Systems | Development | Analytics | API | Testing

How Developers Can Use Generative AI to Improve Data Quality

It sounds counterintuitive—using a technology that has trust issues to create more trustworthy data. But smart engineers can put generative AI to work to improve the quality of their data, allowing them to build more accurate and trustworthy AI-powered applications.

Moving Your AI Pilot Projects to Production

Without a doubt, Artificial Intelligence (AI) is revolutionizing businesses, with Australia’s AI spending expected to hit $6.4 billion by 2026. However, according to The State of Enterprise AI and Modern Data Architecture report, while 88% of enterprises adopt AI, many still lack the data infrastructure and team skilling to fully reap its benefits. In fact, over 25% of respondents stated they don’t have the data infrastructure required to effectively power AI.

The critical role of a hybrid cloud architecture in ensuring regulatory compliance in financial services

A prominent global bank was thrust into the spotlight for all the wrong reasons. The institution was hit with a staggering fine – multiple billions – for failing to comply with new data protection regulations that ultimately led to a customer data breach. The breach, which exposed sensitive information, not only resulted in financial penalties but also caused significant reputational damage.

S1.E19: Web testing with Playwright | QA Therapy Podcast

Feeling uncertain about which framework to adopt for web testing? You're not alone. Tools like Playwrigt, are emerging as excellent options. We're thrilled to have Debbie O'Brien as our guest. Debbie serves as a Senior Program Manager at Microsoft, where she passionately advocates for better testing with Playwright. // R E S O U R C E S.

How to source data from AWS DynamoDB to Confluent using DynamoDB Streams and AWS Lambda

This is a one-minute video showing an animated architectural diagram of the integration between Amazon DynamoDB and Confluent Cloud using DynamoDB Streams and AWS Lambda. Details of the integration are provided via narration.

Shift left to write data once, read as tables or streams

Shift Left is a rethink of how we circulate, share and manage data in our organizations using DataStreams, Change Data Capture, FlinkSQL and Tableflow. It addresses the challenges with multi-hop and medallion architectures using batch pipelines by shifting the data preparation, cleaning and schemas to the point where data is created and as a result, you can build fresh trustworthy datasets as streams for operational use cases or Apache Iceberg tables for analytical use cases.

EP11: Cell-Based Architecture

In this special edition, hosts Sanjiva and Asanka are joined by WSO2 co-founder Paul Fremantle for an in-person recording in the studio. Sanjiva leads the discussion, while Paul and Asanka, co-authors of the cell-based architecture, share their insights and experiences. Together, they explore the core principles of cell-based architecture, its practical applications, and how it reshapes modern software architecture.

The Real Cost of Ignoring Red Alerts in Software Quality

57% of consumers are willing to switch to a competitor after three or four negative interactions. And that's being generous—sometimes it only takes one or two. Companies can’t afford to ignore red alerts anymore. Take Amazon's checkout flow, for example. It always works because they prioritize testing it rigorously to ensure their core business can generate revenue, even if other features are less polished.

Q&A with Bitrise's CSO on Gartner's Magic Quadrant: What's next for DevOps?

The DevOps landscape continues to evolve rapidly. As more organizations embrace DevOps to stay competitive, the landscape is shifting to include more diverse players and specialized offerings. But what's next for the space? Gartner's latest Magic Quadrant for DevOps Platforms report highlights the latest developments and standout players in the space, including Bitrise's growing impact on mobile DevOps.

Enhancing AI Customer Experience: A Practical Guide

Organizations are harnessing the power of AI to revolutionize products and services across industries. But AI-powered solutions have been getting more sophisticated. We need to redesign and amend our approach to understanding how customers experience these solutions. Unlike traditional products, AI solutions are dynamic, continuously learning and adapting. Traditional metrics may fall short of capturing the nuances of how users interact with AI.