Accelerating Development Velocity Using Docker: Docker Across Microservices - Couverture souple

Jangla, Kinnary

Couverture souple

ISBN 10 : 1484239350 ISBN 13 : 9781484239353

Editeur : Apress, 2018

Synopsis

Discover how a software engineer can leverage Docker in order to expedite development velocity. This book focuses on the fundamental concepts this program is built upon and explores how it can help you get your services up and running inside Docker containers. You'll also review tips on how to debug microservices applications that run inside Docker containers.

Tech companies are now developing complex softwares that are comprised of multiple services running on different platforms, and Docker has become an essential part of coordinating the communication between these services and platforms.

This book addresses problems caused by drifting microservices, debugging across services, inconsistent environments across machines, and coordinating development of machine learning systems between a team of developers, etc. Accelerating Development Velocity Using Docker puts you on the path to transforming your complex systems into more efficient ones.

What You'll Learn

• Setup Docker and employ quick solutions to road blocks
  
• Review challenges associated with debugging microservices that sit behind a complex application
  
• Leverage Docker features to seamlessly get multiple microservices up and running
  
• Debug inside a Docker container
  
• Review advanced use cases of Docker that can help consistency of development environments-

Who This Book Is For
Ideal for new to mid-level infrastructure engineers who want to learn how to make their development environments efficient across their and cross teams, or for students who aspire to learn basics of how to debug distributed systems and how to develop efficient applications.

A propos du livre

À propos de l?auteur

Kinnary Jangla has been in the tech industry for a dozen years and is currently an engineering manager at Pinterest overseeing the Docker Machine Learning Homefeed infrastructure team. Her main task is to ensure engineers are able to successfully train models for machine learning scenarios. She previously worked at Uber and Microsoft and is the author of two books and six patents. You can find her on Twitter @kjangla..

Détails de l'édition

• Éditeur: Apress
• Date d'édition: 2018
• Langue: anglais
• ISBN 10: 1484239350
• ISBN 13: 9781484239353
• Reliure: Broché
• Numéro d'édition: 1
• Nombre de pages: 168
• Coordonnées du fabricant: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Allemagne