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The CMDB of the Future - Part 1

The Challenge of the Conventional CMDB

The complex software applications that run modern businesses are often referred to as "mission-critical" and must be kept running 24x7. Unfortunately, the complexity of these applications is often so great that keeping them in a healthy state can be challenging, to say the least.

The Configuration Management Database, or CMDB, was conceived a few years back as a way to discover and maintain a repository of all components on which an application is dependent, along with information about their relationships. Apart from its use in asset management, the thought was that combining the CMDB with real-time monitoring metrics obtained from the underlying components could provide insight into the health state of complex applications, with early warning of incipient problems, and guidance to root cause when incidents do occur.

This is a powerful vision with potentially far-reaching benefits. It is a bit like the internal monitoring system in a modern automobile which relies on a complete and well-defined database of all the components on which the vehicle's operation is dependent and how a failure of any one component might affect the mission-critical operation of the vehicle. A soft female voice might warn you, for example, that your tire pressure is low — and she didn't have to "learn" that low tire pressure can cause a blowout by having one first.

Similarly, today's large, complex, mission-critical business applications can have a huge number of moving parts and underlying software components — with lots of things that can go wrong.

Is it possible to identify and maintain a database of all the internal dependencies of a complex application and create a warning system like that in a modern automobile that is highly deterministic and reliable and can prevent incidents from ever happening in the first place?

Sounds like a really great idea. Why then, has the CMDB seen only limited adoption and little commercial success?

Weaknesses of Conventional Configuration Management Tools

We have seen many products in recent years designed to create and maintain such a Configuration Management Database. However, practical challenges have prevented this vision from becoming reality, and the CMDB seems to have lost favor as a realistic contributor to a monitoring solution.

While successful to some extent, the general consensus seems to be that these products have been simply too limited in functionality or too difficult to use for maintaining reliable content. For some detailed criticism, see "IT Skeptic" Rob England's blog: CMDB: What Does It Really Mean?.

Monitoring a complex multi-tiered application involves the collection of data from many different sources, including infrastructure data (host cpu and memory), middleware service data (message flows, session counts), and application data like log file content or data exposed through JMX. Typically, this can include a dozen or more specific types of data for any platform you build.

Using a traditional CMDB or service model a user would either:

1. manually define the dependency relationships between these components and each application that uses them, or

2. use a tool to auto-discover the relationships using some form of heuristic algorithm.

Both of these methods have serious drawbacks. It is impractical to manually maintain a service model when components are continually being added or the system is modified. The heuristic method seems promising but the drawbacks are just as severe although more subtle; minor flaws and inaccuracies constantly plague the system and can cause mysterious errors that go undetected for a long time.

Automobile manufacturers gradually figured out how to manage the information needed to effectively maintain the health and safety of a moving vehicle. In a similar way, developers of complex applications are slowly discovering ways to make monitoring these systems more automatic and reliable. Fundamental changes in the IT landscape are helping as well.

The CMDB of the Future - Part 2

ABOUT Tom Lubinski

Tom Lubinski is President and CEO, and Board Chairman, of SL Corporation, which he founded in 1983.

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The CMDB of the Future - Part 1

The Challenge of the Conventional CMDB

The complex software applications that run modern businesses are often referred to as "mission-critical" and must be kept running 24x7. Unfortunately, the complexity of these applications is often so great that keeping them in a healthy state can be challenging, to say the least.

The Configuration Management Database, or CMDB, was conceived a few years back as a way to discover and maintain a repository of all components on which an application is dependent, along with information about their relationships. Apart from its use in asset management, the thought was that combining the CMDB with real-time monitoring metrics obtained from the underlying components could provide insight into the health state of complex applications, with early warning of incipient problems, and guidance to root cause when incidents do occur.

This is a powerful vision with potentially far-reaching benefits. It is a bit like the internal monitoring system in a modern automobile which relies on a complete and well-defined database of all the components on which the vehicle's operation is dependent and how a failure of any one component might affect the mission-critical operation of the vehicle. A soft female voice might warn you, for example, that your tire pressure is low — and she didn't have to "learn" that low tire pressure can cause a blowout by having one first.

Similarly, today's large, complex, mission-critical business applications can have a huge number of moving parts and underlying software components — with lots of things that can go wrong.

Is it possible to identify and maintain a database of all the internal dependencies of a complex application and create a warning system like that in a modern automobile that is highly deterministic and reliable and can prevent incidents from ever happening in the first place?

Sounds like a really great idea. Why then, has the CMDB seen only limited adoption and little commercial success?

Weaknesses of Conventional Configuration Management Tools

We have seen many products in recent years designed to create and maintain such a Configuration Management Database. However, practical challenges have prevented this vision from becoming reality, and the CMDB seems to have lost favor as a realistic contributor to a monitoring solution.

While successful to some extent, the general consensus seems to be that these products have been simply too limited in functionality or too difficult to use for maintaining reliable content. For some detailed criticism, see "IT Skeptic" Rob England's blog: CMDB: What Does It Really Mean?.

Monitoring a complex multi-tiered application involves the collection of data from many different sources, including infrastructure data (host cpu and memory), middleware service data (message flows, session counts), and application data like log file content or data exposed through JMX. Typically, this can include a dozen or more specific types of data for any platform you build.

Using a traditional CMDB or service model a user would either:

1. manually define the dependency relationships between these components and each application that uses them, or

2. use a tool to auto-discover the relationships using some form of heuristic algorithm.

Both of these methods have serious drawbacks. It is impractical to manually maintain a service model when components are continually being added or the system is modified. The heuristic method seems promising but the drawbacks are just as severe although more subtle; minor flaws and inaccuracies constantly plague the system and can cause mysterious errors that go undetected for a long time.

Automobile manufacturers gradually figured out how to manage the information needed to effectively maintain the health and safety of a moving vehicle. In a similar way, developers of complex applications are slowly discovering ways to make monitoring these systems more automatic and reliable. Fundamental changes in the IT landscape are helping as well.

The CMDB of the Future - Part 2

ABOUT Tom Lubinski

Tom Lubinski is President and CEO, and Board Chairman, of SL Corporation, which he founded in 1983.

Hot Topics

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...