Systems | Development | Analytics | API | Testing

A Comprehensive Guide to Test-Driven Development in Software Engineering

I often wonder about Steve Wozniak’s claim that the first computers were built to help “common people rise.” Correlating the evolution of software with the upheaval of our human society brings a very hopeful sentiment. Now, software engineering methodologies cater to more nuanced requirements of our “rising,” such as allowing space to correct mistakes (agility) and openness to feedback (adaptability).

Using Moesif with Middy and Serverless for AWS Apps

See the GitHub repository for the source code of this article’s example project. Serverless is a popular framework to build serverless apps using AWS Lambda on the Node.js runtime. Serverless automatically orchestrates necessary resources on AWS and can scaffold a basic project for you that you can build up on. You can solely focus on your application’s core logic, development, and your Lambda functions.

AI-driven test strategy and its impact on software quality

While still in its early days, artificial intelligence is becoming a driving force behind innovation in software testing. While automation has improved testing efficiency, AI can take it further by influencing critical decision-making. Rather than reacting to issues as they arise, teams can now identify potential problems earlier in the development cycle. In this article, we’ll explore how artificial intelligence can help teams rethink their testing strategies.

Throughput in Performance testing: A Comprehensive Guide

Measuring throughput and latency is a critical step in load testing software to ensure application performance and stability. In this article, we’ll discuss essential considerations before beginning performance testing and provide a detailed, step-by-step guide on leveraging production traffic replication in Kubernetes. This approach helps you accurately determine your software’s maximum throughput during performance testing.

Maximizing BigQuery ROI: Hands-On Workshop for Cost-Effective Data Management

As data-driven decision-making becomes a cornerstone of business strategy, managing large volumes of data efficiently and effectively is more critical than ever. Google BigQuery, a serverless, highly scalable, and cost-effective multi-cloud data warehouse, offers unique architecture and unparalleled integration with Google Cloud Platform (GCP) services. However, migrating and optimising data pipelines in BigQuery can present challenges.

The Five Pillars of Customer Identity and Access Management #WordsUnplugged

Customer Identity and Access Management (CIAM), a subgenre of IAM, enables organizations to scale and ensure secure, seamless digital experiences for their customers, while collecting and managing customer identity data purposefully. Powerful CIAM solutions provide a variety of key features including customer registration, social logins, account verification, self-service account management, consent and preference management, single sign-on (SSO), multi-factor authentication (MFA), and adaptive authentication as well as other nice-to-have features.

How Solid Data Strategies are Fueling Generative AI Innovation

If innovation is the ultimate goal in business and technology today, then consider generative AI (gen AI) the vehicle taking us there — and a strong data strategy, the fuel. Despite all its promise of productivity gains and new discoveries, gen AI alone can't do it all. The technology needs a "very ready" data foundation to feed on, something the vast majority of businesses today (78%) do not possess, according to a new report by MIT Technology Review Insights, in partnership with Snowflake.