Systems | Development | Analytics | API | Testing

Meet Qlik Answers

Discover how Qlik Answers transforms the way teams work with data. As part of Qlik’s newly released agentic experience in Qlik Cloud, Qlik Answers brings together natural language interaction, the power of the Qlik Analytics Engine, and governed, trusted data, all supported with transparent reasoning and citations.

Appends for AI apps: Stream into a single message with Ably AI Transport

Streaming tokens is easy. Resuming cleanly is not. A user refreshes mid-response, another client joins late, a mobile connection drops for 10 seconds, and suddenly your “one answer” is 600 tiny messages that your UI has to stitch back together. Message history turns into fragments. You start building a side store just to reconstruct “the response so far”. This is not a model problem. It’s a delivery problem That’s why we developed message appends for Ably AI Transport.

ClearML Enterprise v3.28: Usage Metering, Policy Enhancements, and Smarter Admin Controls

Author: Adam Wolf ClearML Enterprise v3.28 offers new features and improvements to help administrators monitor usage, enforce policies, and streamline operations across large, multi-team environments. This release introduces enhanced usage metering with a simplified interface, improved resource policy management, improved dataset controls, and UI enhancements to provide greater clarity, control, and productivity for AI teams.

Optimizing Bitrise Build Cache clients

Having a build cache solution is a powerful way to speed up builds, especially at scale. Bitrise Build Cache already accelerates builds across multiple ecosystems, but to get the most out of it we also need to optimize the build cache clients themselves and ensure stability across changing network environments. In this blog post, I’ll walk through the steps we took to improve stability and performance for Bitrise Build Cache customers.

What are the key elements of that first POC that make it successful?

A successful POC shows value fast, within just a couple of weeks, by guiding teams through the tool, confirming success criteria, and proving that AI enhances rather than threatens testers’ work. It’s practitioner-focused, methodical, and designed to demonstrate real impact before purchase. — Mush Honda, Chief Quality Architect at Katalon Follow Katalon for more insights in our series!

OpenTelemetry vs. Deep Runtime Telemetry: Which Is Better for Your Node.js Stack?

If you're running Node.js in production, you've likely heard the buzz around OpenTelemetry. It's the industry standard for observability, backed by major vendors, and it promises vendor-neutral telemetry collection across your entire stack. For many teams, it's a game-changer: finally, a unified way to collect traces, metrics, and logs without getting locked into a single vendor's ecosystem.

From APIs to Agentic Integration: Introducing Kong Context Mesh

The promise of agentic AI is clear: autonomous systems that can reason, plan, and act on your behalf. But there's a fundamental problem standing between that vision and enterprise reality: agents need context to make decisions, and that context lives scattered across your organization. Context is any data — or any abstraction that enables access to data — that an agent needs to do its job. Customer records in your CRM. Inventory levels behind your fulfillment APIs.