InfoQ Homepage Presentations
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Going Cloud Native with Spring Cloud Azure
Yitao Dong and Yawei Wang show how to create cloud native apps with Spring Cloud on Azure.
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Chaos Engineering for PCF
Karun Chennuri and Ramesh Krishnaram show chaos tools built on ChaosLemur to verify the resistance to failure of a system running on PCF.
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DevOps at Scale – Success Stories
Omer Felder shares what is needed to achieve the transformation to DevOps at scale, along with the biggest challenges companies and governments face during this process.
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Big Data and Deep Learning: A Tale of Two Systems
Zhenxiao Luo explains how Uber tackles data caching in large-scale DL, detailing Uber’s ML architecture and discussing how Uber uses Big Data, concluding by sharing AI use cases.
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Blind Spots: Cognitive Biases and Systems
Craig Larman keynotes on how the brain influences forming of biases and leads an exercise on finding biases and countering them.
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Testing the Endpoints of Your REST APIs
Tonya Cooper discusses how to test REST API endpoints through unit testing the controllers and integration testing with Postman.
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Spring Boot 2.0 Web Applications
Brian Clozel and Stéphane Nicoll demo a WebFlux application and leverage Boot features such as Actuator, Developer Tools and more.
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The New Kid on the Block: Spring Data JDBC
Jens Schauder describes the current state of Spring Data JDBC, its features and some of the underlying design decisions, especially its DDD-based API.
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Reactive Spring Security 5.1 by Example
Rob Winch demos applying Spring Security to a reactive application, highlighting some of the new features in Spring Security 5.1.
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Securing Spring Functions by Breaking in
Guy Podjarny breaks into a Spring Cloud Functions application and exploits multiple weaknesses, explaining how to avoid them.
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Data-Informed HR for High-performing Teams
Aubrey Blanche provides actionable strategies and methodologies needed to build balanced, high-performing teams at scale.
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Product Management of AI Products
Manjeet Singh discusses how to bring AI to enterprise product lines, how to analyze, plan, and design AI in a SaaS environment along with practices and lessons learned from Agile AI product lifecycle.
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