Cloud testing - The next level of Digital transformation

Organizations these days are realizing the importance of today’s dynamic marketplace and hence adopting digital transformation to stay ahead of the game. Born-on-the-web businesses are able to disrupt very quickly and adapt according to the dynamic industry changes. The key is for every business to be able to get there. And this is where cloud testing applications comes into the picture. Being a kind of software testing which leverages cloud computing, it creates real world traffic and is much more reliable and efficient when it comes to data access and hence can play a key role in driving your organization’s digital transformation initiatives. Reading through this blog will help you get a fair idea on how cloud testing can help you accelerate your company’s digital transformation efforts with quality testing and QA strategies. 

Key reasons would include the following:

Access to apps and devices anywhere anytime 

Since there is an uninterrupted internet connection, you can get access to your resources from anywhere at any time. Best part is that you can make updates and changes in real-time. So you don’t have to make huge investment in hardware giving your team the flexibility to focus more on development and testing activities. 

One of the best values which cloud brings to the table is limitless accessibility to resources. This helps enterprises to develop  and test scalable applications using the right software technologies

Cost effective solutions 

Organizations are looking for successful cost optimization methods for increased business performance and ROI. Similarly, QA is looking for cost-effective mode of operations that ensure efficient testing practises. One critical focus area here would be testing tool licensing and infrastructure costs. Cloud testing helps in saving these costs by enabling teams to access the testing tools from anywhere and make necessary updates and changes without any large investments in tools. This in turn helps in resource optimization by reducing computing power as well.

Promotes team collaboration

The cloud based testing helps organizations to implement DevOps in a better manner and hence increases the collaboration between testers and developers. Leveraging tools such as Heroku and Docker, testers can use testing environments with various configurations and automate testing processes efficiently. 

Continuous Integration and Development Support

Agile and DevOps methodology are being adopted by several organizations these days to make sure continuous development is followed by continuous testing and integration. Cloud testing supports Agile methodology and gives a platform which helps in hosting test management solutions in the cloud and hence helps team to have better collaboration and stay on the same page. 

Cloud testing thus helps in continuous integration by making sure recently created fragments are deployed in a faster way and teams stay on schedule to deliver on time.

 

 

How AI is transforming the future of Software testing?

Artificial Intelligence is not just a technical concept anymore. It’s the hottest topic of the town, transforming enterprises by providing smart and actionable insights. At the same time software testing is now undergoing a major shift from manual to automation as more and more organizations are recognizing the need to adopt DevOps and digital transformation. Needless to say, AI has a huge role to play in this change.

Roadblocks

These days applications interact with other kinds of applications with the help of API, utilizing traditional systems. This eventually results in complexities growing in a non-linear manner. So how does this affect testers? The major challenge for them here is to make sure the new code does not break the existing codebase. Every time a new code is written by the developer, new testing methods should be applied to ensure code quality. This in turn increases the workload of tester due to the rising complexity of code.

AI is considered to mitigate all these roadblocks related to QA and testing. Let’s discuss some of the ways AI bring about major changes in testing.

Simple and Error free

The latest AI offers so many features which has the capability to save the time of testers by sorting through log files. This improves accuracy and the developers will be free of writing long scripts and checking huge amounts of data. The AI driven data results helps testers to locate the exact bug in the system without tedious work of going through thousands of lines of code and even predict future errors and complications in the code. Major benefit here is that it accelerates the timeline and efficiency of the QA team.

Improved Automation

Like we discussed above, the major time share of QA team is consumed by making sure the new code does not break the existing functional code. With more features added to the system, more testing works need to be undertaken, which further burdens the testers' overall productivity

AI can make a big difference here. AI bots can evolve predetermining the changes in the code. Being highly efficient and adaptable, these bots can identify new modifications in the code and understand if it’s really a change in the code or an error to be removed.

Optimized test suite

One of the major challenges faced by software testers is backlogs, which results due to over-engineering and speedy release due to hectic schedules. Bots can help here by identifying repetitive test cases and removing the duplicates. This will help in clearing the backlogs and achieve end to end traceability.

Prescriptive and Predictive Analytics

AI is taking predictive analytics to the next level. AI bots helps organizations to detect vulnerabilities earlier and thus helps them to prioritize their QA efforts effectively without compromising on quality. It can help solve the most complicated problems by predicting certain scenarios and behavioural patterns and take the best decision possible. From analysing test results to identifying bugs and predicting the quality, AI can be used in every area of QA process. You can utilize it to predict flaws earlier, optimize test processes and hence accelerate overall timeline.

 

 

 

Digital transformation universe is fast evolving and QA is rapidly gaining momentum in both business and IT operations. QA and testing is the key factor to make sure these four goals are achieved in every organization today.

Every business demands quick service and response with ease of use, accessibility, usability and performance. Ranging from customer journeys, user experience, cross browser functionality, performance, responsive design and security, they are looking for validation in every functional aspect. Moreover, businesses need to be agile with new competition arising in the market every day while navigating through quality issues across different platforms. It’s quite natural for errors to happen in this scenario. 

Achieving a balance between the risk of bugs and right level of quality control without delaying your ability to innovate determines your overall business success.This makes testing efforts too high with rise of infrastructure cost and lack of manpower.

Although Adoption of Agile and DevOps is increasing how to achieve quality in these fast development cycles without impacting customer value is a big question . The answer lies in digital testing. Digital testing is a type of software testing where a particular code is analyzed using various digital tools to check for software bugs and fix it appropriatley. 

What makes it a better option?

With new technologies emerging as part of digital transformation, most of the times the quality of what is being delivered is compromised. This in turn makes the existing QA and testing methods incapable of finding out errors cropping up in an entirely unfamiliar software. 

Digital testing helps exclusively in figuring out such issues by testing end to end workflows. It acts as a catalyst for efficiency, quality and more importantly innovation. Moreover Digital testing helps you get closer to your customers and transform your entire business processes. 

Benefits of Digital Testing

Improved ROI

Digital testing may not be directly related to ROI,but it can ensure better user experience and optimized task completion rate.This leads to generation of more qualified leads and improved ROI

Identifying reasons for low conversion rate 

Website is undoubtedly the mirror of your business. Any visitor to your website could be your future client. If the customer feels he doesn’t get what he needs regardless of how amazing your website is designed, they will abandon it right then and there. Digital testing allows businesses to find out the exact reason why customers are not satisfied and hence help you mitigate the issue without any further delay. 

Know Your Customer

Digital testing is focused on understanding how the customer use a website or an application. This would help the product management team to redesign particular features to make them more optimal according to the customer requirements. Also the programmers can then schedule their activities accordingly as they now know what risks are lurking in these features.And then the marketing team can now predict what competitors are up to and how would they build their product/websites. 

 

Here are key trends to watch out for in Automation testing

You can’t deny the fact that time is moving fast as we reach the end of the year, and so is technology evolving in a blink of an eye. Software testing is still getting used to the dramatic changes occurring in the development industry. Software technologies are so rapidly advancing that the testers have no choice rather than to upskill their current knowledge and hands-on experience in various newly introduced tools. As it is vital for software testing organizations to understand what’s changing, we have come up with a set of crucial trends to look for and to get a clearer picture on what the next year will look like for software testers.

Codeless Test Automation is the future

This is the time of agile development cycle which involves iterated releases making testing a complicated process. Hence automated testing is a necessity for agile development process. But things get critical when there is a large project with a fast cycle release. Traditional automation involves writing separate execution software scripts for each test case, and then executing them through a separate software setup. But when there is a large project this involves a lot of time by creating test environment and writing test scripts. This is where codeless test automation will increase the scalability of test automation.

Codeless test automation tool helps the software testers and business users to automate test cases without writing a single line of code. It is user friendly and helps to deliver faster results and by decreasing the coding process.

Era of Non-selenium automation testing tools has already begun

Selenium is a great tool as it supports different programming languages like C sharp, Java, Python, Ruby and so on and a lot of language binding is also supported. It also supports different eco-systems like Windows, Mac etc. supports various browsers as well. But the fact is, the monopoly of using Selenium is trying to reduce right now and several other options are available in the market which doesn’t use selenium at all. You can see how users are now moving away from browser-based automation tools to more open source tools. A couple of examples to cited would be Cypress.io, Nightwatch.js, Puppeteer and TestCafe.

Agile & DevOps

As there is an increasing demand to adapt to changing requirements of industry organizations are now going in the path of agile and DevOps to meet the demand for speed.

The adoption of Agile and DevOps has gained much popularity in the past couple of years and is spreading rapidly among test organizations as it helps the team to deliver software without compromising on quality as well as speed. The best part about this is that it can drive faster deployments even for complicated systems with cost effective solutions.

AI for testing

AI and ML approaches are not new in software testing but it’s still in its early adoption stages. Organizations are still getting used to this concept and can be expected to optimize their testing best practices in AI/ML

AI/ML algorithms will help testers to develop better test scripts, test cases, reports etc. And with the help of predictive analysis, they would be able to decide on when and what to test according to flaws anticipated earlier.