Scaling Kubernetes to over 4k nodes and 200k pods

Scaling Kubernetes to Over 4k Nodes and 200k PodsPhoto by Todd Diemer on UnsplashAt PayPal, we recently started testing the waters with Kubernetes. A majority of our workloads run on Apache Mesos, and as part of this migration, we needed to understand several performance aspects of clusters running Kubernetes with a PayPal-specific control plane. Chief amongst these a...

Biometric authentication - Why do we need it?

In recent years, Identity and Access Management has gained importance within technology industries as attackers continue to target large corporations in order to gain access to private data and services. To address this issue, the Grab Identity team has been using a 6-digit PIN to authenticate a user during a sensitive transaction such as accessing a GrabPay Wallet. W...

Cómo fomenta Pinterest un  ecosistema sano de comentarios  gracias al aprendizaje automático

Cómo fomenta Pinterest un ecosistema sano de comentarios gracias al aprendizaje automáticoYuanfang Song | ingeniero de aprendizaje automático para la confianza y la seguridad; Qinglong Zeng | director de ingeniería de señales de calidad de contenido; Vishwakarma Singh | jefe de aprendizaje automático para la confianza y la seguridadThis article was originally publishe...

Capacity Recommendation Engine: Throughput and Utilization Based Predictive Scaling

Introduction Capacity is a key component of reliability. Uber`s services require enough resources in order to handle daily peak traffic and to support our different kinds of business units. These services are deployed across different cloud platforms and data centers ... The post Capacity Recommendation Engine: Throughput and Utilization Based Predictive Scaling appea...

Product Lessons from ML Home: Spotify’s One-Stop Shop for Machine Learning

Introduction  Building platforms is a hard business. Building platforms for discerning machine learning (ML) practitioners with bespoke needs and a do-it-yourself ethos is even harder. In today’s post, we will give you a peek into how we built ML Home, the internal user interface for Spotify’s Machine Learning Platform, and the product lessons we learned ......

Experiment without the wait: Speeding up the iteration cycle with Offline Replay Experimentation

Maxine Qian | Data Scientist, Experimentation and Metric SciencesIdeas fuel innovation. Innovation drives our product toward our mission of bringing everyone the inspiration to create a life they love. The speed of innovation is determined by how quickly we can get a signal or feedback on the promise of an idea so we can learn whether to pursue or pivot. Online experi...

#4 Session of MasterClass — Design, Leadership and Business impact

#4 Session of MasterClass — Design, Leadership and Business impactThere is no set path to becoming a Product Designer. Product design requires a diverse set of skills, ranging from user empathy to coding, and the greatest designers are highly talented generalists who work well with teams with areas of expertise they lack.Victor Salciotti will walk us through his journ...

A Lightweight Distributed Architecture to Handle Thousands of Library Releases at eBay

A new lightweight distributed architecture is proposed and applied on eBay’s release system to support thousands of libraries release work in high efficiency....

Auto-Diagnosis and Remediation in Netflix Data Platform

By Vikram Srivastava and Marcelo MaywormNetflix has one of the most complex data platforms in the cloud on which our data scientists and engineers run batch and streaming workloads. As our subscribers grow worldwide and Netflix enters the world of gaming, the number of batch workflows and real-time data pipelines increases rapidly. The data platform is built on top of...