How should organizations plan for a cloud environment and optimize it for efficiency at scale? InfoQ reached out to 3 leading cloud practitioners to uncover practical advice on this topic. Each panelist has dealt with the sometimes-messy transition from on-premises to cloud, and coached organizations through their journey.
As more organizations expand their use of public cloud services, from early-stage startups to the biggest businesses and governments in the world, the problems of cloud computing at scale start to arise.
When assessing technology that empowers a DevOps transformation, it’s easy to focus in on the headline capabilities (“configuration management!”) and miss out on the bigger picture. How can teams shipping cloud (or on-premises) applications use the full suite of DevOps technologies to simplify delivery and management at scale? This article classifies and explains key enabling technologies.
Yaniv Yehuda looks at the challenges involved in automating database deployments and offer suggestions based on Agile and DevOps concepts. 7
In this article Ping Chen shares her experiences on how to pragmatically maintain a large legacy application. 9
In this article we hear a very personal story on introducing a DevOps mindset at a large bank. In particular how the automation of configuration and release management processes enabled collaboration.
Learning Gerrit Code Review presents an overview of the Gerrit review tool, from how to install and configure projects through to how to integrate with other services like GitHub and Jenkins.
Mitchell Hashimoto released his book "Vagrant up and running" which covers everything from basic Vagrant usage to extending its functionality.
Konrad Lukasik provides practical advice on versioning and preparing a database for delivery using upgrade scripts. The article is based on experiences from enterprise environment and includes scripts 12
The number of jobs in a continuous integration tool can range from a few to several thousand, all performing various functions. There is an approach to manage these jobs in a more efficient manner. 1
To refactor legacy code, the ideal is to have a suite of unit tests to prevent regressions. However it's not always that easy. This article describes a methodology to safely refactor legacy code. 7
In his new article Jonathan Natkins explains how to use components of Apache Hadoop, including Flume, Hive and Oozie to implement a typical Data management system. 2