In this special guest feature, Sasha Gilenson of Evolven examines the importance of blended analytics in realizing the promise of IT Operations Analytics. Sasha Gilenson is CEO of Evolven, a technology company that provides IT Operations Analytics solutions for enterprise businesses. Founded in 2007, Evolven is headquartered in Jersey City, New Jersey, USA, with offices in Europe and Israel. Prior to Evolven, Sasha spent 13 years with Mercury Interactive (acquired by HP), managing the QA organization and participating in establishing Mercury Interactive’s Software as a Service (SaaS). Sasha played a key role in the development of Mercury Interactive’s worldwide Business Technology Optimization (BTO) strategy and drove field operations of the Wireless Business Unit, all while taking on the duties as the Mercury Interactive’s top “guru” in quality processes and IT practices domain.
One of the most talked about topics in IT has been IT Operations Analytics (ITOA). Leading vendors and start-ups have made significant progress in leveraging analytics to offer better IT operational insights. However, available ITOA solutions still struggle to make sense of IT Big Data, which perpetuates operations in narrow silos.
IT decision makers need to finally break these silos, by applying an approach that blends and analyzes all relevant sources of IT information. Extracting insights and drawing intelligent correlations from a variety of data, Blended Analytics helps to see beyond individual components and finally draw insights based on the whole picture.
What’s Wrong with Today’s ITOA Solutions
Today’s ITOA solutions are limited by silos, a focus on symptoms, and weak analytics.
- Silos: Who sees the whole picture? IT operations data is very diverse, nevertheless, many ITOA solutions perpetuate a siloed approach, making existing silo tools (e.g. Application Performance Management or APM) “smarter”, while leaving them limited to only their own silo.
- Symptom-focused: ITOA solutions focus on the “symptoms” (APM, log, network) indicating problems, only responding after something happens (an abnormality arises). Yet when a “symptom” is observed, users may already be feeling the impact from the abnormal system behavior. Even more so, identifying the true root-cause of problems based only on “symptoms” is difficult.
- Narrow Analytics: Many of the new ITOA components intended to enhance current product suites are merely new dashboards or a KPI aggregation, still relying on users to define data analysis algorithms, or just providing catalogs of pre-defined statistic functions.
Blended Analytics: The Secret Sauce
To fully realize the value of ITOA, analytics must provide actionable insights to drive operational decisions and activities (both manual and automated). In contrast to the limitations of today’s ITOA solutions, the Blended Analytics approach provides useful insights by analyzing all relevant data sources, focusing on change, and applying powerful analytics.
All relevant Data Sources: Blended Analytics collects, correlates and analyzes data together from multiple data sources (APM, Network, Log, Deployment Automation, Service Desk, CMDB, and Changes (e.g. in configuration, data, capacity, code, etc.). The analysis uses a combination of methods to extract useful insights, and identify behavioral patterns, unusual event occurrences and anomalies.
By combining information from across silos, correlating symptoms and root causes as well as mapping them into context that users can grasp, Blended Analytics improves the probability of early issue detection (prevention), accelerating troubleshooting.
Change-centric: a critical component, yet surprisingly often overlooked data source is changes. In today’s complex IT environments, most operational issues are due to changes. This is why the first question usually asked when performance issues come up is: “what changed?” It is extremely difficult to know exactly what changed. What piece of code, what configuration parameter, what data table was changed as a result of some automated or manual action, which could be authorized or not.
Effective Blended Analytics analyze the data stream through a prism of change, offering quick access to actual and potential root causes.
Powerful Analytics: In order to turn the massive amount of heterogeneous data into actionable insights, Blended Analytics relies on a combination of analysis approaches, including Machine Learning based anomaly detection, risk scoring, domain-specific heuristics and knowledge-base.
Delivering the Full Promise of ITOA
In today’s competitive, complex landscape, optimized IT operations serve as the foundation for business success. To ultimately realize the benefits and promise of IT Operations Analytics, IT decision makers need to apply Blended Analytics to bust out of their silo-focused approach, and put CHANGE as the cornerstone for analyzing everything that happens in IT environments. By collecting all relevant data sources, focusing on change and applying powerful analytics, the next generation of IT Operations Analytics tools will truly offer intelligent analytics and critical insights for maintaining stability and performance.
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