apps accordingly.  

  • Scope For Innovation 

It is really important for companies to keep innovating and developing their application on a regular basis to ensure that they are dwelling well with the pace of digital transformation. The various process like  Agile and DevOps are being leveraged to ensure that Continuous Development is followed by Continuous Testing and possibly Continuous Integration.  

loud Testing is a constant supporter of Agile as it facilitates a platform encouraging collates and also helps the teams to stay on the same page. It ultimately leads to  Continuous Integration by ensuring that the latest developed fragments are being deployed faster and teams are staying on schedule to deliver services well on time. With the constant availability of a test environment, teams are able to test the applications for performance, functionality, security, and scalability as well. 

Read more: Why cloud testing is essential?

Top 10 Tools For Web Application Testing in 2022

Web application testing, it’s a kind of software practice that ensures quality by testing the functionality of a given web application. Its entire focus is to check whether the application is working as intended or as per the requirements or not. Web testing allows you to find books at any given time, prior to a release, or even on a day-to-day basis. 

Advantages and Importance of Web Application Testing 

As mentioned, the demands of enterprises are surging day by day with an increase in technological advancements. Also, to strive in the competitive market landscape, it is important to ensure that the quality of the website or application is maintained. In this case, web application testing plays an important role in how your customers perceive the company and turn how much faith they have in its products.   

Moreover, in today’s world, the Internet has become an integral part of all of our lives. Most of us make a decision by searching for information on the Internet, and this is the reason why web applications are becoming a mandate for all kinds of businesses. Undoubtedly in this scenario, to ensure the quality and effectiveness of the app, rigorous testing of the website and the application becomes crucial. 

Testing is really an important part of software development. Whenever there is a code change, bugs can appear somewhere else in the system, also the cost of fixing these bugs can rise with time. This is why it’s important to leverage a good web application testing service provider so as to ensure that your time and money all turn out to be fruitful. 

Most Demanded Web Application Testing Tools Of 2022 

Web application testing is the heart of a good web application. Companies all over are focusing on web application testing to offer a seamless performing web application with an excellent user experience.  

Catering to its importance, it’s undeniable that there are lots of web application testing tools available in the market. In this blog, one will know about the best web application testing tools that are highly preferred and highly demanded for quality assurance testing services, finding even a minute error in the web-hosted application. 

WebLoad   

  • It is one of the most efficient web application performance testing tools for web-hosted applications. 
  • Its main focus is to signify the load handling capability of the website application. 
  • By opting for this tool, it’s easy to test complex tasks as there is a powerful scripting potential embedded there. 
  • Performance-related issues, errors, bottlenecks, and loopholes in the application can be detected and defined using this tool 
  • It guarantees the high response efficiency of your web application. 
  • It is integrated with selenium, Jenkins, and various other tools to enhance its testing power. 

Netsparker 

  • It is one of the best web application testing tools, which is known for its accurate results. 
  • It has an inbuilt security scanner embedded to identify the minor and major loopholes in almost all web APIs. 
  • This tool is best to identify the faults and bottlenecks and ensure whether they are real or false. 
  • One can use this tool either as a windows software or even as an online service provider. Howsoever the features and efficacies would remain the same in both the versions. 

Test IQ   

  • It is one of the best web application testing tools that ensure your applications work seamlessly without any possibility of bugs and errors. 
  • It goes well with crowd testing as, with this tool, the apps are tested under real-world conditions. 
  • Some of the additional features that make test IQ the best web application testing service include feedbacks from real humans, faster releasing, and real device testing to find the core and the root of the problems. 

Experitest   

  • This tool allows the users to test web applications over 1000 devices at a time over the cloud. 
  • Both manual and automated cross browsing tools are meant for testing the web application in this tool. 
  • It goes well with any browser. 
  • It is integrated with APM and selenium for better results. 
  • This tool has the potential to run over 100 tests altogether in parallel.
  • It also allows you to perform visual testing to determine the efficiency of UI responsiveness over different resolutions. 

Read more web app testing tools

Benefits Of Cloud-based Test Automation

Going a few years back in time, website development or software engineering were entirely different concepts. However, the introduction of innovations like artificial intelligence, machine learning, cloud, DevOps, and QA have all made way for extensive transformation.  Especially, the ever-growing focus on quality assurance and software testing have made quality assurance services a vital part of software development lifecycle. More importantly, the evolution of QA as a process from manual to automation testing has delivered all the necessary speed to the software testing initiatives.  

While manual testing was already adding the necessary precision to software testing for on-prem and cloud, cloud-based test automation has revealed much bigger potential. Especially the availability of a huge number of test environments adds much more depth to test initiatives while shortening the feedback loops, fixing bugs, and quicker releases. 

All in all, continuously delivering improved software allows you to create a much more progressive user experience for your end-users. Besides, it serves as a link between improved customer experience and revenue, keeping all things documented.  

In this blog, we will aim to underline how cloud-based test automation could help deliver all the necessary speed and scalability to your digital innovations. But before we jump on the same, let us quickly jump on the benefits cloud-based test automation could bring to your business.  

Cloud-based Test Automation Benefits:

Most of the time, QA teams working on cloud test automation are involved in exploratory testing which is used as a tool to refine user journeys for cloud-based products. As cloud offers increased access to test environments, it enables testers to experience quicker exploratory testing. 

Also, the faster and improved access to insights on cloud-based test automation adds to the test coverage, streamlining all the unknowns. Apart from this, exploratory testing could be injected with AI to auto-generate test cases covering possible user-journeys which cannot even be guaranteed with manual testing.  

On that note, let us quickly jump on benefits that cloud-based test automation could bring to your digital initiatives: 

Scalability 

The best thing about cloud testing is the support it offers on scaling IT resources with minimal disruption. The same goes for cloud-based automation testing as it allows working on any changing requirements of the organization with quick scalability on test execution supporting increase or decrease of testing capabilities. It therefore allows preventing conflicts arising within teams due to limiting or changing resource requirements. Above all, it helps testers to quickly pursue any requested feature or any annoying bug that causes issues on an existing product module which is usually not easy with limited test environments.  

Cloud-based automation testing allows teams to meet their testing objectives within the touch of a button. Adding to that, the convenience of cloud can be witnessed at all times with immediate availability of testing infrastructure. Ultimately, it solves the hassle of any delays or process limitations that might happen due to lack of hardware or local installation issues.  

Parallelization  

Another significant benefit that comes with cloud-based automation testing is the advantage of scaling test execution. Parallelization allows test teams to spin up multiple pre-configured test environments mimicking different testing parameters of product under test.  

Working on cloud-based test automation even allows you to run different software versions of the same application on virtual machines. On contrast, it even allows running same software across different operating systems and devices. When testing is completed for these environments, the results are reported back, and the machines can be spun down and destroyed with no user data retained.  

Furthermore, it helps optimizing and expanding the test coverage through exploratory testing. Besides, a model-based approach can be added to the process creating one final model that can simultaneously execute tests for multiple systems under test.  

Improved Collaboration 

Whether you are working in an office cubicle or anywhere in the middle of the world, cloud enables collaboration. And therefore, QA and Dev teams can collaborate in real-time overcoming the limitations of siloed teams.  

Cloud-based automation testing allows multiple teams working together in collaboration to experience faster feedback loops and have greater visibility on CI/CD pipeline. All in all, cloud-based test automation helps accelerate the entire process of development to deployment offering necessary business competitive advantage.  

Read more: Cloud-based testing

Ways AI can Automate Routine Tasks

Voice recognition, autonomous vehicles, healthcare, education, banking, and software testing!! AI has impacted every field with its dominance. We all continue to witness a surge in technological advancements. With this, AI’s role in our lives is only growing bigger. According to oberlo.in, the market size of artificial intelligence was valued at $51.08 billion in 2020, which is projected to reach $641.3 billion by 2028.  

Adopting AI practices can have many benefits for a business and its employees. It can yield higher quality, improved and increased reliability, and consistent output.  

Automation of routine tasks with the help of AI can help workers/employees spend more time on creative or complex tasks that provide enhanced value to the company and its customers.  

Also, they are not overlooking the fact that these technologies will radically transform the way of work and the workplace itself. Machines and AI technologies will be able to carry out more tasks done by human beings, complement and enhance the work done by humans, and even perform some tasks beyond what humans can do.  

With all these years of watching automation from so close and delivering AI testing solutions that were meant to align with future, let’s look at the ways AI can automate routine tasks!  

Ways AI can Automate Routine Tasks

1. Automating Customer Support and Service 

  Adopting or leveraging the chatbots option for automated customer support can help in saving a lot of time. 24/7 availability of Chatbots for customers can assist in automatically answering your questions, providing recommendations, and directing you to decide and strategize about the next step of your customer support strategy.  Furthermore, Chatbots can gather intelligence on customer needs, engagements, and emotions which can further help in boosting business profits.   

2. AI: The Game Changer Of Software Testing 

 AI technologies and tools can learn different user flows and thereby facilitate the creation of test cases based on accurate user data, increasing test coverage and making automated testing much more effective.  

This also means testers will not need to spend time generating test data based on production users since this step will be done by AI automatically. This will make testing more effective and help to increase test coverage, making it easy for user flows.  

With the help of AI, Users can register tests independently and use tests created automatically. This would further generate efficient automated test sets. In this way, even people with negligible technical knowledge can augment software testing coverage, thereby further increasing the productivity of the entire team. 

Advantages Of AI In Automated Software Testing: 

  • Visual validation by performing visual testing on applications 
  • Increased and improved accuracy and efficiency 
  • Better test coverage  
  • Reduction in costs and defects 
  • Saves time and faster time to market. 
  • Editing content in less duration 

AI technologies can edit the content produced in real-time, thereby developing an infinite number of variations. Shots will be switched out, and music and sound effects will change on the fly, all dictated by real-time user engagement and the personal features of the one viewing it.  

3. Creating Jobs And Integrating Human Workflows 

  With the help of Artificial intelligence in the workplace, creating jobs can be automated. This will also integrate the workflows. This is not only where it will stop, but also the workplace structure will continue to change due to AI and automation views radically. However, not forgetting that humans will play an integral role in making sure these worlds (AI and routine world) combine efficiently and effectively.   

4. Channelizing Future Strategies And Planning   

Every business today involves building strategies that will help enhance its overall business. Human beings or PR personnel are also crucial in building clientele relationships when talking about the PR industry. However, the teams can collect the data through AI and automation tools and services. This will eventually help in informing future strategies. This intelligence will specifically become a helping aid when it comes to media monitoring and ensuring that companies are able to stay abreast of competitor news and coverage.   

Read more: How AI can help automate complex routine tasks?

What Should You Include In Big Data Testing?

Organizations today are constantly looking for different ways to leverage the dominance of big data to gain a competitive edge over their competitors. A massive set of raw data needs a careful design in testing to ensure the desired outcomes are achieved when the application or particular service goes live. Also, not forgetting that testing becomes crucial with the exponential growth in the number of big data applications globally. 

Although Google hasn’t shared the exact number, however, according to skai.io, Google handles around 3.8 million searches per minute globally.  

Today, Internet has become so powerful and dominant because of data. Whenever people search for something, it’s always about searching for data about data. And this is possible and fruitful only because someone has preserved this information when you search for it somewhere over the Internet. Again, it’s all due to the technology that is evolving. With the advancement of technology, we also witness a surge in demand for substantial data applications, which obviously need extensive focus on software testing services. 

Decades back, data was preserved by using simple data files. However, when the complexity of data grew, database management came into existence. A few years later, both structured and unstructured data were generated at a giant level, thereby gaining a term called “big data.”  

In this blog, we will learn what big data testing is, its benefits, and the effective strategies to implement it. Let’s begin!!  

What Is Big Data Testing? 

In simple words, big data testing is a software testing procedure that involves examining and validating the functionality and performance of big data applications. When we talk about big data, it implies a huge amount of data that traditional storage systems cannot handle. 

Practices For Handling Big Data Testing 

Performing comprehensive testing of Big Data requires great expert knowledge to achieve robust results within the defined budget and timeline. This can be done by adhering to some effective practices for testing big data applications. Let’s explore them quickly: 

  • Exploring the test data 

The testers must work on the right datasets based on the requirements and the test cases, catering to the complexity of the data. When we get to know about the required format, it will help us identify the test management tool that can help deal with requirements for testing an application. In this case, it is important to choose a test data management solution that ensures effective coverage analysis and enhances the data visualization. 

  • Validate your test data 

The current landscape wherein organizations are implementing a child methodology, and it is possible that data can be sourced even from the actual users. Therefore, the test data must be protected against any breach in the development process. The biggest security of the data is also of utmost importance. Sensitive personal data such as name, address, contact information, and financial information should not get leaked. Therefore, it is critical that the test data is validated and the resulting test cases give a real-time picture of the production environment whenever the application goes live. 

  • Choosing automation for the whole process 

Testing big data includes scripting, data masking, cloning, and provisioning. Leveraging automation testing for all of these is effective as it will accelerate the process and make it much more efficient. Automation tools can help ensure that the data is provided in the expected format whenever required. Even the production of test data can be automated. It will eventually help save time in the longer run, reduce efforts, and expose any sort of error with the data on an ongoing basis. Other than this, the queue a team can also help in streamlining and validating the data management efforts. 

  • Focus on the testing environment 

A test environment is of vital importance as it provides accurate feedback about the quality and behavior of the application under test. It is important that the testing environment has enough space for the storage and processing of a large amount of data. It should also have minimum CPU and memory utilization to keep performance high to test big data performance. 

  • Other aspects 

Another strategy to manage big data testing is to ensure that the test objective is clear. Sometimes the communication gap between the testers and stakeholders can also cause a hindrance in the process of big data testing. This is why it is important to stay connected with the objective of big data testing. 

What should you include in Big Data Testing? 

There are some big data testing methods or types that one needs to know. Let’s discuss some of them: 

  • Functional testing 

It is a front-end application testing that provides a boost to data validation. It compares the real results produced by the front-end application against the expected results. 

  • Performance testing 

The automation process in big data allows one to test performance in different scenarios, such as testing the application with different varieties in volumes of data. 

  • Data ingestion testing 

It helps verify that all the data is extracted and loaded correctly within the big data application. 

  • Data storage testing  

In this type of big data automation testing, the QA testers can verify the output data and know whether it is correctly loaded into the warehouse by comparing it with the warehouse data. 

  • Data migration testing 

This type of big data testing validates that data migration from the old system to the new system witnesses minimal downtime with exactly no data loss. 

Read more: Benefits of Big data testing

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