Systems | Development | Analytics | API | Testing

For a few years now, Node.js has been widely recognized among developers. So, what is this latest buzz surrounding Node.js that we keep hearing about? Why is it so well-liked? You all must be curious to know the answers to these questions, right? Well, websites have undoubtedly grown significantly during the past 20 years, and Node.js has also experienced rapid expansion.

Although the severity of the risks can vary, it’s nevertheless crucial for your development process to reduce risk as much as possible.

As fraud continues to grow in prevalence, SecOps teams are increasingly investing in fraud prevention capabilities to protect themselves and their customers. One approach that’s proved reliable is the use of log analytics and telemetry data for fraud prevention. By collecting and analyzing data from various sources, including server logs, network traffic, and user behavior, enterprise SecOps teams can identify patterns and anomalies in real time that may indicate fraudulent activity.

Functional testing is a process that expands across the software development life cycle, from code-level testing to regression testing. Different levels of testing are well represented in the testing pyramid. To get a firm grasp on how these types of testing work and their relationship, we'll look further into each layer.

Hardware and software systems often involve numerous parameters that influence a system’s output(s). Those parameters can represent input, environment, or usage patterns and can have a finite or infinite number of options/values. For instance, on a booking flights website, the Flying From, Flying to, Class, (number of) Adults, and (number of) Children input parameters can easily provide hundreds of different combinations for creating tests.

Say goodbye to constant “One-Offs” and hello to “Set It and Forget It”

Our customers share why they chose Fivetran to replicate their database data and how their analytics have improved as a result.

Deploying trained models takes models from the lab to live environments and ensures they meet business requirements and drive value. Model deployment can bring great value to organizations, but it is not a simple process, as it involves many phases, stakeholders and different technologies. In this article, we provide recommendations for data professionals who want to improve and streamline their model deployment process.

As we hurtle into a more connected and data-centric future, monitoring the health of our data pipelines and systems is becoming increasingly harder. These days we are managing more data and systems than ever before, and we are monitoring them at a higher scale.

gRPC is an open source remote procedure call (RPC) framework that enables client and server applications to communicate with each other remotely and transparently. In this blog post, we are going to discuss gRPC. First, we’ll talk about RPCs and why they are important. Then we’ll explain how gRPC works, taking a closer look at protocol buffers and the architecture of gRPC.