Sat.Dec 03, 2016 - Fri.Dec 09, 2016

article thumbnail

Introducing Chaperone: How Uber Engineering Audits Apache Kafka End-to-End

Uber Engineering

As Uber continues to scale, our systems generate continually more events, interservice messages, and logs. Those data needs go through Kafka to get processed. How does our platform audit all these messages in real time? To monitor our Kafka pipeline … The post Introducing Chaperone: How Uber Engineering Audits Apache Kafka End-to-End appeared first on Uber Engineering Blog.

Kafka 75
article thumbnail

Zalando Continues Being Part of the React Ecosystem at ReactNL 2016

Zalando Engineering

After attending React Europe 2016 in June, we had the pleasure to be a sponsoring partner for the first ReactNL Conference in Amsterdam this year. It was a great experience to meet developers in the React community from all around the globe, as well as showing them a taste of our Berlin offices by having “Club Mate” available for one and all! Flying the Zalando Tech flag, Kolja Wilcke and Andrey Kuzmin had an interesting talk about one of their Hack Week projects called “Elm Street 404” , an int

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Hive vs.HBase–Different Technologies that work Better Together

ProjectPro

HBase and Hive are two hadoop based big data technologies that serve different purposes. For instance, when you login to Facebook, you see multiple things like your friend list, you news feed, friend suggestions, people who liked your statuses, etc. With 1.79 billion monthly active users on Facebook and the profile page loading at lightning fast speed, can you think of a single big data technology like Hadoop or Hive or HBase doing all this at the backend?

article thumbnail

Cherami: Uber Engineering’s Durable and Scalable Task Queue in Go

Uber Engineering

Cherami is a distributed, scalable, durable, and highly available message queue system we developed at Uber Engineering to transport asynchronous tasks. We named our task queue after a heroic carrier pigeon with the hope that this system would be just … The post Cherami: Uber Engineering’s Durable and Scalable Task Queue in Go appeared first on Uber Engineering Blog.

article thumbnail

From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

article thumbnail

Hack Like a Girl with Zalando Tech

Zalando Engineering

I recently had the opportunity to be a mentor at the Hack Like A Girl Hackathon. It was organized by Geek Girls Carrots Berlin , with Zalando on board as a sponsor. The hackathon had a health and fitness theme, and I jumped at the chance to volunteer for the event. Before the hacking was to begin, participants and mentors met up at the Native Intruments offices on Friday evening to brainstorm their health and fitness related hacks for the weekend.

Coding 52
article thumbnail

Cherami: Uber Engineering’s Durable and Scalable Task Queue in Go

Uber Engineering

Cherami is a distributed, scalable, durable, and highly available message queue system we developed at Uber Engineering to transport asynchronous tasks. We named our task queue after a heroic carrier pigeon with the hope that this system would be just … The post Cherami: Uber Engineering’s Durable and Scalable Task Queue in Go appeared first on Uber Engineering Blog.

article thumbnail

Recap of Hadoop News for November

ProjectPro

News on Hadoop-November 2016 Microsoft's Hadoop-friendly Azure Data Lake will be generally available in weeks. TechRepublic.com, November 2, 2016. Microsoft's cloud-based Azure Data Lake will soon be available for big data analytic workloads. Azure Data Lake will have 3 important components -Azure Data Lake Analytics, Azure Data Lake Store and U-SQL.

Hadoop 52