Home » Author Archives: Viktor Farcic

Author Archives: Viktor Farcic

Viktor Farcic is a Software Developer currently focused on transitions from Waterfall to Agile processes with special focus on Behavior-Driven Development (BDD), Test-Driven Development (TDD) and Continuous Integration (CI).

Centralized System and Docker Logging with ELK Stack

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With Docker there was not supposed to be a need to store logs in files. We should output information to stdout/stderr and the rest will be taken care by Docker itself. When we need to inspect logs all we are supposed to do is run docker logs [CONTAINER_NAME]. With Docker and ever more popular usage of micro services, number of ...

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Build Automation Panel

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Last Tuesday, I participated in an online panel on the subject of Build Automation as part of Continuous Discussions (#c9d9), a series of community panels about Agile, Continuous Delivery and DevOps. Automating the build pipeline has many challenges, including third-party dependencies, build version management and especially culture, and panelists discussed real-life experiences addressing these challenges. Continuous Discussions is a community ...

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Microservices Development with Scala, Spray, MongoDB, Docker and Ansible

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This article tries to provide one possible approach to building microservices. We’ll use Scala as programming language. API will be RESTful JSON provided by Spray and Akka. MongoDB will be used as database. Once everything is done we’ll pack it all into a Docker container. Vagrant with Ansible will take care of our environment and configuration management needs. We’ll do ...

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Monolithic Servers vs Microservices

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Introduction At the beginning applications were simple and small due to simple requirements. With time requirements and needs grew and with them our applications became bigger and more complex. That resulted in monolithic servers developed and deployed as a single unit. Microservices are, in a way, return to basics with simple applications that are fulfilling today’s needs for complexity by ...

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Continuous Deployment: Implementation with Ansible and Docker

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This article is part of the Continuous Integration, Delivery and Deployment series. The previous article described several ways to implement Continuous Deployment. Specifically, it described, among other things, how to implement it using Docker to deploy applications as containers and nginx for reverse proxy necessary for successful utilization of blue-green deployment technique. All that was running on top of CoreOS, ...

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Continuous Deployment: Implementation

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This article is part of the Continuous Integration, Delivery and Deployment series. Previous post described several Continuous Deployment strategies. In this one we will attempt to provide one possible solution for reliable, fast and automatic continuous deployment with ability to test new releases before they become available to general users. If something goes wrong we should be able to rollback ...

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Continuous Deployment: Strategies

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This article is part of the Continuous Integration, Delivery and Deployment series. Previous article provided introduction to continuous deployment. In this one we’ll continue where we left and explore different strategies to deploy software. The article is in no way an exhaustive list of ways to deploy applications but tries to provide few common ways that are in use today. ...

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Continuous Deployment: Introduction

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This article is part of the Continuous Integration, Delivery and Deployment series. Continuous deployment is the ultimate culmination of software craftsmanship. Our skills need to be on such a high level that we have a confidence to continuously and automatically deploy our software to production. It is the natural evolution of continuous integration and delivery. We usually start with continuous ...

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Continuous Delivery: Code Coverage

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This article is part of the Continuous Integration, Delivery and Deployment series. In the previous article we explored unit tests as the first and fastest set of tests we should run. Now it’s time to see whether our unit tests provide enough code coverage. Code Coverage Unit tests by themselves do not provide enough confidence unless we know that they ...

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