Continuous Deployment

continuous deployment tool

Problem

Complex deployment process that is difficult to automate: many components with different configuration have to be deployed to different target environments such as staging, test and production environments. High effort for manual deployments.

Solution

Visual modelling of software creates one place to keep an overview over deployments. Model is used as basis for end-to-end automation in Python automation engine. Modular automation makes changes to the deployment automation a breeze. 

The problem

Automatic deployment of software that consists of many components and/or is intended to be delivered in many different configurations to a wide variety of target systems is challenging. Do you know some of these problems?

  • Since the software is actively under development, the deployment process changes frequently. Therefore, there is hardly any investment in automation because the effort required to constantly adapt the automation is too high.
  • Manual deployment is very time-consuming. Changes in the software and the deployment process often lead to errors that take time to analyze and resolve.
  • The deployment process (and the software itself) is hardly documented. Information about changes that need to be taken into account during deployment is not always reliably passed on internally.
  • Attempts to automate the deployment with classic deployment tools or self-developed scripts were time-consuming and did not improve the situation.
  • Introducing deployment automation would be a change that affects multiple teams and departments. Getting everyone on board and implementing such a change is difficult.
  • There are no internal resources available to deal with deployment automation.

The solution: continuous deployment tool from Cloudomation

Modelling and end-to-end automation of the deplyoment process with Cloudomation Engine:

  • The Cloudomation platform allows easy modeling of the software, components and their dependencies. The modeling serves as a target state description for the underlying automation.
  • The automation of the deployment process is implemented in Python. In Python, complex and nested conditions can be easily mapped and any deployment logic can be automated.
  • By visually representing the software and the deployment process, the deployment process becomes tangible and understandable.
  • Modular automation in defined individual steps makes changes to deployment automation easy. 
  • Existing scripts and automations in other tools can be integrated and reused.
  • With affordable entry-level packages and flexible pricing, you can test deployment automation in a small team and gradually roll it out throughout the wider organization.
  • Our team is at your disposal throughout the entire process: develop your automations yourself, together with us, or commission us to carry out the entire implementation – just as you wish.
  • Automations remain lean, maintainable and clear

How it works

Visual modeling of your software as a basis for your automation: Describe your software. Use the model in deployment automation. Keep track of things.

Pro-code automation: This allows unprecedented flexibility with no predefined data model and no limits to express complexity.

Lean, fast, customer-centric: Lightweight platform, focus on customer enablement, customer-centric product development. 

The result

Modeling your software provides an overview and basis for deployment automation:

  • Since the model is used for automation, it always remains up to date
  • Model templates enable a quick start

Flexible automation that grows with the user:

  • Tailored to your requirements: As simple as possible, as complex as necessary
  • Adding, removing and changing release variants is quick and easy
Visibility and opportunity to collaborate on the process for all teams:
  • Graphical representation of the process also tangible for non-technicians
  • Traceability for all process steps