Systems | Development | Analytics | API | Testing

Optimize Database Connection Pools for Peak Performance

When scaling an application to handle higher traffic, performance stalls or database errors often trace back to database connection pools running on default or generic settings that buckle under real-world load. The result? Connection timeouts, resource exhaustion, and users facing delays while the backend struggles. Establishing a new database connection can take 50 to 100 milliseconds per request, and multiplying that overhead by thousands of concurrent users can overwhelm infrastructure.

HTTP/3 Load Testing: Cloud Practices in 2026

HTTP/3 load testing requires more than updating legacy scripts. The move from TCP to UDP-based QUIC changes how traffic is generated and validated. Many popular tools, such as k6, default to older protocols unless HTTP/3 is specifically negotiated and confirmed. To avoid testing fallback scenarios, pair your application-level load tests with QUIC-aware validation.

Open Data Infrastructure in the age of AI agents

Fivetran + dbt Labs CEO George Fraser and Fivetran + dbt Labs President Tristan Handy sit down with Andreessen Horowitz general partner Martin Casado, one of the leading investors in software and AI infrastructure, to talk about Open Data Infrastructure in the AI era. Martin and his team have invested in dbt, Fivetran, Tabular, Cursor, OpenRouter, and many other companies.

Webinar Recap: Run Playwright Tests in the Cloud and Report Every Result with Katalon True

Playwright test suites can remain unchanged while reporting results alongside Katalon Studio and manual testing activities in a centralized platform. This was the focus of the webinar Bring Playwright into Katalon True, delivered in two sessions on October 14, 2026. The webinar focused on how Playwright integrates into a broader testing workflow rather than comparing Playwright with Katalon. Playwright is a free, code-first framework for browser automation that many teams already use.

Intelligent Document Processing Platform: 4 Must-Have Features for 2027

An intelligent document processing (IDP) platform uses AI technologies to automatically capture, classify, extract, validate, and route data from unstructured documents such as invoices, contracts, emails, PDFs, or even hand-written scans. As organizations continue to adopt AI into their daily workstreams, IDP is on track to shift from a back-office efficiency tool to a core component of enterprise AI automation.

Appian Q3 Release Highlights: AI Speed Meets Enterprise Controls

AI is evolving faster than organizations can keep up, and often it’s the most important operations that fall the furthest behind. That’s exactly why Appian is focused on AI for complex, enterprise-grade processes—to make applying AI automation to important work easy. Over the last quarter, Appian has continued to invest in capabilities that help you deploy AI fast without sacrificing control: Over 80% of developers regularly use AI coding tools.

Optimize Load Test Script Maintenance with AI

AI-driven load test script maintenance can significantly reduce the manual updates required by traditional tools. As your application evolves – whether through new user flows, updated endpoints, or changing parameters – AI features in some platforms help automatically adjust scripts to reflect these changes. This simplifies maintenance and allows your team to focus on testing outcomes rather than constant script rewrites.

Marketing Root Cause Analysis: Using AI to Diagnose Why Performance Dropped (and What It Leaves Out)

Your dashboard already told you ROAS dropped. The expensive question is why, and answering it means correlating data across platforms, isolating variables, and testing hypotheses against the numbers. Done by hand, that is an afternoon per incident. Done by AI, it takes seconds, with one catch.

Top Automated Testing Platforms for AI-Driven Software Development

AI-driven software development has reshaped what QA teams face daily. Codebases evolve faster, release cycles are shorter, and a single missed regression can hit production within hours. Today's top automated testing platforms have moved well past scripted checks, they now use machine learning to write, maintain, and adapt tests on their own. The five platforms below represent where the market stands in 2026, chosen for their AI architecture, enterprise track record, and real documented results.