Gartner Kills Business Service Management

In a research note dated February 20 2017, titled “BSM Is Dead; Use Other ITOM Tools to Convey Value and Manage Operations”, Gartner put the BSM category of management and monitoring tools out of its misery.

Summary of the Gartner BSM Note

The summary of the Gartner note that killed BSM is in the image below.

The key takeaways are:

  • Business Service Management and Monitoring tools have failed to deliver on their promised value to customers
  • Leading Infrastructure and Operations organizations should use best-of-breed approaches incorporating BVD (Business Value Dashboards), ITOA (IT Operations Analytics), APM (Application Performance Management), and NPMD (Network Performance Management and Diagnostics).

Exactly What Products Did Gartner Kill?

Gartner did not specify which vendors and products are covered by its death sentence, so we will fill in that gap for you. BSM (Business Service Management) was a term invented by IBM, BMC, HP and CA to cover their suites of monitoring tools that collectively were supposed to allow one vendor to monitor everything in the enterprise and allow enterprises to ensure that everything was working properly and performing properly.

So the products that this pertains to would include:

  • The IBM Tivoli, Netcool, and Omnibus lines of products
  • The BMC Patrol, Event Management, and Remedy lines of products
  • The CA Unicenter and Spectrum products
  • The HP line of Operations Management and Applications Performance Management products

Why Did These Legacy Solutions Die?

These solutions died (in our opinion) because they made an unkeepable promise. That promise was that one vendor could keep up with the pace of innovation in the entire IT industry and provide a comprehensive solution that covered the entire waterfront. This was a difficult promise to keep when these solutions were first launched 20 years ago and it has become an impossible promise to keep now that the pace of innovation keeps accelerating.

As these solutions died the vendors became Blind Dinosaurs. Blind in the sense that they did not have the vision and the financing to keep their products current. And Dinosaurs in the sense that these products became painfully expensive things for customers to own – turning them into legacy solutions that most customers would very much like to get rid of. Our Blind Dinosaur graphic is below.

The Blind Dinosaurs

What Replaces the Legacy Business Service Management Tools?

Gartner advises its clients to replace these legacy Business Service Management Tools with best of breed solutions from a variety of categories of tools:

  • BVD’s (Business Value Dashboards) – this is a brand new category of tools, focused upon allowing enterprises to combine IT data (metrics) with business data in a way that is relevant and valuable to the business. This category is so new that Gartner has not produced a Magic Quadrant for it yet, so we do not yet know who Gartner considers to be the leading vendors in this space.
  • ITOA (IT Operations Analytics) – Gartner also calls this category Algorithmic IT Operation (AIOps). This is also such a new category that Gartner has not yet produced a Magic Quadrant listing and ranking the vendors in the space.
  • APM (Application Performance Management) – this category and associated Magic Quadrant have been around for years but has seen a complete turnover in leadership. The legacy vendors used to lead this category, but it is now lead by AppDynamics, Dynatrace and New Relic.
  • NPMD (Network Performance Management and Diagnostics) – this category is lead by NetScout, Viavi, and Riverbed, with ExtraHop scoring points for having the strongest vision in the space.

The Result of a Best-of-Breed Strategy

The single thing that we are best at in the IT industry is solving one problem, only to create a new problem in the process. So it is with a best-of-breed strategy for monitoring. For as soon as you implement a best of breed approach, which for most enterprises requires at least 10 or 20 different tools, you have a Franken-Monitor. That means that your monitoring data is now spread out into 10 or 20 different databases, and you have no way to analyze these disparate sources of data in a related manner. The resulting Franken-Monitor is shown below.

The Franken-Monitor

Data-Driven IT Operations – The Solution to the Franken-Monitor

IT has built data lakes for the business, allowing business analysts to use data to drive better business decisions. To solve the problem of the Franken-Monitor, IT needs to embrace the idea of Data Driven IT Operations – meaning to use data and the analysis of data to improve the performance, effectiveness and cost profile of IT in support of critical business services. The OpsDataStore architecture for Data Driven IT Operations is shown below – with OpsDataStore as the common big data back end for all IT Operations and Applications data.

The OpsDataStore Architecture for Data Driven IT Operations

The OpsDataStore Difference

The idea of combining disparate sources of data in IT is not new. Splunk and other log stores have been doing this for years. But the problem with logs is that they have a time stamp and then some text and are inherently unstructured. That means that by definition a log store has to be “a stupid log store” because the store cannot assume anything about the contents of the logs as they are ingested.

The world of IT data (metrics) is entirely different. Metrics are associated with objects (transactions, applications, virtual servers, physical servers, and datastores), and objects have relationships between them. Transactions and applications run on virtual servers, which in turn run on physical servers, and use datastores. What is unique about OpsDataStore is that not only do we consume the metrics from a variety of disparate tools, we capture the relationships between them at ingest time. An example of such a topology map is shown below.

OpsDataStore Topology Map

Knowing which objects are related to each other (Transaction–>Application–>Virtual Server–>Physical Server–>Datastore) is a huge step forward but it is not enough. What is required is to be able to analyze the metrics from these related objects in the context of each other.

For example, you can see how the latency of a set of datastores is affecting the response times of the transactions running on those datastores.

Related Metrics in OpsDataStore

Knowing what metrics are related to each other makes it possible to do Deterministic Root Cause. This means using relationships that are factually correct between things like transactions and their supporting infrastructure to do root cause. An example of this is shown below.

Deterministic Root Cause in OpsDataStore

Finally we can drill down to see how the behavior of individual elements of infrastructure like servers or datastores are affecting critical business transactions. Below is an example of how CPU Ready, a measure of CPU contention on a set of VMware hosts is affecting the performance (response time) of a set of critical business transactions.

Root Cause Drill Down in OpsDataStore

The OpsDataStore Product

How do we do all of this? The answer is that we have a multi-vendor big data platform fed by market leading partner vendors (AppDynamics, Dynatrace, ExtraHop, VMware and Intel). We ingest data from our partners every minute, calculate the relationships between their objects on a continuous basis, and store the resulting metrics, aggregates and relationships in a RAM based analytical datastore that supports queries from any commercial tool on the market. We build our own dashboards in Tableau a market leading BI tool.

The OpsDataStore Product Architecture

Benefits of OpsDataStore

OpsDataStore’s real time big data approach combined with a best of breed ecosystem of partnering tool vendors delivers the following benefits:

  • Play Offense – use the analytics in OpsDataStore to prevent problems that disrupt critical business transactions
  • Solve Problems More Quickly – use the analytics in OpsDataStore to quickly solve problems that span your entire stack from your transactions through to your infrastructure.
  • Optimize Density and Save Money – with the OpsDataStore set of related metrics you can easily boost the density of your virtualized environment while protecting the response time and throughput of your critical business transactions.
  • See Your Data Your Way (Business Value Dashboards) – use our Tableau workbooks or build your own visualizations in the tool of your choice.


Gartner has pronounced the legacy Business Service Management products from the legacy monitoring vendors (IBM, BMC, HP and CA) to be dead. Gartner recommends replacing these legacy solutions with a best of breed approach. This results in tool proliferation and data proliferation which makes it hard to provide quality services in a cost efficient manner. OpsDataStore uniquely solves this problem by combining a best of breed ecosystem with a real time big data and relationship platform.