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Cloud services, whether they be infrastructure or software offerings, have become a common part of most company’s IT landscape.  There is no question that cloud services enable users to access powerful functionality without the up-front costs of developing them internally or the ongoing administrative costs to maintain them.  While some of the management burden is transferred out to the cloud service providers, cloud services are still critical components that support your company’s operations and your internal IT staff need to understand the various pieces of the puzzle and how they fit together.

 

Most IT staff who have worked with cloud services for the past year have given up on the notion that they need (or want) full transparency to manage the details at the level that they managed internal systems.  Service providers don’t want to share the information and IT staff are realizing that digging to that level of detail negates the value that they could be receiving by using cloud services.  The consensus opinion regarding cloud services is that consuming organizations need to treat the services as ‘black boxes’ and focus on managing the service interfaces into and out of the boxes and leverage supplier SLAs to influence what happens in the box.

 

Unfortunately, with service providers operating pieces of the system, putting the big picture together can be a difficult chore for your IT staff and developing confidence that the picture is complete and correct can be even tougher.  One of the biggest challenges is reconciling a diverse level of granularity and abstraction across the IT landscape.  Your IT staff may have detailed visibility into the things that they manage directly, but have no visibility to the infrastructure which supports an externally hosted software service.

 

When they try to bring these pieces together (which they need to do frequently for things like security assessments, continuity planning and business process optimization) the pieces don’t often fit together well. To do those things effectively, they need to be able to aggregate configuration and asset information from cloud service providers and other suppliers together and integrate that information with internal perspectives.  This requires them to deal with issues of data accuracy, redundancy, conflicting perspectives across data sources, differences in levels of detail, data captured at different periods of time, and gaps where the needed data isn’t available.

 

The key to resolving the big picture challenge is creating an accurate profile of your different data sources and using them to guide your data integration activities.  This includes understanding what data you have available, how current it is, what perspective it was captured from, how granular of detail is provided, what is missing or abstracted from view, and where it fits in the context of other available data.

 

There is presently no standard across cloud service providers for configuration data, which means that you need to assume that the data from each provider will be unique.   As you combine different data sources, the data received should be validated against what you believe the profile to be, verified for completeness and correctness and then integrated with data collected in the past (already in your CMDB) and any other new data available.  In this integration process, some important things to look for are duplicate data captured from multiple sources, different perspectives on the same piece of data (which can be enlightening to analyze), updates to existing data records, and signs that something has been removed from the environment (this is one of the most overlooked data scenarios but is critically important for managing your IT environment).

 

Many IT service management systems and discovery tools provide capabilities for capturing and importing data as well as performing basic quality checks against individual data streams.  Unfortunately, most of the data aggregation problems occur when multiple data sources are brought together and often ITSM and discovery tools fall short of resolving them.  This is where data quality management capabilities can be helpful – profiling the different data sources and providing a mechanism for scrubbing and cleansing data as it is imported into the CMDB so that the big picture you collect is complete, accurate and trustworthy.

 

Blazent is an industry leader in data quality management for IT asset and configuration data – helping companies effectively bridge the gaps that they encounter working with cloud services, ITSM capabilities and discovery tools.  To learn more, visit www.blazent.com