Systems | Development | Analytics | API | Testing

We want to express our appreciation to the many contributors to this release including NodeSource team members @RafaelGSS, @juanarbol. Thank you for all your efforts to keep moving Node.js forward! Node.js 24 has officially landed! This release brings some exciting improvements to JavaScript developers, making Node.js faster, more capable, and more aligned with the latest JavaScript standards.

Today, we’re excited to announce the general availability of Serverless Postgres — a fully managed, fault-tolerant, and effortlessly scalable Postgres database service purpose-built for large scale and AI applications. Since the public preview, over 50,000 databases have been created for use cases ranging from multi-tenant SaaS to AI agent memory, RAG pipelines, and ephemeral dev environments.

Performance bottlenecks can break user experience – and fixing them often requires deep dives into tech stacks, complex tools, and long hours of scripting. That’s fine if you’re a seasoned engineer, but what if you’re a product owner, agency leader, student, or DevOps lead who just wants to know: How well does my app actually scale?

Explore how the Sauce Labs Trust Center serves as a cornerstone for building secure testing relationships.

Not every message in a realtime app needs to be available in message history, like in the rewind backlog or in persistent storage. Ably is introducing ephemeral messages to let you deliver transient updates - like reactions, typing indicators, or cursor positions - which are only delivered to clients that are connected at the moment the message is published.

As organizations continue to adopt AI-driven applications, managing usage and costs becomes more critical. Large language models (LLMs), such as those provided by OpenAI, Google, Anthropic, and Mistral, can incur significant expenses when overused. This blog will explore how you can streamline your AI workloads by leveraging Kong’s token rate-limiting and tiered access features.

Key Takeaways Integrating Amazon DynamoDB with Amazon Redshift is being done using methods like Zero-ETL, DynamoDB Streams with Lambda, or AWS Data Pipeline. Zero-ETL is simplifying real-time transfers, while Lambda and Data Pipeline are offering more flexibility for transformations.

When exploring common types of software architecture, it’s important to understand the foundational patterns that drive modern application development. Software architecture patterns like MVC, client-server, microservices, and event-driven models help teams build scalable, maintainable, and robust applications. Software architects have built a broad range of options with varying features.

Software quality assurance has evolved significantly in recent years, with behavior-driven development (BDD) emerging as a powerful methodology for aligning technical teams with business objectives. At the center of this evolution sits Gherkin, a simple yet powerful specification language that bridges the communication gap between technical and non-technical stakeholders and simplifies the creation and maintenance of automated tests.

That's a lot of tests.