The Internet of Things (IoT) is changing the way we physically and digitally interact in the world. With the global IoT market projected to reach nearly $2 trillion by 2028, developers are looking for ways to take advantage of the increasing demand and gain a cutting edge. For many teams, IoT development combined with using digital twins for verification allows them to make better decisions during development and visually market their devices after launch. How?

Changes to your requirements have consequences. To make informed decisions with your product, leaders must consider all of the potential implications. The best way to do this is by performing a detailed impact analysis whenever a requirements change is requested.

Adoption of service meshes like Istio is increasing. As a result, Speedscale has developed a webassembly plugin. We extended Envoy using Rust, and no changes are required to your Istio configuration. This allows us to leverage the same sidecars that you have deployed throughout your environment to inspect API traffic. Once we are listening through Istio, the typical Speedscale magic can take place. We can use the data to build integration/performance test suites and autogenerate service mocks.

I recently had the opportunity to attend and present at NRF’s Retail Converge Event. After a year of disruption, changing operations, and a new normaI for consumer behavior, several important topics came to the forefront for leading retailers. Here are my top five takeaways from the event: There is a heightened push to modernize supply chains.

With the never-ending potential of technology to disrupt everyday processes, more and more industries are deciding to adapt to one exciting area of innovation today: artificial intelligence (AI). In fact, Global Industry Analysts Inc. predicts that AI will be worth 164.03 billion GBP by 2026, and here, we look at four industries set to be disrupted by AI. Since the healthcare sector collects and greatly depends on personal data from their patients, AI will play a crucial role in data management.

Sometimes, the data you want to analyze lives in AWS S3 buckets by default. If that’s the case for the data you need to work with, good on you: You can easily ingest it into an analytics tool that integrates with S3. But what if you have a data source — such as logs generated by applications running in a Kubernetes cluster — that isn’t stored natively in S3? Can you manage and analyze that data in a cost-efficient, scalable way? The answer is yes, you can.

G2 is one of the leading review and comparison sites for business software, so as an API management platform, we’re especially proud to be recognized as high performers by G2 and its users in Summer 2021. DreamFactory received three of the coveted badges in the Summer review of top software and service providers including.

For all of the buzz surrounding both artificial intelligence and data-driven management, many companies have seen mixed results in their quest to harness the value of enterprise data. To avoid those pitfalls, we mixed best-of-breed and proprietary solutions to develop our enterprise data platform (EDP), focusing much of our attention on a combination of smart changes in technology, culture and process for data lakes.

Like most organizations, Yellowfin has a CRM tool. The data in your CRM should be able to help you understand how you’re selling and how you win. But everyone I speak to is frustrated by the analytics they get from their CRM. We realized very quickly that the reporting in our CRM tool wasn't meeting our needs, so we built our own solution.

Despite Selenium's popularity across the QA industry, it has drawbacks and won’t be the best fit for everyone. Specifically, Selenium IDE: In this post, we'll compare seven alternatives to Selenium, focusing primarily on our platform, Rainforest QA, and explore how the alternatives approach solving these drawbacks.