How to Evaluate CMDB Tools When Integrating Automation Platforms
Your configuration management database (CMDB) is the “central warehouse” for your company’s entire IT infrastructure. It’s the single source of truth (SSoT) that tracks your valuable IT assets, namely, servers, databases, and network routers. It also visualizes how these assets connect and depend on one another to function.
When your IT team connects the CMDB to an enterprise automation platform, they must have an acute understanding of how data flows between both systems, making Application Programming Interface (API) exposure critical. This article outlines strategies for evaluating Cloudaware’s CMDB products based on API exposure (accessibility) and data reconciliation features.
Evaluating API Performance
Think of an API as a bridge that enables communication between the CMDB and an automation platform. While Cloudaware’s CMDB products can help streamline a successful integration, it’s important to know how to evaluate these products across various parameters, starting with the API architecture itself.
These types of products require standard RESTful and GraphQL APIs. For instance, GraphQL limits automation platforms to requesting only the specific attributes it needs, which saves network bandwidth from over-fetching requests.
Your CMDB tools need high rate limits to accommodate high-volume automation workflows. Restrictive limits can literally stop critical projects in their tracks.
If your company utilizes bulk hardware (or endpoints), your CMDB API must be able to support an automation platform’s ability to fetch, synthesize, and update large datasets within a single request. Once an asset record is updated, Cloudaware’s CMDB tools use webhooks to push immediate notifications to dashboards.
Data Reconciliation
CMDB tools and automation platforms often store different asset records for the same hardware or virtual asset. Your CMDB must be able to reconcile this data by matching, combining, and cleaning asset records.
IT teams can verify data reconciliation features by checking if the CMDB can determine if an incoming asset already exists.
CMDBs manage asset inventories with primary identifiers, such as serial numbers, Universally Unique Identifiers (UUIDs), Media Access Control (MAC) Addresses, which are physical manufacturer codes for devices, and hostnames, the network labels given to connected devices. Checking these variables prevents duplicate asset record entries.
Built-in data normalization tools optimize Cloudaware’s CMDB data cleaning processes further by organizing data into standardized formats. For example, if an automation platform script reports an operating system (OS) as RHEL 8 while another reports it as “Red Hat Enterprise Linux 8,” the CMDB will standardize the OS field into a uniform format.
Any lingering data mismatches should be automatically logged by the CMDB, overwritten in the system, or trigger alerts to team members with proper user permissions.
IT teams should also check for data reconciliation priority, which allows for more advanced field-level data authority in CMDBs. A project leader can configure the CMDB to accept IP address details from a specific cloud orchestration tool or allow a specific procurement database to access asset cost records.
IT Infrastructure and Context
IT infrastructure components depend on each other to work properly. This leads to the next role of a CMDB: maintaining structural context. This is important for API exposure, which refers to the accessibility level of an API when sharing data with stakeholders and software.
To maintain quick automation workflows, IT teams must verify if an automation platform has instant API visibility should a server ever fail. This is crucial for preventing operational disruption and application crashes.
If an automation platform is configured to set up a new virtual machine or network, the connected CMDB should be able to map the new components and update the infrastructure without manual intervention.
Plan Your Automation Layer Integration
Ensure your CMDB is equipped to bring an automation platform into your IT infrastructure. IT teams should test API performance across multiple parameters, check for data reconciliation and normalization features, and confirm AI exposure.
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