Environment Management
Manage the environments for all solution delivery activities.
Improvement Planning
Practices-Outcomes-Metrics (POM)
Representative POMs are described for Environment Management at each level of maturity.
- 2Basic
- Practice
- Define a standard production environment.
- Outcome
- A standard production environment is defined.
- Metric
- Existence of a defined production environment.
- Practice
- Test solutions using data obtained from production, as required.
- Outcome
- Problems found by testing better match the potential problems in the live system.
- Metrics
- # of data-related problems found after roll-out.
- # of hours used to generate test data.
- 3Intermediate
- Practice
- Implement environments on virtualized infrastructure (e.g. cloud, virtual machines).
- Outcome
- A virtualized infrastructure is in place.
- Metric
- Time required to stage a specific environment.
- Practices
- Ensure that cleaned and anonymized cloned production data is used and data access is controlled.
- Put in place reference (gold) copies of data.
- Outcome
- Efficiency is increased.
- Metrics
- # of data-related problems found after roll-out.
- # of hours used to generate test data.
- 4Advanced
- Practices
- Implement replica environments on a virtualized infrastructure.
- Ensure that self provisioning of production-like test environments is in place.
- Put in place fully repeatable roll-forward and roll-back methods.
- Outcomes
- Data integrity is maintained.
- Being able to self-provision environments reduces test time.
- Metrics
- # of replica environments that are not self provisioned.
- # of environments provisioned (tests deployed and torn down).
- Practices
- Ensure that there is a system in place to generate new data suitable to the test environment.
- Ensure that test suites seamlessly integrate with refreshed data.
- Outcome
- For new systems with little or no live data, this will help identify problem at an early stage.
- Metrics
- # of data-related problems found after roll-out.
- # of hours used to generate test data.
- 5Optimized
- Practices
- Implement multiple types of environments that can be automatically provisioned, and supported.
- Ensure that definitions of environments are solution-led, depending on specific needs.
- Outcome
- Data integrity is maintained with maximum flexibility.
- Metrics
- # of replica environments that are not self provisioned.
- # of environments provisioned (tests deployed and torn down).
- Practices
- Ensure that there is an overall master data strategy in place, part of which includes the provision of test data.
- Where appropriate, implement advanced techniques, such as artificial intelligence (AI).
- Outcome
- Data usefulness is improved, and generated data is normalized to the environment.
- Metrics
- # of data-related problems found after roll-out.
- # of hours used to generate test data.