• Introducing FuseBox, an alternative to Webpack
• Advanced web security topics
• Scaling Machine Learning at Uber with Michelangelo
• EvilGinx – Standalone man-in-the-middle attack framework
• Why you should avoid ORMs (with examples in Node.js)
• Learn Document Node in 10 seconds from my business card

• Monolithic Architecture vs. Microservices: Choosing the Right Architecture for the Project
• Apache Kafka’s Distributed System Firefighter — The Controller Broker
• Profiling: The Case of the Missing Milliseconds
• Power-efficiency for performance-deficiency
• Avoid Architectural Change Disaster with App Performance Monitoring
• Neural Networks For Music: A Journey Through Its History
• Role of DevOps in Mobile App Development
• A Container For Your App, My Dear!

Siapa dan apa yang dilakukan di Jenius?

Halo! Perkenalkan nama saya Dedi Setiadi, saya bekerja di Jenius sebagai Quality Assurance Specialist.  Kenapa Quality Assurance? Ga cuma makanan atau kendaraan aja dong yang perlu Quality Assurance, sebuah perangkat lunak pun perlu ada Quality Assurance.

Selain memastikan aplikasi Jenius ini sudah sesuai dengan requirement (baik itu dari sisi teknis maupun estetis), we, as a Quality Assurance love to break what the developers already build (atau istilahnya mencari-cari kesalahan gitu). Jadi bisa dibilang QA itu punya love-hate relationship sama para developer. 😂😂

• Kubernetes 202 — Making It Fully Operational
• Who Is in Charge of Developing a DevOps Culture?
• 7 open source platforms to get started with serverless computing
• The End Is Near for Mobile Apps
• 3 best practices for continuous integration and deployment
• Reflecting on Building Real-time APIs at Facebook
• Add It Up: China Uses Open Source to Deliver Cloud Services

• awesome-css-frameworks
• How to solve the last mile logistics conundrum?
• Measuring Performance With Server Timing
• How S3 Signed URLs work
• Introducing the Apollo GraphQL Platform
• Understanding Production: What can you measure?
• Uber Introduces PyML: Their Secret Weapon for Rapid Machine Learning Development