Imagine using shared resources that are allocated dynamically, create flexible testing environments, and that simulate user scenarios and real-world traffic - that’s just some of the benefits of cloud testing.
It’s standard practice for companies to monitor APIs during production to ensure that the live API endpoints are up, functioning quickly and returning expected information to the user. That way, testing teams know whenever something breaks down and can fix any issue before users notice any discrepancy.
But what if consumers find issues related to the API issue before you do? And what if the problem is more serious than slowness?
Nothing is more frustrating than funding a test automation project that results in endless time and resources to maintain , or worse, funding one that requires re-building after six months. Often a test automation strategy fails because the objectives were not identified early on or the scripting strategy excluded considerations for long-term maintenance.
The primary goal of API testing is going beyond QA manual testing material by executing code-level testing of both the application and the API. A full, organized suite of testing can verify the individual parts of each method, class and package within the API. Strong API testing practices can ensure the security of the application’s code and confirm the expected interaction between the API layer and the application.
There’s a lot that needs to happen during API testing, so where should your team begin?
Before the benefits of automation tools were as commonly recognized as they are today, CTOs, product managers and engineering leads were slowed down by repetitive manual tasks, bottlenecks and miscommunication across teams. True efficiency and innovation was a distant goal, something they could only discuss in abstract terms without understanding the value of certain services in software testing.
Today, product companies strive to lead in four key areas: innovation, efficiency, accuracy and speed. Automation advantages in software testing are designed to place more power in the hands of developers, QA engineers and IT leadership.
QA managers are tasked with continuously finding ways to improve quality assurance and overall software integrity, but are also asked to find ways to increase productivity of team members. But, between rounds of testing and writing up issue reports, there never seems to be enough time to carry out these changes.
Increasing productivity of your QA team doesn’t have to be difficult. Targeting easy wins allows for more time to implement additional tactics that improve team productivity. And since there are a lot of tasks that QA teams tackle, increasing QA productivity can help successfully drive a company’s revenue growth.
Here are 6 ways to increase productivity within your QA testing team:
Healthcare applications must process a huge number of transactions and a massive amount of patient data each day. To ensure that all this data is handled appropriately over time, it is integral that test cases for the healthcare application apply data sets of varying complexity.
To save time and resources, consider implementing test automation where possible. But what is test automation? And what benefits of automation in healthcare can your team expect?
Most healthcare enterprise applications are loaded with critical data related to patients and the various organizations they serve. This can include health records, payment information, account details, and identity details. Due to the incredible sensitivity of this data, thorough software security testing is a necessity for healthcare applications so that critical information doesn’t fall into the wrong hands.
By “wrong hands,” we mean criminals in the identity theft business, hackers skilled in malware and phishing schemes, and cyber-attackers aiming to hold critical files or your entire system hostage by ransomware.