Try asking IT for data on the development, test, production and disaster recovery environments in the data centre and public clouds like Amazon Web Services (AWS) or Azure. It’s a straightforward question, yet answering it accurately and without going through a time-consuming audit is difficult for many IT operations departments.
Service configuration management is a core ITIL (Information Technology Infrastructure Library) management practice, and the CMDB (configuration management database) is the data warehouse that stores information on IT assets. IT’s task is to load and maintain the CMDB with accurate, up-to-date, comprehensive information. Maintaining the CMDB is a significant challenge for organisations that have large IT footprints or that make frequent changes using devops CI/CD automations to deploy applications and IaC (infrastructure as code) to configure multicloud infrastructure.
Enter DDM (discovery and dependency mapping) tools that scan networks to extract configuration information and update CMDBs with accurate data. A DDM is essential for organisations with large data centres and cloud infrastructures and can be a game changer in improving ITSM (IT service management) processes, such as incident management or change management.
DDM tools are often a data source for AIops or machine learning capabilities and are a form of hyperautomation when combined with low-code automation, workflow, and integration tools. For example, categorisation engines can use DDM’s data to group systems, or anomaly detectors can flag outlier flow patterns.
DDM-powered CMDBs scan autoscaling infrastructure for changes
A typical CMDB stores information on CIs (configuration items), including the configurations of network devices, servers, virtual servers, cloud instances, applications, web services, databases, storage configurations, and other infrastructure components. Many CMDBs capture dependencies between CIs and allow rolling them up into business services.
CMDBs may be part of an ITSM platform or an independent product. Top platforms include Atlassian Insight, BMC Helix, Cherwell CMDB Software, CloudAware CMDB, IBM Control Desk, Ivanti Asset Manager, ManageEngine CMDB, Micro Focus Universal CMDB, ServiceNow CMDB, Proactivanet Discovery and Asset Management, Symphony SummitAI, Virima CMDB, and many others.
Keeping the CMDB updated isn’t an insurmountable challenge for smaller organisations with a few hundred IT assets or when IT systems don’t change frequently. It may not be a top priority for organisations that only use the CMDB for asset management, either.
But the CMDB’s correctness is vital for organisations that want to integrate the CMDB with other ITSM processes, such as incident management or change management. It’s also critical for large enterprises with multiple or geographically dispersed data centres with tens of thousands of CIs.
If your infrastructure is entirely automated, then devops teams can automate DDM with tools like Chef’s integration with ServiceNow or Ansible-CMDB. But for many organisations running hybrid clouds, multiclouds, or using multiple devops automation tools, a do-it-yourself approach to maintaining the CMDB may not be an option.
DDM tools are the data integration platforms for CMDBs. These tools may be a feature of a CMDB or separate capabilities from secondary providers, such as Autointelli, FireScope, Resolve, or ScienceLogic. The more advanced tools are agentless and can scan networks without installing software on the servers or virtual hosts. A differentiating feature is when the DDM also captures the dependencies between system components and provides topology maps to illustrate them.
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