A lack of efficient SaaS testing can result in an unreliable platform that fails to achieve the convenient, quality experience, and agility that users expect. This infographic will help you develop and implement strong SaaS testing strategies.
SaaS platforms have been on the rise for some time now. From professional endeavors to leisure activities, more of our experiences are shifting towards a virtual delivery. And because immediate access from any location makes the shortlist for any software system, consumers often choose SaaS applications over on premise software systems.
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.
Expectations from your development cycle never slow down. Your team must deliver deployments faster and produce stronger product quality in order to remain competitive in the market and maintain relevance with consumers. But how can your team succeed when your resources are consistently constrained?
The good news is that your QA team can do more with less. When your team invests in software testing automation tools, you can expect to boost effectiveness, efficiency and test coverage within your testing process.
Language translation within a product impacts more than the words on the screen. When not tested thoroughly, localization can alter the compatibility with regional operating systems, interrupt a product’s functionality and scramble the layout of the entire user interface.
Both Agile and DevOps teams feel the pressure to quickly release products to market without sacrificing product quality. Fortunately, cloud based test automation tools enable IT teams to tackle these challenges successfully. In fact, many companies have streamlined QA processes, improved product security, accelerated information sharing and reduced cost - all with cloud based load testing tools.
As your business grows, data storage becomes one of the biggest challenges that you will likely face at some point. Among the myriad of big data challenges, the most notable are shortage of server capacity, sharing issues, security and file backup.
