The results of the APMdigest Big Data survey, sponsored by Netuitive, have shown significant increases in the growth of IT environments, volume and diversity of performance metrics, and data monitoring frequency – all factors driving Big Data in APM.
Click here to read: 3 Factors Driving the APM-Generated Big Data Boom
The explosion in Big Data proves that most organizations have the monitoring part down. The challenge is what to do with all the data, once collected. How can you correlate and analyze Big Data, and make some sense out of it? This is the key to the future of APM.
According to the survey, 9 out of 10 companies are only able to analyze less than half the metric data they collect. In fact, 45% analyze less than a quarter of the data, and no companies at all claimed to analyze more than 75% of APM data.
Breaking Down the Silos
One of the greatest barriers to analysis of APM data are the monitoring silos which keep information in disparate systems. More than three quarters (77%) of survey respondents said they are not satisfied or unsure about their cross-silo analytics capabilities to correlate business, customer experience and IT metrics.
Larger companies, with greater than 5,000 managed elements, were even more likely to be dissatisfied with their cross-silo analytics capability – due, in large part, to the complexity and distributed nature of applications and the siloed nature of organizations supporting them.
To get a complete view of application or service performance, 59% of respondents agreed that it was critical to go beyond IT silos and correlate business KPIs as well as customer experience data. Customer experience was highlighted by survey respondents as the most relevant metrics for understanding application and service performance. However, IT infrastructure, business KPIs and application infrastructure were also seen as important. The ultimate goal is to understand the correlated behavior of all of these metrics together.
“The industry agrees that to reach the highest level of maturity in understanding application performance, you must cross silos and correlate business, IT and customer experience metrics,” noted Graham Gillen, Product Marketing Director for Netuitive.
Making Big Data Actionable
The objective is to turn Big Data into an advantage rather than a challenge. Even though an increasing volumes of metrics is driving Big Data, it is those granular metrics that will make the difference, and enable a truly effective APM initiative.
“Increasing business requirements for more dynamic infrastructures and rapid release cycles are driven by customer demand,” explains Jonah Kowall, Research Director, IT Operations Management at Gartner. “These ever shortening windows further increase the need for more granular metric collection and analytics to process the data.”
Experts agree that automated predictive analytics tools are needed to turn massive amounts of application performance data into practical, usable information. There is no going back, no way to avoid the tsunami of Big Data bearing down on IT, and the industry is looking to advanced performance analytics as the solution.
“There’s no question that Big Data has become a driver for Advanced Performance Analytics (APA), where capabilities for processing tens of millions of KPIs or data points in real time or near real time is becoming more and more common,” said Dennis Drogseth, VP, Application and Business Services at EMA.
“Moreover, these APA capabilities provide unique contextual advantages and efficiencies that are alien from traditional data warehousing in terms of discovery, tiered analytics via trusted sources, and service modeling versus data modeling, among others. As a result, EMA is putting a full bore focus on APA as it puts a radically new face to Big Data in a way that may cause quite a few jaws to drop in the coming years.”
Survey Methodology: The survey,was conducted by phone and online during June and July 2012, assessing the opinions of targeted IT professionals in the US and the UK.
