How IT monitoring integration strategy impacts the business

Survey of 400+ IT pros

Executive summary

In June 2018, Blue Medora partnered with the VMware User Group (VMUG) to survey more than 400 of the group’s members about the current and near-future state of monitoring integration in their environment.

Central to the research was an in-depth exploration of Dimensional Data (as defined on page 3). Specifically, the research looked to confirm if the increased access, data depth and context provided by a Dimensional Data stream positively impacted IT outcomes.

Dimensional data is…

Dimensional data refers to a real-time metric stream provided by a monitoring integration as a service (MIaaS).

A Dimensional Data stream will include highly granular behavioral detail — beyond what a single endpoint API connection might include — as well as rich relational context.

  1. Universal data language
    Eliminate data silos with multi-platform access to all metrics in your environment.
  2. Internal relationship links
    Make better decisions with richer visualizations, improved metric depth.
  3. External relationship metadata
    Separate root cause from symptoms quickly using full-stack context.
  4. Super metrics
    Understand actual health more quickly with calculated ratios and rates.
Key findings

Adoption
Nearly 9% of organizations currently have access to Dimensional Data across the majority of their integrations.

Demand
On average 43% of organizations without a specific dimension of data wish to adopt within the next 18 months.

Impact
Nearly 40% of the top performers in utilization and productivity gains had fully deployed dimensional data

Cost savings
Those who fully deployed Dimensional Data: 1 in 5 saw more than $1m/year savings, 1 in 2 saw more than $100k/year savings

Part I

Dimensional Data adoption

3 in 4 have significant gaps in data depth

Q.

Please estimate how many of your current monitoring integrations include visibility into the individual endpoint components so you can drill down into a specific component, such as a PostgreSQL database instance, node or query.

70% say most integrations not multi-platform

Q.

Please estimate how many of your current monitoring integrations can be leveraged by multiple monitoring platforms within your environment without customization.

2 in 3 lack relational visibility in most integrations

Q.

Please estimate how many of your current monitoring integrations include the context you need to understand relationships between a specific endpoint technology and all other technologies in your stack. (Ex. application, database, VM, host and LUN)

75% lack super metrics in most integrations

Q.

Please estimate how many of your current monitoring integrations include synthetic metrics, known as super metrics. These calculated metrics combine multiple raw metrics to calculate rates or ratios that have more meaning. (Ex. average database execution time)

Only 9% “fully deployed”

The deployed percentage was calculated based on responses to the 4 previous questions (depth, multi-platform, relational visibility, super metrics).

Part II

Dimensional Data impact

Half of top downtime performers at least 75% deployed

Q.

Please estimate how much downtime your monitoring integrations prevent in a given year?

50% of top troubleshooters at least 75% deployed

Q.

Please estimate how much your monitoring integrations enables faster troubleshooting in your environment?

Dimensional data doesn’t impact SLAs

Q.

Please estimate often your team is able to meet or exceed SLAs?

37% of top utilization performers fully deployed

Q.

Please estimate how much your current monitoring integrations help you improve resource utilization?

40% of top productivity performers fully deployed

Q.

Please estimate how much your monitoring integrations improve your team’s productivity (i.e. better collaboration, faster troubleshooting, shared visibility)?

1 in 5 fully deployed saw +$1m savings/year

50% of fully deployed save more than 100k/year

Q.

Please estimate how much cost savings can be attributed to monitoring integrations in your environment (combined value of increased utilization, better capacity planning, reduced downtime, etc.)?

52% of top overall performers 75%+ deployed

Overall score calculated based on the 6 “results” questions (downtime, troubleshoot, SLA, utilization, productivity, cost savings).

Part III

Methodology and participants

Goal

To measure how various monitoring integration strategies and Dimensional Data access may or may not impact IT results.

Method

All VMUG members were invited to take the online survey via email. Participants were not compensated for their time.

Participants

410 respondents with IT responsibilities at organizations with 500+ employees.

60% run 3+ monitoring platforms

Top job roles: 76% at the admin/architect role

Top industries

Q.

Please select your organization’s industry.

Wide variety of monitoring tools in the mix

Q.

Which monitoring tools are currently in use in your environment?

Half plan to consolidate monitoring tools

50% Plan to consolidate monitoring tools

Part IV

Conclusion and resources

Conclusion

Your monitoring integration strategy matters more than you might think

Most monitoring research focuses on the efficacy of monitoring platforms or analytics engines, but doesn’t spend a good deal of time looking at the data that goes into them. This research supports the idea that universal access to a Dimensional Data stream or other integration strategy that includes metric breadth, depth and context will likely have a positive impact on key business measures like IT productivity, utilization, cost savings and downtime.

Resources

“Dimensional Data: Making the Leap from Monitoring to Observing”
The New Stack article
http://bit.ly/2OGAaid

“Maximize your current monitoring using new Data Collection Methods”
Blue Medora white paper
http://bit.ly/2Bjfpre

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