Systems | Development | Analytics | API | Testing

The modern-day SDLC methodologies such as agile, CI/CD, and DevOps are flexible enough to incorporate change requests in each sprint, which increases the probability of introducing errors in existing functionality. This makes validating existing functionality, detecting newly introduced bugs, and resolving them mandatory in each build release. Whether manual or automated, such software testing is widespread and referred to as regression testing.

Data fabric is an architecture that integrates different data systems and tools. It provides unified access to data stored across various locations to organize, manage, and govern it without moving it to a central database or data warehouse or changing its format. Data fabric relies on metadata to ‘understand’ the data’s structure, lineage, and meaning across various sources. This information enables informed decision-making and optimized data usage.

Defect management is the systematic process of detecting, documenting, and resolving defects within software applications. A defect refers to any flaw or deviation from the expected behavior, which can arise from coding errors, incorrect logic, incomplete implementations, or unforeseen interactions between software components.

Started in 2009 as a research project at UC Berkeley, Apache Spark transformed how data scientists and engineers work with large data sets, empowering countless organizations to accelerate time-to-value for their analytics activities. Apache Spark is now the most popular engine for distributed data processing at scale, with thousands of companies (including 80% of the Fortune 500) using Spark to support their big data analytics initiatives.

Tips for writing natural language prompts to generate SQL and charts using BigQuery data canvas’ NL2SQL and NL2Chart capabilities.

Learn about BigQuery data canvas in this technical walkthrough with a real-world example based on the public github_repos dataset.

Spring Boot is an open source Java framework designed to facilitate the creation of stand-alone, production-grade Spring applications. Whether you’re developing a RESTful API, a microservice, or a batch task, Spring Boot simplifies the process. While platforms like Microsoft Azure and Amazon Web Services (AWS) offer cloud deployment options for Spring Boot applications, Choreo provides specialized features and tools tailored specifically for Spring Boot, streamlining deployment and management.

Modern applications store a lot of data, yet databases continue to be the primary source of data that these applications need to function. This is where database APIs come in, making it easier for applications and services to retrieve and manipulate data. A database API’s biggest advantage is that it eliminates database operations’ dependence on proprietary methods and provides a unified interface, streamlining data operations. Here’s everything you need to know about database APIs.

An API allows communication between different systems, and like any other software, it requires clear instructions so developers can use them effectively. Clear and comprehensive API documentation helps developers understand how to use APIs in their applications. API documentation tools simplify creating detailed reference docs, tutorials, and API documentation. These tools assist in documenting REST, SOAP, or GraphQL APIs effectively. They produce comprehensive API docs that support developers.

In the last article, we gave a general introduction to using Swift for backend development. We discussed its advantages: its robustness, stability and, above all, its simplicity. Now we’re going to drill a little deeper, and provide some best practices that will help you in your day-to-day work. Our work today will focus on Vapor, an open-source web framework that provides a robust foundation for websites, APIs and Cloud projects.