Why You Need a Software Delivery Machine
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Many teams have a clear vision of how they want their software delivery to work. For example, what checks and staging deployments should occur on commits; what approval steps are required before promotion to production; what code needs to be included in new projects and what provisioning should occur on project creation; and what policies matter around license files and security scanning. But it’s hard to realize that vision. Typical challenges include: * Growing proliferation of services, meaning many delivery pipelines that can’t easily be changed as one, and many repositories with dependencies, configuration and usage practices getting dangerously out of date. * Bringing on new developers, due to lack of effective knowledge sharing and lack of automation * Creating new projects without copy/paste, leading to wasted effort and inconsistency * Lack of visibility into the whole elephant. What is deployed where? What is at what version? What is happening across the organization? Who should be informed in the case of a production alert, and to what code does it relate? The solution to these software problems is more software. These problems can best be addressed together, through greater automation, backed by a model spanning development and delivery. It’s what we call a software delivery machine.
Transcript
Many teams have a clear vision of how they want their software delivery to work. For example, what checks and staging deployments should occur on commits; what approval steps are required before promotion to production; what code needs to be included in new projects and what provisioning should occur on project creation; and what policies matter around license files and security scanning.
But it’s hard to realize that vision. Typical challenges include:
- Growing proliferation of services, meaning many delivery pipelines that can’t easily be changed as one, and many repositories with dependencies, configuration and usage practices getting dangerously out of date.
- Bringing on new developers, due to lack of effective knowledge sharing and lack of automation
- Creating new projects without copy/paste, leading to wasted effort and inconsistency
- Lack of visibility into the whole elephant. What is deployed where? What is at what version? What is happening across the organization? Who should be informed in the case of a production alert, and to what code does it relate?
The solution to these software problems is more software. These problems can best be addressed together, through greater automation, backed by a model spanning development and delivery. It’s what we call a software delivery machine.