The numbers confirm this too: as per a survey of 500+ IT leaders and executives, the number-one driver of cloud migration is security and data protection. Fifty-eight percent of the respondents ranked security as one of their main priorities.

Then we have data modernization, which involves transferring the data from legacy to modern databases. According to the survey, 55 percent of respondents concurred that data modernization is a key factor in their companies shifting to the cloud. Cost savings and performance of IT operations rank third in the survey results. Cost is less of a factor compared to other key benefits of the cloud, which is a key enabler for organizations’ digital transformation efforts.

QA or Quality assurance and testing services are an indispensable part of any company’s cloud migration journey. For they help organizations avoid issues around cloud scalability, server breakdown, databases, website crashes and more which could potentially tarnish a brand’s reputation while costing time and resources.

In terms of application testing for cloud migration, the focus areas mainly include the following:

• Functional validation
• Integration testing
• Scalability and performance testing
• Security testing

Functional validation

This type of testing mainly validates the production readiness for applications moved to the cloud. The validation process typically involves the verification of key facets of migrated applications and whether they are performing according to the service level agreements (SLAs).

For robust cloud migration, organizations must verify SaaS (short for software as a service) and cloud services function and validate the end-to-end application’s function.

When it comes to cloud testing an application, the following test cases must be executed to check:

• Whether a valid input generates the expected results
• Whether object references and page layout work as expected
• Cross-platform compatibility
• Service integration with applications
• If the automated test suite is compatible with cloud applications

Integration testing

It must be noted that cloud migration is not only about moving the in-house workload to the cloud, but it also includes managing different variables such as authorization, authentication, integration, security, compatibility, testing and security.

Of the variables, integration with third-party tools is significant. Organizations must ensure their applications are well-integrated with third-party applications and communicate seamlessly without glitches.

It is also mandatory to identify dependencies among applications and the service level agreement with each app – because dependencies between systems and applications can make integration testing potentially challenging.

QA and testing teams must consider the following when performing integration testing:

• Cloud testing with third-party tools when varying service level agreements are at play
• Uncover coordination glitches in the cloud
• Application configuration within the cloud environment
• Resources for integration testing and validation
• Systems and interfaces that are part of integration testing
• Integration of multiple applications can complicate migration

Performance testing

This is a significant element of an organization’s cloud migration success while also being a critical part of application development.

When migrating an application to a cloud service, factors such as scalability and response time must be validated. Through automated performance testing process, a software or an application is tested for issues that require attention.

When it comes to performing performance testing, QA engineers and testers must consider the following:

• Identify the architecture of an incompatible application
• Identify the monitoring needs and setup tools
• Keep track to validate response time with regard to service level agreements
• Carry out load testing in parallel
• Record performance under different loads that meet service level agreements
• Check service level agreements, business transactions and end-to-end flow of applications

Security testing

Security is one of the main concerns of cloud migration, with service providers spending millions of dollars to provide optimal protection for their clients’ workloads.

Given the sophistication and sheer volume of cyberattacks, advanced cybersecurity measures must be put in place to ensure confidential organizational data is secure.

Business process security testing, user privacy security testing, application transaction security testing, data privacy and data security testing are the main types of testing a cloud application. 

Security testing helps eliminate the security risks of software systems and applications. The primary focus for organizations is user validation to go with validating data security in transit, during use and at rest.

The following factors must be considered at the time of security testing:

• How is data stored when idle?
• What are the different compliance requirements?
• Who has access to the data?
• Where, when and why users access data?
• What sensitive data is used, stored or transferred?
• Identify legacy applications running on obsolete systems
• Ensure only authorized users access the cloud network
• Ensure appropriate measures are put in place against Distributed Denial of Service (DDoS) attacks
• Validate application, frontend and backend processes

Plan for disaster recovery and business continuity

Despite taking all necessary precautions before cloud migration, organizations must brace themselves for possible worst-case scenarios.

The measures may include simple data recovery, taking stock of the various attacks, disaster recovery practice and more.

Organizations must validate their disaster recovery strategies in the event of cloud outages. The following practises will help:

• Periodically test, measure and update business continuity practises
• Update business continuity plan based on test results
• Run simulations and assess team’s readiness
• Validate application instances to automatically restore in case of hardware failures

Summary

As per a recent study, 77 percent organizations believe that cloud technology gives them a competitive advantage—which partly explains why an increasing number of them are transitioning to the cloud. Cloud is powering organizations’ digital transformation efforts and enabling them to build innovative, digitally-collaborative and customer-friendly products and solutions at scale. It is also helping organizations respond to opportunities with greater agility.

Not with standing all the key benefits of cloud migration, organizations must follow the above QA testing checklist to the letter to ensure they avoid security, performance, functionality issues and potentially extra costs, time and resources during IT migration.

The post The 5-step QA testing checklist for successful cloud migration appeared first on Indium.

But now the concerned matter is whether the theory will be able to bring about the necessary and the expected changes in the software testing field or not.

Software testers and developers from all over the world are trying various methods to incorporate the idea to create a new version of technologically advanced world.

Will this new introduction become a salvation or the cause of destruction? Even though, there is still an underlying uncertainty, the use of the AI theories has become abundant to an extent.

According to The Times Higher Education, China is leading the pack with over 41000 research papers on AI and various countries are following this theory to perform various functions.

Let’s take a glance at the attributes of the Artificial Intelligence and its related aspects of software testing!

What is artificial intelligence?

We all know that the robots and the technologically developed machines are quickly replacing the human labours, be it bots or any automated machine.

Now, when the mechanical strength is being replaced by artificial power, why not the natural intelligence of human beings is replaced by something similar?

This proposition led to the development of a new concept of artificially induced intelligence, similar to the human intelligence in any sense yet advanced and quicker.

This is known as Artificial Intelligence. It is actually a probabilistic approach towards any situation.

Apart from this, AI technologies behave like humans and produce results the same way. Some of the best technologies developed to date that uses AI are speech recognition, virtual agents, machine learning platforms, robotic process automation and so on.

The success of the Artificial Intelligence in these fields has driven the software minds to use the theory of the same in the aspect of developing software and testing the different parameters of the same.

What is the requirement of ai in software testing?

Software testers benefit more on automation than the manual checking process.

The term ‘software testing’ revolves around a number of algorithms and technical processes which examines the quality of the software, the output, its market efficiency and other attributes.

Now, software testing does not involve a step or two for the software testing purposes.

Rather, the entire software developed is subjected to a series of repeated tests where at each level, the parameters are examined by various methods.

This requires intelligence, extensive manpower and time. Also, the revenue spent by various macro software-giants accounts to around billions.

The use of Artificial Intelligence will certainly cut out all the excess things that are needed for the testing process.

The AI algorithm and the various processes are based on introducing automation and better ‘intelligent’ analysis of any faults or errors within the software.

The entire work is done at low maintenance since AI means artificially induced intelligence, enough brainpower to run the processes without extensive care.

Benefits of ai in software testing

The benefits of the application of Artificial Intelligence are extensive. The combination of AI and machine learning (ML) help to automate and improve testing by applying reasoning and problem-solving, while AI in software testing helps reduce the time spent in manual testing. This, in turn, helps testers focus on more complex tasks and potentially building innovative features.

In addition, some can modify the existing testing methods while others will definitely introduce mind-blowing changes in the field of software testing.

1. Improved Quality

With the application of the artificially induced intelligence, the quality of the software will develop widely.

Since all the testing methods will be carried out automatically and with secured assuredness, the quality will be improvised greatly.

Moreover, the longevity of the applications will be increased greatly along with the increased market efficiency

2. Effective and Trustworthy 

AI algorithms have introduced effectiveness in the software testing.

The artificial intelligence theories have also increased the reliability of the testing methods by reducing the manpower and also the intensive costs.

The process is trustworthy since the errors will be checked by checking codes that will not leave the errors unattended without resolving them.

3. Earliest Feedback

As the AI testing process is automated, the software developers will get a quick feedback report on the working and the efficiency of the applications.

Also, the bugs and the disputes will be resolved quickly and hence, the products can be launched quickly in the market.

4. Improved Traceability 

AI algorithms have introduced effectiveness in the software testing. The artificial intelligence theories have also increased the reliability of the testing methods by reducing the manpower and also the intensive costs.

The process is trustworthy since the errors will be checked by checking codes that will not leave the errors unattended without resolving them.

5. Integrated Platform

The entire process is conducted on integrated and embedded platform. This will make it easier for the software developers to launch the website easily on the client’s website.

Hence, the execution process will become more flaccid.

The application of the Artificial Intelligence continues to be adopted widely in the software testing space and in the future, the technology will help improve current tools and frameworks to target specific issues.

The post The Role of AI in Software Testing appeared first on Indium.