webAI and MacStadium(link is external) announced a strategic partnership that will revolutionize the deployment of large-scale artificial intelligence models using Apple's cutting-edge silicon technology.
In today's digitally driven work environment, leveraging technology to improve efficiencies is an essential component of any modern business. This is especially true for those in the business of software.
As a business's software development life cycle (SDLC) continues to speed up, and more code is developed and deployed at a faster rate, testing that code for quality to ensure optimal user experience is critical. The SDLC is also only growing more complex, so finding ways to simplify and automate wherever possible are critical too.
That's why a modern SDLC should start with software test automation.
Inclusive Automation
Software engineers are well-versed in inclusive or universal design, creating a product that is usable by as many people as possible. This should be applied to software test automation too.
Traditionally, a software developer uses code to script automation. Problems can arise with this approach when testers don't have the technical understanding to maintain these tests or grow the scale of these tests as the software pipeline expands. Starting with inclusive codeless automation solves this challenge by removing the complicated coding part of the process.
Facilitating Automation
Validating software on both web and mobile applications can create unique challenges for software test automation. To avoid issues, it's important to create applications with inclusive automation in mind, including details baked into your code.
■ Every element has a unique identifier. Software test automation should act on these IDs, not something else, such as position on a page in mobile vs. web. Unique identifiers enable automation to act and do its job.
■ Content descriptions are used to explain an element's purpose. This helps distinguish between UI elements. This also needs to be part of standard automation testing.
Identifiers and content descriptions are not optional for developers looking to implement functional and advanced testing automation that doesn't break.
Limits to Software Test Automation
Codeless automation can handle complex situations, but it has its limits. Some tests are still better to be done manually. For example, any tests that involve data from two separate sources (like from APIs, which are very common for apps today), make it difficult to automatically validate. This is because individual apps behave differently. Synchronizing two systems into one for testing is challenging for any type of automation, not just codeless testing.
The Potential of Software Test Automation
Software test automation can empower organizations and their software development. But it isn't always easily embraced or added. One big reason behind this is that developers don't want to stop developing new features to pay down existing technical debt. So areas like refactoring or desiloing are put off.
Performance will eventually suffer if technical debt isn't paid down. In the long run, pausing development progress to implement automation will be worthwhile. Advanced automation planning and strategy should go directly into your SDLC and be a consistent effort to identify app elements and improve automation around them.
Industry News
Development work on the Linux kernel — the core software that underpins the open source Linux operating system — has a new infrastructure partner in Akamai. The company's cloud computing service and content delivery network (CDN) will support kernel.org, the main distribution system for Linux kernel source code and the primary coordination vehicle for its global developer network.
Komodor announced a new approach to full-cycle drift management for Kubernetes, with new capabilities to automate the detection, investigation, and remediation of configuration drift—the gradual divergence of Kubernetes clusters from their intended state—helping organizations enforce consistency across large-scale, multi-cluster environments.
Red Hat announced the latest updates to Red Hat AI, its portfolio of products and services designed to help accelerate the development and deployment of AI solutions across the hybrid cloud.
CloudCasa by Catalogic announced the availability of the latest version of its CloudCasa software.
BrowserStack announced the launch of Private Devices, expanding its enterprise portfolio to address the specialized testing needs of organizations with stringent security requirements.
Chainguard announced Chainguard Libraries, a catalog of guarded language libraries for Java built securely from source on SLSA L2 infrastructure.
Cloudelligent attained Amazon Web Services (AWS) DevOps Competency status.
Platform9 formally launched the Platform9 Partner Program.
Cosmonic announced the launch of Cosmonic Control, a control plane for managing distributed applications across any cloud, any Kubernetes, any edge, or on premise and self-hosted deployment.
Oracle announced the general availability of Oracle Exadata Database Service on Exascale Infrastructure on Oracle Database@Azure(link sends e-mail).
Perforce Software announced its acquisition of Snowtrack.
Mirantis and Gcore announced an agreement to facilitate the deployment of artificial intelligence (AI) workloads.
Amplitude announced the rollout of Session Replay Everywhere.
Oracle announced the availability of Java 24, the latest version of the programming language and development platform. Java 24 (Oracle JDK 24) delivers thousands of improvements to help developers maximize productivity and drive innovation. In addition, enhancements to the platform's performance, stability, and security help organizations accelerate their business growth ...