Configuration Management (CM) is a systematic discipline for identifying, controlling, and documenting all components of a system throughout its entire lifecycle. This structured approach ensures consistency, traceability, and control over system changes from development through operation to decommissioning.
Configuration Identification: Unique identification and documentation of all Configuration Items (CI) such as software, hardware, documentation, and processes. Hierarchical structuring and baseline definition create systematic order.
Configuration Control: Formal control and approval of all changes through Change Control Boards (CCB). Change requests are evaluated, approved, and implemented according to defined procedures.
Configuration Status Accounting: Continuous capture and reporting of current status of all configuration items. Traceability matrix tracks changes and dependencies.
Configuration Verification and Audit: Regular verification of correspondence between documented and actual configuration through systematic audits.
Software Development: Version control systems like Git manage source code, build artifacts, and release packages. Continuous Integration/Continuous Deployment (CI/CD) automates configuration management processes.
IT Service Management: Configuration Management Database (CMDB) documents all IT assets and their relationships. Service mapping visualizes dependencies between business services and technical components.
Aerospace: Aircraft configurations are meticulously documented for safety and certification. Engineering Change Orders (ECO) control modifications to critical systems.
Automotive Industry: Vehicle configuration management manages millions of variants and options. Product Lifecycle Management (PLM) integrates CM into the entire development chain.
IEEE 828 defines international standards for Software Configuration Management. ISO 10007 specifies CM requirements for quality management systems.
ITIL Framework integrates Configuration Management into IT Service Management processes. Definitive Media Library (DML) and Configuration Management Database represent central information sources.
DoD-STD-973 regulates Configuration Management for defense projects. AS9100 extends ISO 9001 with aerospace-specific CM requirements.
Version Control Systems: Git, Subversion, and Perforce manage source code and documentation. Branching and merging strategies support parallel development.
Build and Release Management: Jenkins, Azure DevOps, and GitLab CI/CD automate build, test, and deployment processes. Infrastructure as Code (IaC) applies CM principles to infrastructure.
Asset Management Tools: ServiceNow, BMC Remedy, and Lansweeper document IT configurations. Auto-discovery automatically detects system changes.
Change Advisory Board (CAB) evaluates change requests for risks and business impact. Emergency changes follow accelerated approval processes for critical problems.
Impact assessment analyzes effects of planned changes on dependent systems. Rollback plans ensure quick recovery in case of problems.
Configuration baselines define approved configuration states at specific points in time. Functional, allocated, and product baselines mark important development milestones.
Baseline audits verify correspondence between documented and implemented configuration. Variance reports document identified deviations.
Configuration Item accuracy measures precision of CMDB data. Change success rate evaluates quality of change processes.
Mean Time to Recovery (MTTR) after configuration changes shows stability of CM processes. Compliance rate measures adherence to CM procedures.
Requirements management links configuration items with requirements for traceability. Test management coordinates configuration testing with CM activities.
Project management integrates CM milestones into project plans. Quality management uses CM data for audit and compliance evidence.
Complexity of modern systems requires automated CM tools and processes. Federated CMDB approaches integrate data from various sources.
Cultural change from ad-hoc management to disciplined CM requires systematic training and change management.
Tool integration between different CM systems uses APIs and standard interfaces for data flow.
AI-supported Configuration Management automatically recognizes patterns and anomalies. Machine learning optimizes change success probabilities.
Cloud-native CM tools support DevOps and agile development practices. GitOps extends Git-based CM to infrastructure and operations.
Configuration Management evolves into an intelligent, automated system that ensures system integrity, change control, and operational excellence in increasingly complex IT landscapes.