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Let IT Initiatives be The Driver of CMDB Health Projects

This post is from the Numerify blog and has not been updated since the original publish date.

Last Updated Dec 13, 2018 — AI-Powered Analytics expert

Let IT Initiatives be The Driver of CMDB Health Projects

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The CMDB is Dead!

IT operations gurus and service delivery pundits have regularly predicted the demise of the Configuration Management Database (CMDB) over the last 15 years. They had rightful reasons to think so. For starters, CMDBs are still cumbersome and depend on ineffective and tardy manual processes for maintenance. CMDB automated discovery and mapping tools, while significantly improved since the early days, always need to be augmented with manual updates. In the modern world of agile, hybrid clouds, virtualization, containers, and serverless computing, where change is too rapid, CMDBs may also be perceived to be less relevant.

Long live the CMDB!

If you fast forward to 2018, the CMDB, whether a federated variant (CMDBf) or a generic configuration management system, is still central in large enterprises and underpins many processes. In large enterprises, disciplines such as IT asset management, Change Impact (CI), service delivery analysis and security audit and compliance still rely on CMDBs, however imperfect they may be. The sheer size of IT deployments in these enterprises requires tracking a high volume of equipment, applications and relationships. Even when enterprises gradually modernize their infrastructure, CMDBs will likely evolve to subsume newer technologies and adapt to a world of clouds, containers, SDN, virtual storage, etc.

Yet, the challenges of trusting and relying on CI asset and relationship information are issues that IT leaders continue to grapple with. Groups need to rely and trust CMDB data as well the results of using this data in group processes.

Tailor CMDB health upgrade to specific IT initiatives

To overcome these trust and reliance challenges with CMDB data quality, large enterprises increasingly undertake targeted CMDB health upgrade projects in parallel to specific IT initiatives.

At a high level, this can be viewed as a continuous three-step process in an ongoing evolutionary framework.

1. Tailor and tie CMDB health and data quality projects with bite-sized operational and strategic initiatives.

Below are some examples of typical IT initiatives that our customers have undertaken for targeted segments, divisions or applications:

  • Retiring low performing assets
  • Application health
  • Infrastructure modernization
  • Incident Reduction
  • Change Management

2. Use CMDB health analytics to bring razor sharp visibility to gaps in correctness, currency, compliance, consistency of CI and relationships data.

3. Track progress in CI Data Quality over time and foster a continual improvement process with teams.

Going a step further, one can also measure IT initiative success with parallel improvement projects to CMDB Quality for the specific applications or infrastructure elements in consideration.

CMDB perfection is the enemy of success

Enterprises that successfully improve their CMDB health, also realize that seeking close to perfection will inhibit success. So, they make steady improvements through continuous data quality improvement visibility. Analytics and machine learning models can eke out context and intelligence from imperfect data while evolving the CMDB to greater health and quality.

Improving CMDB health through ongoing analytics

A number of our customers have leveraged the 3-step approach above to improve CMDB health with analytics through pegging it with specific IT initiatives.

An initiative such as consolidated application health visibility across stakeholders naturally engenders a parallel CMDB health upgrade plan, given the reliance on accurate and current application to infrastructure topologies and relationships. In a specific customer case, IT operations, business owners, and app development teams were reporting different versions of app health and needed a common view for consistent decision making and to build credibility with business leaders. They needed health scorecards for applications and supporting infrastructure with degradation of health scores by incidents, outages and changes, as well as qualitative risk data. They launched a parallel CMDB health upgrade initiative with analytics to surface gaps. The need was to:

  • Fix relationships, completeness and correctness to support App Health views with respect to the percentage of mandatory fields that were incomplete.
  • Identify changes to CIs that were unauthorized, whether done through automated robots or manually to fix and for process improvement.
  • Track CMDB CI completeness and correctness over time to see how visibility was driving improvement.

CMDB completeness and correctness dashboards enabled IT to fix CMDB configuration and relationships gaps in an ongoing manner to support accurate application health and portfolio views. The underlying CMDB health improvement engendered trust with the data as manifested in application health dashboards, bringing stakeholders together for consensus driven operational decisions.

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