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Making the Right Application Discovery and Dependency Mapping (ADDM) Investment

Dennis Drogseth

This is the second in a series taken from Chapters Three, Twelve, and Appendix B in CMDB Systems: Making Change Work in the Age of Cloud and Agile. It is not meant as a substitute in any way for the book, but should provide you with a good beginning point for thinking about the technology selection process. Our first blog was on core CMDB selection.

The Application Discovery and Dependency Mapping (ADDM) market is evolving rapidly, and in multiple directions at once. While this can be confusing, it is overall a good thing. Through this diversity, vendors delivering ADDM capabilities are, as an aggregate, seeking to be more responsive to a yet broader set of constituents, use cases, and roles than ever before. This includes requirements emerging from internal and external (public) cloud, the extended enterprise across ecosystems, agile application development, and a dramatic upswing in currency, ease of deployment and modularity.

In some cases you will want to be sure to select an ADDM package that integrates with your core CMDB at initial deployment. In other cases it may come at a later time as a separate investment. On the other hand, depending on use case and overall readiness, an ADDM package may be the right starting point for growing your CMDB System in Phase One even without a core CMDB.

Multi-Use Case versus Performance-Optimized

Image removed.Probably the first place to start in evaluating the ADDM opportunity is to group vendor solutions into two general categories: multi-use-case and performance-optimized. While there has been some blending, each group is optimized for distinct values.

Multi-Use Case: ADDM first became an area of intense innovation roughly 10 years ago with the initial tidal wave of interest in CMDB deployments and the need to capture service-related interdependencies more effectively. Subsequently, that first crop of companies was largely acquired by leading platform solutions with native CMDB integrations. As a group, these ADDM pioneers were and still are focused on capturing configuration-related changes as well as application-to-infrastructure residency, with use cases targeted at asset and change management.

Performance-optimized ADDM: About five years ago, the industry began to see a new crop of ADDM solutions more focused on performance interdependencies, transactional awareness, and more real-time dynamic currency. Many of these also supported CMDB integrations; all were highly automated and, to some degree, were complementary to ADDM-related investments from the first wave. Vendors in this category are raising the bar on in-depth transactional awareness; dynamic, operational insights into application-to-application and application-to-infrastructure interdependencies; and higher levels of automation in terms of discovery and currency.

As the ADDM market progresses, both groups are beginning to harvest strengths from each other, and in this respect, they are becoming more alike. On the other hand, at least for the foreseeable future, there will be numerous situations where a complementary relationship between two separate ADDM packages may well be the right choice.

Read: 6 Key Points of ADDM Evaluation

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Making the Right Application Discovery and Dependency Mapping (ADDM) Investment

Dennis Drogseth

This is the second in a series taken from Chapters Three, Twelve, and Appendix B in CMDB Systems: Making Change Work in the Age of Cloud and Agile. It is not meant as a substitute in any way for the book, but should provide you with a good beginning point for thinking about the technology selection process. Our first blog was on core CMDB selection.

The Application Discovery and Dependency Mapping (ADDM) market is evolving rapidly, and in multiple directions at once. While this can be confusing, it is overall a good thing. Through this diversity, vendors delivering ADDM capabilities are, as an aggregate, seeking to be more responsive to a yet broader set of constituents, use cases, and roles than ever before. This includes requirements emerging from internal and external (public) cloud, the extended enterprise across ecosystems, agile application development, and a dramatic upswing in currency, ease of deployment and modularity.

In some cases you will want to be sure to select an ADDM package that integrates with your core CMDB at initial deployment. In other cases it may come at a later time as a separate investment. On the other hand, depending on use case and overall readiness, an ADDM package may be the right starting point for growing your CMDB System in Phase One even without a core CMDB.

Multi-Use Case versus Performance-Optimized

Image removed.Probably the first place to start in evaluating the ADDM opportunity is to group vendor solutions into two general categories: multi-use-case and performance-optimized. While there has been some blending, each group is optimized for distinct values.

Multi-Use Case: ADDM first became an area of intense innovation roughly 10 years ago with the initial tidal wave of interest in CMDB deployments and the need to capture service-related interdependencies more effectively. Subsequently, that first crop of companies was largely acquired by leading platform solutions with native CMDB integrations. As a group, these ADDM pioneers were and still are focused on capturing configuration-related changes as well as application-to-infrastructure residency, with use cases targeted at asset and change management.

Performance-optimized ADDM: About five years ago, the industry began to see a new crop of ADDM solutions more focused on performance interdependencies, transactional awareness, and more real-time dynamic currency. Many of these also supported CMDB integrations; all were highly automated and, to some degree, were complementary to ADDM-related investments from the first wave. Vendors in this category are raising the bar on in-depth transactional awareness; dynamic, operational insights into application-to-application and application-to-infrastructure interdependencies; and higher levels of automation in terms of discovery and currency.

As the ADDM market progresses, both groups are beginning to harvest strengths from each other, and in this respect, they are becoming more alike. On the other hand, at least for the foreseeable future, there will be numerous situations where a complementary relationship between two separate ADDM packages may well be the right choice.

Read: 6 Key Points of ADDM Evaluation

Hot Topics

The Latest

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 ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...