Blue Medora’s VMware User Group Survey Studies the Impact of Monitoring Integration Strategy on Business
GRAND RAPIDS, MICH. – August 23, 2018 – In a June 2018 survey of over 400 IT professionals, Blue Medora took a closer look at how various metric collection strategies and access to Dimensional Data impacts IT success.
The research wanted to test if increased access, data depth and context provided by a Dimensional Data stream positively impacted IT outcomes. 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.
The big takeaway – many organizations are running multiple monitoring tools in an effort to get the appropriate data depth and context they need across their entire IT stack. Sixty percent of respondents are already running three or more monitoring systems. But despite that, two-thirds of IT ops teams still lack visibility into the external resource relationships and three-quarters lack access component-level data resolution, resulting in more downtime than peers using monitoring integrations that provide this critical capability.
While VMware vRealize was the most common monitoring platform at 60%, other popular platforms were SolarWinds (44%), Microsoft SCOM (40%), Splunk (35%), Nagios (34%) and Microsoft Azure Manager (20%).
Seventy percent of respondents said most of their monitoring integrations were not compatible with more than one monitoring platform, a leading cause of metric silos in many organizations.
Only 9% of organizations have access to Dimensional Data across the majority of their integrations and are considered fully deployed. On average, 43% of organizations wish to increase Dimensional Data adoption within the next 18 months.
Nearly 40% of the top performers in utilization and productivity gains had fully deployed Dimensional Data.
Of those who fully deployed Dimensional Data, one in five saw more than $1m a year in savings and one in two saw more than $100k in savings.
“Most monitoring research focuses on the efficacy of monitoring platforms or analytics engines but doesn’t spend a great deal of time looking at the data that goes into them,” explained Christian Fernando, chief products officer, Blue Medora. “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 context on key business measures like IT productivity, utilization, cost savings and downtime.”
Blue Medora partnered with the VMware User Group (VMUG) to survey 410 of the group’s members about the current and near-future state of monitoring integration in their environment. All had IT responsibilities at organizations with over 500 employees. 76% of respondents held an admin or architect role within the IT organization.
To learn more about Blue Medora’s multi-platform monitoring service, visit our blog.
Blue Medora’s mission is to advance delivering IT monitoring integration as a service. Since its founding, Blue Medora has innovated deep performance inspection capabilities across disparate enterprise technologies, at tremendous scale and quality. BindPlane now supports 146 distinct technologies, enhancing the monitoring and analytics engines of VMware, New Relic, Microsoft and others. Blue Medora’s unique “Dimensional Data” approach to the monitoring integration challenge is designed for customers seeking best of breed telemetry and management across multiple IT teams and operating across hybrid/heterogeneous environments.
About Blue Medora
Blue Medora’s pioneering IT monitoring integration as a service addresses today’s IT challenges by easily connecting system health and performance data–no matter its source–with the world’s leading monitoring and analytics platforms. Blue Medora helps customers unlock dimensional data across their IT stack, otherwise hidden by traditional approaches to metrics collection.
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