Systems | Development | Analytics | API | Testing

AWS and Confluent: Meeting the Requirements of Real-Time Operations

As government agencies work to improve both customer experience and operational efficiency, two tools have become critical: cloud services and data. Confluent and Amazon Web Services (AWS) have collaborated to make the move to and management of cloud easier while also enabling data streaming for real-time insights and action. We’ll be at the AWS Public Sector Summit in Washington, DC on June 26-27 to talk about and demo how our solutions work together.

AI for APIs: Unlock Growth and Efficiency

AI-powered tools can enhance API marketplace management by automating various tasks such as API discovery, onboarding, and governance. Advanced recommendation systems can match developers with relevant APIs based on their preferences and project requirements, facilitating faster adoption and increasing transaction volumes within the marketplace.

What is API Monitoring? Best Practices to Track API Performance and Metrics

API downtime can cost businesses an average of $140,000 to $540,000 per hour. Maintaining reliable and high-performing APIs has become critical for any digital business’s success, with much at stake. This scenario is where API monitoring steps in. An important part of API management, monitoring API metrics allows organizations to detect issues rapidly and optimize their API performance.

Data Lineage: A Complete Guide

Data lineage is an important concept in data governance. It outlines the path data takes from its source to its destination. Understanding data lineage helps increase transparency and decision-making for organizations reliant on data. This complete guide examines data lineage and its significance for teams. It also covers the difference between data lineage and other important data governance terms and common data lineage techniques.

Snowflake: Automate tuning for data cloud speed and scale

40% of companies surveyed will increase their AI investment because of advances in GenAI (McKinsey). And 80% plan to maintain or increase their investment in data quality/observability (dbt). With this in mind, Unravel is hosting a live event to help you leverage data observability to achieve speed and scale with Snowflake. Join Unravel Data for this event about automating tuning with AI-powered data performance management for Snowflake with Eric Chu, Unravel Data VP of Product, and Clinton Ford, Unravel Data VP of Product Marketing.

Addressing the Elephant in the Room - Welcome to Today's Cloudera

Hadoop. The first time that I really became familiar with this term was at Hadoop World in New York City some ten or so years ago. There were thousands of attendees at the event – lining up for book signings and meetings with recruiters to fill the endless job openings for developers experienced with MapReduce and managing Big Data. This was the gold rush of the 21st century, except the gold was data.

Which Language Should Testers Use?

Should you design tests in the same language as the application you’re testing, or should you use the language you’re best at? @Hanson Ho recommends using the language that’s most popular in the application’s platform. This way, you’ll have more help available from the community. If you want more insights like this one, check out Test Case Scenario.