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Performance monitoring with OpenTracing, OpenCensus, and OpenMetrics

If you are familiar with instrumenting applications, you may have heard of OpenMetrics, OpenTracing, and OpenCensus. These projects aim to create standards for application performance monitoring and collecting metric data. Although the projects do overlap in terms of their goals, they each take a different approach to observability and instrumentation.

Machine Learning-Powered Search Ranking of Airbnb Experiences

How we built and iterated on a machine learning Search Ranking platform for a new two-sided marketplace and how we helped itgrow. Airbnb Experiences are handcrafted activities designed and led by expert hosts that offer a unique taste of local scene and culture. Each experience is vetted for quality by a team of editors before it makes its way onto the platform.

How Uber Monitors 4,000 Microservices

With 4,000 proprietary microservices and a growing number of open source systems that needed to be monitored, by late 2014 Uber was outgrowing its usage of Graphite and Nagios for metrics. They evaluated several technologies, including Atlas and OpenTSDB, but the fact that a growing number of open source systems were adding native support for the Prometheus Metrics Exporter format tipped the scales in that direction. Uber found with its use of Prometheus and M3, Uber’s storage costs for ingesting metrics became 8.53x more cost effective per metric per replica.

The State of Kubernetes Configuration Management

Configuration management is a hard, unsolved problem. We share some unique insights about the strengths and weaknesses of several popular K8s config management tools. Of all the problems we have confronted, the ones over which the most brainpower, ink, and code have been spilled are related to managing configurations.

Teaching AI to learn speech the way children do

A collaboration between the Facebook AI Research (FAIR) group and the Paris Sciences & Lettres University, with additional sponsorship from Microsoft Research, to challenge other researchers to teach AI systems to learn speech in a way that more closely resembles how young children learn. The ZeroSpeech 2019 challenge (which builds on previous efforts in 2015 and 2017) asks participants to build a speech synthesizer using only audio input, without any text or phonetic labels. The challenge’s central task is to build an AI system that can discover, in an unknown language, the machine equivalent of text of phonetic labels and use them to re-synthesize a sentence in a given voice.

Ambassador 0.50 GA Release Notes: SNI, New AuthService and Envoy v2 Support

Updating Neural Networks to Recognize New Categories, with Minimal Retraining

Using Perforce in a Complex Jenkins Pipeline

Hi, I’m Guy ‘RiotSomeOtherGuy’ Kisel, a software engineer at Riot. You might remember me from Running an Automated Test Pipeline for the League Client Update. I work on the Riot Developer Experience team – our responsibilities include providing Jenkins servers and related infrastructure for engineers to use for building, testing, and shipping their software to the millions of players that play League of Legends.

Introducing AresDB: Uber’s GPU-Powered Open Source, Real-time Analytics Engine

At Uber, real-time analytics allow us to attain business insights and operational efficiency, enabling us to make data-driven decisions to improve experiences on the Uber platform. For example, our operations team relies on data to monitor the market health and spot potential issues on our platform; software powered by machine learning models leverages data to predict rider supply and driver demand; and data scientists use data to improve machine learning models for better forecasting. In the past, we have utilized many third-party database solutions for real-time analytics, but none were able to simultaneously address all of our functional, scalability, performance, cost, and operational requirements.