Joyent > Case Studies > Voxer Success Story

Voxer Success Story

Company Size

1,000+

Region

America

Country

United States

Product

Voxer Walkie Talkie

Tech Stack

Node.js
Riak
Joyent Cloud
SmartOS
DTrace

Implementation Scale

Enterprise-wide Deployment

Impact Metrics

Customer Satisfaction
Productivity Improvements

Technology Category

Application Infrastructure & Middleware - API Integration & Management
Platform as a Service (PaaS) - Connectivity Platforms

Applicable Industries

Software
Telecommunications

Applicable Functions

Business Operation
Sales & Marketing

Use Cases

Chatbots
Real-Time Location System (RTLS)

Services

Cloud Planning, Design & Implementation Services
Software Design & Engineering Services

About The Customer

Voxer is a social networking application that delivers walkie-talkie capabilities to a smartphone. It is one of the world’s largest and most popular Node.js applications, attaining the top ranking in its category in both the Apple App Store™ and the Android Market™. The application automatically detects other Voxer users who are already in a social graph and allows the user to immediately talk to them in real-time with voice quality comparable to standard cell phone calls. Originally developed as a distributed communications tool for first responders and other push-to-talk (PTT) users, Voxer has exploded in popularity among urban teens and other civilian users who enjoy the ease of use and the free messaging capabilities, delivered over WiFi, 3G and 4G mobile networks.

The Challenge

Voxer, a social networking application that turns your phone into a walkie-talkie and an all-in-one messenger, faced a challenge when its user base grew 10X over the course of a month. Their Linux-based storage system could not handle the load, leading to peak times where users had to wait for their messages to be downloaded, instead of always streaming them live. Voxer's back-end software is written entirely in Node.js, which can be challenging to understand and operate in production and at scale. The company needed to improve performance and gain complete transparency into all critical processes in the Voxer architecture and application stack, from low-level CPU and disk processes to database queries to web application servers and HTTP operations.

The Solution

Voxer CTO Matt Ranney elected to move Voxer’s core applications from bare-metal running in a managed hosting environment to the Joyent Cloud. As part of the move, Voxer transitioned its application stack off of the Linux operating system and on to Joyent SmartOS, a high-availability carrier grade cloud operating system. Ranney chose to make the switch specifically to take advantage of SmartOS’ Joyent Cloud Analytics and DTrace. DTrace is a dynamic tracing framework that allows operations teams and developers to analyze and instrument in nearly any part of any discrete compute process via 70,000 probes embedded throughout SmartOS. DTrace enables these deep-dive analytics in production environments in real-time with minimal system load (less than 1%). SmartOS also features unique debugging tools for Node.js that allow transparency equivalent to what can be achieved with native unabstracted coding and application environments.

Operational Impact

Voxer was able to use DTrace to achieve CPU profiling for Node.js applications and view the entire application stack to spot “hot” functions. This afforded Voxer critical insights on where the CPU was allocating compute resources and, by extension, what parts of an application stack were impacting performance and user experience.
Voxer gained granular insights into lower-level processes that greatly impact application performance such as disk I/O, file system latency, and network I/O. Because Voxer could run DTrace and Joyent Cloud Analytics through SmartOS on Joyent Cloud, Ranney could glean extremely detailed application activity information and gain transparency into how much compute resources each process was using.
Voxer was able to save money by optimizing application performance. Running cleaner code and more efficient applications enabled better utilization per virtual environment and lower costs.

Quantitative Benefit