Your configuration management database (CMDB) is an important resource, but also one of the hardest to maintain. You aren’t alone in this. Most large, enterprise-class organizations are challenged with capturing and maintaining an accurate and complete picture of the assets, software, and configurations which comprise their IT infrastructure. Like any other system, IT Asset Management (ITAM) requires a programmatic approach across people, process, and technology. Even the best ITAM software and most efficient (and documented) processes will fall short if not rigorously and routinely used by the individuals responsible.
What Might You Look For in an Automated Discovery Tool?
If you were to ask a room full of IT leaders from multiple industries and various sizes, “How confident are you in the accuracy of your IT asset inventory?” you will likely see more than a few sheepish smiles and chuckles. The reality is that capturing and maintaining accuracy and completeness is difficult. Organically over time, accuracy and completeness tend to diminish due to a lack of governance and not utilizing auto-discovery.
While some organizations may claim that their IT infrastructure is stable and consistent, the constant changes acting upon the organization force rapid changes; both from within the organization (e.g. merger or acquisition, tech refresh, movement to cloud) and from outside (e.g. PCI and/or HIPAA compliance).
Further complicating ITAM is that the information or data elements needed for each asset will change, depending upon its current use/purpose and your organization’s future initiatives or projects. For example, if an organization needs an accurate inventory in order to ensure that all key IT assets are under an appropriate maintenance coverage plan, the information and data elements needed in the ITAM repository are relatively straight-forward (make, model, serial number, rack location, etc.).
Contrast that situation with the organization who has recently merged with another and has initiated a data center consolidation project. In that case, the information and data elements needed from the ITAM repository go far beyond basic information. Now application interdependencies, communication flows/protocols, and recovery objectives become crucial elements of the ITAM repository.
CMDB Accuracy Metrics
So, how can you restore and maintain your CMDB accuracy and completeness? Our experience has shown that two concurrent approaches have proven effective: The use of discovery software (to automate the scanning of your environment), combined with manual information gathering will enable an organization to ‘get a handle’ on their IT infrastructure. However, this should not be a “one and done” approach. The best accuracy results from routinely executing scans and rigorously reviewing and augmenting the data captured.
The following are key features you should consider:
- No impact on network or device performance
- Automatic application dependency and web service topology mapping
- Device relationship and communications
- Built-in CMDB and ITAM solutions
- Agentless network discovery via WMI, SSH, SNMO, port scan, custom probes
- Perform deep scans of physical and virtual installs of Windows, Unix, Linux, and mac for hardware configurations, software, patches, processes, services and more
- Various levels of discovery based on needs
Another key capability to look for is the ability to easily integrate with your existing CMDB.
IT Discovery Tool Limitations
So why would any manual effort be needed if the tool can do it?
The reality is that certain information or data elements that need to be part of your IT asset repository are simply not “discoverable” by any tool, regardless of how effective it is. Take the very simple data element of ‘asset ownership’. Is your asset owned or leased? And if leased, who is the leasing company? What is the monthly lease amount? And when does the lease expire? The software probing your network will not have access to this information – and yet these are key data elements that you would need in your asset management repository.
Here’s another example. If you were planning a data center migration or consolidation, how would you capture key information that likely resides as intellectual capital held in the mind(s) of your IT and application teams? What is the Recovery Time Objective (RTO) and Recovery Point Objective (RPO) for an application, what are the applications dependencies when migrating from one data center to another?
Manual data gathering is the means to capture these data elements or information. And there are a variety of techniques that can be employed. Techniques such as group interviews, online surveys, or system-to-system data mapping are used to validate auto-discovered data and rationalize any missing pieces.
As mentioned previously, an organization’s current strategy and IT initiatives will drive the level of discovery required. Below are three levels of discovery and the typical Use Cases addressed:
A basic auto-discovery captures the physical and virtual assets deployed in your data center(s), and generates an inventory list that can be imported into a CMDB or used for other purposes.
- Upcoming hardware maintenance renewal
- Seed a CMDB
- Compliance audit
- Merger & Asquisition (M&A) planning
- Technology refresh
- Software licensing
Basic discovery plus auto-discover applications and services running in your environment, with visual dependency maps, communication flows, and business service maps.
- Implement or improve change management
- Infrastructure optimization planning
- Develop a cloud strategy
- M&A integration planning
Goes a layer deeper to verify auto-discovered data and manually capture key data from application owners and IT resources, such as RTO/RPO, maintenance windows, DR testing, maintenance contracts, licensing, etc.
- Digital transformation
- Data center migration/consolidation
- Cloud migrations
- Implement an ITAM solution
- Disaster Recovery strategy & planning
- Optimize support contracts & licensing
What benefits can you expect from instituting a routine ‘discovery’ of your IT infrastructure?
- Improves the accuracy and completeness of your existing inventory or Asset Management system-of-record (e.g. CMDB).
- Establishes a baseline of your infrastructure via auto-discovery, including hybrid and public cloud ecosystems. This enables better planning and optimization of your IT infrastructure.
- Enhances security by identifying potential risks to your environment. You can’t protect what you don’t know.
- Provides automated service maps enabling visual insight into complex relationships and dependencies through machine learning and social discovery. This will help to identify impacts to changes or outages in your ecosystem.
- Enables better business decisions via real-time and accurate data.
What are some of the ways in which you have addressed the challenge of maintaining the accuracy and completeness of your IT asset management repository? Let’s start a conversation.