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DevOps: learn all about the culture of software development

Technically speaking, DevOps is the short form of development and operations software development culture that brings developers (Dev) and system administrators (Ops) closer together, making the necessary link for a more effective delivery of value.

DevOps culture is nothing but adoption of automated processes to quickly and securely deploy applications and services into production, freeing people to focus on other valuable activities, and reducing the risk of human failure. For this, software development, operations, and support teams involved (such as quality control) should be integrated.

Having multidisciplinary and autonomous teams working in silos increases security in internal processes that directly impact the customer experience. One could mention the practice of instant rebound, such as: each time changes are sent by the team, the entire DevOps conveyor belt is automatically triggered. At the end, the conveyor itself instantly notifies the development team pointing out the failures detected or the success of the deployment.

“The digital act is usually triggered to work on the DevOps review. Either in optimizing and deploying the method and culture, or in migrating from a common process conveyor to a more complete one – which brings more results, and delivers higher quality products. The most important thing is to monitor all phases, generate insights, and put them into practice, maximizing value delivery”, says Sólon Soares, our Software Architect.

Following are the DevOps life cycle stages:

  • Planning
  • Development 
  • Continuous integration (building and testing)
  • Continuous delivery (version generation in artifact repository)
  • Continuous deployment (in QA, HML, PRD, and other environments)
  • Monitoring

DevOps and agile go hand in hand, because both go far beyond practices: we are talking about real cultural changes, so that the Agile mindset gave rise to a model of fast delivery aligned with customer’s expectations. DevOps optimizes this system.

The most important thing is that both have a chain of actions that aim to reduce risks and costs, increase quality in automation processes and, above all, maximize the delivery of value.