BuildR is an extension of the Rake build tool for Apache projects that allows defining and building Java projects. It provides features like defining dependencies, compiling code, packaging artifacts, custom tasks, testing, and calling other build tools like Ant from within a BuildR project definition. BuildR supports languages like Java, Scala, Groovy, and Ruby and provides additional capabilities like an interactive shell, IDE project file generation, and code coverage tools.
1. Habitat consists of several components including Habitat Studio for packaging applications, Habitat Plans for instructions to install applications, and Habitat Depot for uploading and downloading application packages. 2. The packaging process starts with creating a Plan which defines how to build an application from source code using Bash. The built package is then uploaded to the Depot. 3. At runtime, the Habitat Supervisor manages application behavior using the predefined Plan. It provides service discovery, deployment coordination, and a REST API for management.
This document discusses how Chef configuration management is used centrally at Sky Betting and Gaming to provide tools and services for developers to deploy applications. It describes how the Platform Services team started by "fixing disaster recovery" and introduced Chef. Key aspects of their process include using Chef configuration for infrastructure, applications, CI pipelines, and integration tests. The document also outlines their use of a tool called pscli, which acts as "glue" by pulling Docker images containing tools like ChefDK, Terraform, and Packer and executing commands in containers to perform tasks like generating cookbooks, running Kitchen tests, and applying Terraform configurations.
1) The document discusses using Spring Boot, Docker, and Kubernetes for Java microservices. 2) It provides instructions on building a Spring Boot app as a Docker container and deploying it to Kubernetes. 3) Demos are shown for building a sample app, running it on a local Kubernetes cluster, and splitting the app into microservices deployed to Kubernetes.
When your code base and dependency graph become big you should consider moving to bazel as your build tool. It's both extremely fast and highly accurate. You'll need to decide and think about 5 key points in order to achieve a successful migration.
What's new in Chef presented at EMEA Community Summit in London, October 2016 by Thom May and Tim Smith
Part 2 of Compliance Automation with Inspec Overview presented on 9/29 at TSA DevOps Transformation Day
Tutorial for OpenShift beginners: Use Eclipse IDE to develop and deploy a Java based HelloWorld API function in 8 steps.
At Wix We decided to switch to the Bazel build tool. The result was a dramatic improvement in performance and accuracy. As Wix Backend grew exponentially with more than 700 micro-services, it became obvious our build times on Maven have been slowing us down. We decided to switch to the Bazel build tool while harnessing the “remote build execution” feature. The result was a dramatic improvement in performance and accuracy of builds. In this talk, I will share with you how to achieve a successful migration to Bazel from Maven or Gradle, focusing on 5 important areas you have to think about and decide on the right approach for you, ranging from choosing the right build unit granularity to remote caching best practices. I will also describe and demonstrate some of the available tools in the eco-system that help with the migration and with making everyday work easier.
The document discusses using Bazel for building Scala projects. It begins with an overview of Bazel and how it uses small targets and rules to build code more incrementally and in parallel compared to tools like Maven and Gradle. It then covers the rules_scala plugin, which provides rules for compiling Scala code into JARs and running tests. Features of rules_scala like dependency management and support for multiple Scala versions are also summarized. Overall the document promotes Bazel and rules_scala as enabling significantly faster builds of large Scala codebases.