Systems | Development | Analytics | API | Testing

Your Kafka Doesn't Have to Live Behind a Wall There's a problem that almost every platform team running Kafka at scale eventually hits, and it usually starts with a reasonable ask: "Can you give our partners access to this event stream?" What follows is rarely simple. You start scoping VPC peering. Then someone asks about firewall rules. Then you realize each new external consumer is going to need its own network arrangement.

Combining MCP Servers and LLMs with MS SQL Server simplifies database management with natural language queries, automation, and robust security. Here’s what you need to know.

A global leader in entertainment, gaming, and hospitality partnered with WSO2 to take the organization’s first step to becoming an agentic enterprise by building an intelligent solution that would transform how support teams operate. The solution, a virtual support engineer, automated a manual issue resolution process and reduced resolution times from 2 hours to 1 minute, helping to provide a better support experience for both customers and internal operations teams alike.

Heroku's logging system is your primary window into application behavior, but its ephemeral nature and streaming architecture can feel mysterious at first. This guide walks through everything developers need to know about Heroku logs, from understanding what they are and how to access them, to working around their limitations and forwarding them to external services like Honeybadger Insights for complete observability. Read on to master Heroku logging.

Better specs and clearer task decomposition are a significant step forward. But specs and plans describe intentions. What AI agents also need is visibility into what systems actually do at runtime.

In 2026, PropTech is no longer experimental. For most owners, operators, and investors, technology isn’t something you pilot — it’s core infrastructure. The shift is visible in both numbers and behavior. The global PropTech market is expected to grow from ~$34.4B in 2025 to ~$40.4B in 2026, with a projected ~17% CAGR through 2035. But growth alone doesn’t explain what’s happening.

When building AI experiences, choosing between WebSockets and HTTP isn't always straightforward. Which protocol is better for streaming LLM responses? How do you maintain continuity when users switch devices mid-conversation? Should you use both? The answer depends on the type of AI experience you're building. Modern AI applications often require both protocols, each serving different purposes. The key question is: how do you decide which communication pattern fits each scenario in your AI stack?