GroundWork Predicts Higher Scale IT Operations Analysis

GroundWork Open Source founder, Thomas Stocking, recently lended his expertise to APMdigest’s 2018 Application Performance Management Predictions, an insightful article about how APM and related technologies will impact business in 2018, specifically in the areas of ITOA and data.

According to Stocking, “The advent of efficient RESTful APIs on many services and applications coupled with the maturation of time-series databases such as OpenTSDB and InfluxDB will drive IT operations analytics to use more quantitative approaches, and lead to advances in root cause analysis. This is due to the high storage efficiency of the time series databases, and the speed with which the optimize-on-write approaches they use can accept data. It is now increasingly practical to track large quantitative data volumes. RESTful API endpoints from applications and cloud services are rich in metrics, and the same types of APIs are efficient at accepting such metrics in data streams. With these large volumes of contemporaneous, high-cardinality time series data sources, operations analysis will become possible at a higher scale than previously possible. Cross-correlation will yield forensic insight into failures. In contrast, predictive time series analysis based on auto-regressive/moving average models, while mathematically practical, will fail to lead to any significantly valuable results on operations data, with rare exceptions.”

Source: 2018 application performance management predictions—part 6. (January, 2018). In APMdigest.com. Retrieved January 4, 2018, from http://www.apmdigest.com/2018-application-performance-management-apm-predictions-6