Systems | Development | Analytics | API | Testing

DevSecOps is about ensuring security throughout the software cycle. While it offers many benefits, it also has its own challenges that you must understand. Performing AST (Application Security Testing) is a common and effective way to find vulnerabilities and weaknesses in an application and make it resistant to security threats. Traditionally, AST has been performed at the end of the software/application development process, more like an afterthought.

It’s no secret that more and more applications are moving to the cloud. According to the 2022 Flexera State of the Cloud report, 50% of all workloads are in public clouds. In addition, moving from on-premises software to SaaS was a top priority for 42% of survey respondents. According to the BetterCloud’s 2023 State of SaaSOps report, organizations are using 130 SaaS apps on average. Many of these apps are the backbone of your organization.

Testing in production carries a lot of risk, like possibly causing downtime for users. However, the advantages of using real user traffic are many, which has led to the popularity of traffic mirroring. Mirroring can be implemented as part of pre-deployment testing, as well as other parts of the developer experience like the development itself. But, how do you get started with it?

If you’ve got an agile team interested in shipping fast without breaking things, this post is for you. In this piece, I’m going to explain how we at Rainforest QA approach automated testing in a continuous integration / continuous delivery (CI/CD) pipeline, with a focus on end-to-end (e2e) functional testing. The aim of our testing and other DevOps methodologies is to maintain a healthy balance between speed and product quality.

The last thing a business wants is to be known as an unreliable and poorly performing service, especially if there are similar solutions a few clicks away. So being aware of the performance of a WebRTC application or any other software solution is a must to avoid issues in the future. A solution can be developed by experienced people and tested before it is released, but even so it doesn’t mean performance degradations will never appear.

With the growth in the number of electric and autonomous vehicles, where the vast majority of components are built on software, the amount of code in a vehicle is only going to increase. Connectivity, both within the vehicle and outside, is also increasing, meaning that the security of these systems has become more critical than ever before. For any system where there is communication between components or with the outside world, there is an increase in possible software cybersecurity threats.

Once a customer is ready to purchase, the final frontier lies ahead: the payment process. Because online transactions already come fraught with a learning curve, companies must use extensive payment gateway testing to deliver frictionless payment experiences. Even minor glitches can cause cart abandonment and reduce sales volume. Where other aspects of software may enjoy the leeway to go live while minor problems are ironed out, payment gateways cannot afford anything less than perfect reliability.

Artificial Intelligence (AI) is coming, whether we like it or not. It is likely to transform every aspect of what it means to be human and represents an existential opportunity – or potential threat – to everyone living and yet to be born. Hyperbole aside, ChatGPT software intelligence has been a hot news topic of late. While it has some limitations, to many of us it’s the first real glimpse of AI’s capabilities.

Software development has changed a lot in the last 10 years. Practically every company is a software company today. And it’s predicted that the next 10 years will have 10-times the change. But let’s take it one year at a time and look into the future of software development 2023.