July 13, 2016
Ep. #1, Driving Adoption With Your Product Launches
Welcome to Practical Product, a new podcast where you'll learn how to define the right product to build. In this first episode, hosts Craig ...
Heavybit is excited to announce our latest Heavybit member, LightStep.
LightStep enables developers and DevOps to trace individual requests with incredibly high fidelity and use this information to identify root causes and fix problems in highly concurrent or microservice-based applications.
The world is moving to highly concurrent, heterogeneous distributed systems. Monolithic applications have been split into lean and modular microservices. With this evolution, teams move faster and applications scale more easily. However, visibility into the production stack has suffered. Teams are being forced to reconsider how they do everything from latency monitoring, alerting, and distributed debugging to resource accounting, security audits, and policy enforcement.
LightStep’s powerful product solves this problem and delivers unprecedented visibility into modern software systems. The founding team brings a deep understanding of performance monitoring and production systems, informed by their experiences and lessons learned building Google’s Dapper technology.
We are excited to be working with LightStep to help drive change in how software services are built.
About the Founders:
Daniel Spoonhower | LinkedIn
Spoons (aka Daniel Spoonhower) worked on Google’s infrastructure (including deployment and configuration management) and on the Google Cloud Platform frontend. He has a PhD in parallel programming languages and still hasn’t found one he loves.
Benjamin Cronin | LinkedIn
Previously Ben was the CTO of Pusher, a design agency specializing in high-quality engineering work for clients such as Tesla Motors, Meraki and Lululemon. Prior to his role as the CTO of Pusher, he spent seven years at Autodesk as an engineering lead working on the AutoCAD graphics pipeline
Ben Sigelman | LinkedIn
Ben spent nine years at Google where led the design for several large (~1e6-process) distributed systems. The most significant of these were Dapper, an always-on distributed tracing system; and Monarch, a high-availability timeseries collection, storage, and query system.