Docker announced three new products — Docker Scout, next-generation Docker Build, and Docker Debug.
Low-code and no-code solutions are becoming increasingly popular, particularly for building software. As companies look for ways to lower expenses, IT and DevOps teams are turning to these kinds of solutions to keep up with the pace of innovation while utilizing fewer resources. In fact, they're so popular for software development that Gartner predicts their use will triple by 2025.
Low-code and no-code solutions can play another integral role for DevOps teams beyond building software: improving testing by enhancing quality engineering, which is the practice of product and service quality assurance and control through the combination of testing, DevOps, and agile delivery, and provides more roles and teams with the opportunity to conceive, design, build, test, and deploy applications the way they are intended. The importance of integrating quality engineering through low-code and no-code solutions is rapidly growing as applications and processes become more complex.
What Are Low-Code and No-Code Testing Solutions?
Similar to how developers use low-code and no-code solutions to build software, DevOps teams use this technology to test their products and catch bugs without having to manually write code. This is particularly helpful since the testing process can be long and tedious.
Teams constantly run tests during the building process to ensure the software doesn't break and, once the application is ready, teams run more performance tests to make sure the application will work smoothly. AI within no-code and low-code testing solutions assumes a plethora of these tasks and helps streamline the entire process.
How Do No-Code and Low-Code Testing Solutions Help?
Low-code and no-code testing solutions help improve quality engineering in three key ways: removing human error, bringing in non-technical support, and helping streamline the update verification process.
First and foremost, quality engineering would not be true to name if it did not produce accurate results and insights. Low-code and no-code automation assumes the mundane and tedious steps that often churn out inaccuracies, like configuring tests and integrating code, helping to reduce inaccuracies and ensure reliability.
Second, low-code and no-code solutions use an intuitive interface to write tests rather than code, allowing non-technical, business experts to support testing activities. This frees up developers to focus on more advanced and high-level deliverables for each project. This not only alleviates common bottlenecks in the software development lifecycle, but also allows teams to focus on more strategic initiatives and more quickly achieve business goals.
Lastly, developers that are building on a platform rather than creating new software or a new application can leverage low-code and no-code testing solutions to spend less time on updates. For example, the platform might release updates which require the team to verify new functions, assess their utility for the organization, and — most importantly — ensure that the update did not break any of their existing customizations. Low-code and no-code solutions reduce the time spent verifying platform updates and investigating why the app no longer functions as expected.
Creating Quality With Low-Code and No-Code Solutions
While large engineering teams have historically been required to keep up with the pace of development, low-code and no-code testing solutions allow thinly stretched teams to do more with less without sacrificing quality.
Low-code and no-code solutions allow DevOps teams to integrate quality by automating and streamlining processes to ensure accuracy, expanding quality responsibility to more non-technical users, and allowing teams to rectify issues before it's too late. As companies look to deliver complex applications that work as intended, low-code and no-code solutions should be considered a must for their useful role in quality engineering.
Industry News
Intel Granulate announced the release of the Auto-Pilot functionality for recommendation implementation in its Kubernetes Optimization solution.
Azul announced Code Inventory, a new feature of Azul Vulnerability Detection that provides developers and DevOps teams a precise catalog of the source code actually used in production by Java applications, making it easy to accurately identify dead and unused code for removal.
Tricentis announced the addition of Virtual Mobile Grid to Tricentis Mobile.
Parasoft announced new advancements in its Continuous Quality Platform for functional solutions, which include Parasoft Virtualize, SOAtest, CTP, and DTP.
The latest releases introduce capabilities including:
- GenAI integration for API testing
- Comprehensive microservices code coverage
- Web accessibility testing
- Powerful learning mode for creating and updating virtual assets
These innovations are set to transform the landscape of software testing for enterprise application development and test teams.
LinearB announced the release of free DORA Metrics dashboards.
PerfectScale, a provider of Kubernetes optimization, has successfully closed $7.1 million in seed funding.
Spectro Cloud announced Palette EdgeAI to simplify how organizations deploy and manage AI workloads at scale across simple to complex edge locations, such as retail, healthcare, industrial automation, oil and gas, automotive/connected cars, and more.
Kong announced Kong Konnect Dedicated Cloud Gateways, the simplest and most cost-effective way to run Kong Gateways in the cloud fully managed as a service and on enterprise dedicated infrastructure.
Sisense unveiled the public preview of Compose SDK for Fusion.
Cloudflare announced Hyperdrive to make every local database global. Now developers can easily build globally distributed applications on Cloudflare Workers, the serverless developer platform used by over one million developers, without being constrained by their existing infrastructure.
Kong announced full support for Kong Mesh in Konnect, making Kong Konnect an API lifecycle management platform with built-in support for Kong Gateway Enterprise, Kong Ingress Controller and Kong Mesh via a SaaS control plane.
Vultr announced the launch of the Vultr GPU Stack and Container Registry to enable global enterprises and digital startups alike to build, test and operationalize artificial intelligence (AI) models at scale — across any region on the globe. \
Salt Security expanded its partnership with CrowdStrike by integrating the Salt Security API Protection Platform with the CrowdStrike Falcon® Platform.
Progress announced a partnership with Software Improvement Group (SIG), an independent technology and advisory firm for software quality, security and improvement, to help ensure the long-term maintainability and modernization of business-critical applications built on the Progress® OpenEdge® platform.