In a recent webinar AIOps and IT Analytics at the Crossroads, I was asked several times about the borderline between AIOps and monitoring tools — most particularly application performance monitoring (APM) capabilities. The general direction of the questions was — how are they different? Do you need AIOps if you have APM already? Why should I invest in both?
Surrounding these questions were problems inherent in the acronyms themselves, each of which had become its own internal battle ground due to warring marketing campaigns, media hype and sheer technical complexity. So I'd like to start off by highlighting a few fundamental design-point differences.
APM in its roots remains primarily monitoring, even if it includes some predictive capabilities, and moreover it's focused primarily on application performance (as per the name) including some application/infrastructure interdependencies. And while the boundaries do become somewhat blurred as APM vendors increasingly embrace machine learning and analytic capabilities, in the broader scheme, APM tools, given their domain-specific focus, can become critical sources for more far-reaching AIOps platforms.
AIOps solutions are fundamentally platform investments that cross all layers of the seven-layer stack. As a term, AIOps aligns most closely to EMA's definition of advanced IT analytics (AIA), which shows a growing breadth of data sources (in the research mentioned above the average was more than 12, in which transaction data competed with IoT data, configuration data, log file access and even spreadsheets for first place).
Moreover, AIOps/AIA solutions typically leverage as many as 13 different analytic heuristics, from big data search, to predictive, prescriptive and if/then flavors of machine learning. And perhaps even more striking, our research showed that currently deployed AIOps platforms are expected to assimilate an average of 23 different monitoring and other tools, with a significant percentage indicating more than 50. And most importantly, AIOps/AIA solutions can go far beyond performance management to support change, capacity, security or SecOps, cost optimization, and cloud migration needs, along with DevOps and end user experience analytics.
So the basic takeaway here is that AIOps is a unifying technology that embraces APM, network management, systems management, database management and cloud across multiple use cases by assimilating and proactively analyzing data from a wide variety of sources. It is broader in scope, use case, and value than APM, and more intrinsically aligned with advanced levels of automation.
A Few Similarities
But I would be doing APM a disservice if I were to dismiss it as just another category of monitoring tool. And in fact, APM evolution did help to contribute significantly to the birth of meaningful AIOps capabilities. For this I would highlight the following four areas:
■ APM grew in stature in reference to how it managed applications in context with their infrastructure interdependencies — hence it became a top-down venue for assessing effective service management and service delivery.
■ As such many APM solutions evolved far more dynamic capabilities for discovering and modeling application/infrastructure interdependencies, application discovery and dependency mapping (ADDM), which have become foundational for many AIOps solutions, either through direct integrations, or through their own discovery capabilities.
■ APM has begun to put a growing focus on end-user experience management (EUEM), which has become a growing source of relevance to AIOps solutions seeking to align with business value.
■ And many APM solutions have aggressively sought to embrace business performance metrics which are similarly a growing area of AIOps investment. However, here it should be pointed out that AIOps platforms have a potentially more versatile foundation for assessing business value that can more address capacity, costs, security/compliance concerns and other metrics.
How AIOps Investments can Unify IT
AIOps is a unifying technology and hence a platform for change across potentially all of the IT organization, not just operations (despite its name). Our research, both this year and last year showed dramatic values in AIOps for toolset consolidation across virtually every silo. Moreover, IT service management (ITSM) integrations remain paramount, along with growing opportunities for helping development, security teams, and operations, to work more effectively together.
AIOps Investments can Unify IT only if they're properly understood
However, it might be more accurate to state that AIOps Investments can Unify IT only if they're properly understood. To leverage the full value of a truly unifying platform investment requires leadership, creativity and flexibility in how the IT thinks and works. In parallel with CMDB/CMS initiatives, which are not surprisingly seeing a resurgence in context with AIOps deployments among other things, AIA/AIOps initiatives require a willingness to share data and explore new levels of process efficiencies, with heightened levels of automation. Moreover, AIOps opens the door to exploring problems freshly, with more cohesiveness and a far more proactive mindset than in the past. Best practices still apply here (the jury's still out about which is most directly applicable), as does alignment with digital transformation initiatives that give added weight and value to transforming IT.
But the time is nigh. Once too good to be true, AIOps technologies are evolving so that third-party solutions are well worth the investment. And despite the AIOps name, you should recognize the investment as a foundation to galvanize potentially all of IT. AIOps/AIA is in my view less a market (it is too diverse in design and value currently) and more a landscape of innovation. So selecting the right solution for your priorities will require a clearly defined set of priorities for use case, stakeholders and need, as you build toward increasing value.
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