While Go provides a testing package and a go test command, the former only offers basic testing capabilities. The package also has some drawbacks, such as missing assertions and increasing repetition with large-scale tests. As a result, several Go testing frameworks have been created to augment it. Go testing frameworks consist of tools and resources for creating and designing tests. Some of these frameworks incorporate the testing package and go test command, while others take a different approach.

Bringing you closer to DevSecOps, the brand new 'Scan with AppSweep' Step on Bitrise makes your apps more secure with continuous security assurance.

WebTransport is a new specification offering an alternative to WebSockets. For applications that need low-latency, event-driven communication between endpoints, WebSockets has been the go-to choice, but WebTransport may change that. WebSockets is a technology that enables bidirectional, full-duplex communication between client and server over a persistent, single-socket connection. This allows for low-latency, realtime updates, and the creation of richer communication and gaming applications.

Choosing the right method to store your data can be a critical decision early in the development process. When deciding on which type of database to choose for your project it really comes down to the data structure you wish to use rather than the specific product or provider. In this blog post, we are going to look at relational and non-relational databases and explore the differences and use cases for both.

Operationalizing AI pipelines is notoriously complex. For deep learning applications, the challenge is even greater, due to the complexities of the types of data involved. Without a holistic view of the pipeline, operationalization can take months, and will require many data science and engineering resources. In this blog post, I'll show you how to move deep learning pipelines from the research environment to production, with minimal effort and without a single line of code.

Over the past decade, the successful deployment of large scale data platforms at our customers has acted as a big data flywheel driving demand to bring in even more data, apply more sophisticated analytics, and on-board many new data practitioners from business analysts to data scientists. This unprecedented level of big data workloads hasn’t come without its fair share of challenges.

Organizations trust Snowflake with their sensitive data, such as their customers’ personal information. Ensuring that this information is governed properly is critical. First, organizations must know what data they have, where it is, and who has access to it. Data classification helps organizations solve this challenge.

Today’s applications run on data. Customers value applications not only for the functionality they provide, but also for the data itself. It may sound obvious, but without data, apps would provide little to no value for customers. And the data contained in these applications can often provide value beyond what the app itself delivers. This begs the question: Could your customers be getting more value out of your application data?

The goal of user interface (UI) testing is to verify that: However, most software testing tools either test the appearance of the application or the functionality—few tools do both well. To test functionality, most automated software testing tools primarily interact with the underlying code of an application, while assuming that the visual layer (what the user sees) is rendering properly.

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