Articles

This article discusses a theoretical foundation for code coverage analysis as well as a practical implementation approach based on the Travis-CI continuous integration system and the Coveralls code coverage analysis tool.

Intentions behind code coverage analysis

Code quality is the cornerstone of any project. Poor code imposes more and more overhead for its maintenance over time, while adding new features takes more time and effort than it would for the quality code. It goes without saying, that criteria for code quality are not universal, they are defined and modified throughout the life cycle of the code.

There are many ways and tools for managing code quality from technical, as well as from organizational perspectives. These tools, when applied by experienced professionals, can ensure compliance with high standards and make the developers proud of their code. These very same tools may in other cases completely paralyze the team by encouraging the developers to dovetail their code for passing excessive checks, at the same time ignoring its more important quality-defining properties.

Our company develops distributed software applications. In order to provide cooperation between components, these applications employ different methods of inter-process communication. The most of the complexity arises during the implementation of the algorithms for distributed processing of interconnected data. These problems require utilization of a special purpose distributed coordination system. The most popular and widely used coordination system is Apache Zookeeper.

For the last two years we have been using Docker containerization solutions for the needs of development, CI and production environments. All current products for the customers are being developed to be run in Docker.

We have a very positive experience about that solution. However, Docker changes a lot, from version to version it introduces new amazing stuff like Compose, Swarm, additional security features, which, sometimes, lead to errors in containers that was considered as stable.

The article demonstrates an approach to the integration of Apache CloudStack (ACS) with 3rd party systems implemented by exporting of ACS’s events data to Apache Kafka message broker.

Nowadays the product integration capabilities are vital when developing modern complex services. Speaking about cloud and telecommunication industries, services are being integrated together with billing and monitoring systems, 3rd party cloud services and providers, helpdesk trackers and other business-oriented and infrastructure components.

The article describes a method for deployment of highly available ACS management servers with multi-master cluster of MariaDB (Galera).