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Deep Data Collection (Part 2)


Deep Data Collection (Part 2)


This article is part of a series covering how changes still present a risk for today's IT operations, despite advances in technology and processes, and how a change-centric analytics approach addresses this.

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Evolven can collect information from other existing IT management and IT monitoring tools. While not required, with this information available, Evolven can provide more insights for all identified changes.

Evolven takes information, like a change request from the service desk or an application topology from CMDB or symptom information from monitoring tools - all the different alerts and events. Evolven correlates all this information in an analytics engine.

Using machine learning as well as anomaly detection, statistics and heuristic algorithms, Evolven’s patented analytics provide answers to such questions as ”what actually changed” and “what’s different in your environment.”

Getting to the Root Cause

Since changes could exist deep down at the granular level, change-centric analytics needs to also look at which of these changes could be the root cause for an incident being investigated or which other changes can be potentially risky or could potentially cause a performance, availability or stability issue in the environment. Evolven collects change data from the entire environment, and if available Evolven correlates this data with IT management tools already present in the system.

Evolven addresses three key questions:

  • What changed?
  • What cause an issue?
  • What can cause an issue?

Looking at all Information

To answer these questions, it’s very important to have the right information. Since this information isn’t always accessible and other tools do not actually collect this information, Evolven’s change-centric analytics make a deep data collection. Evolven looks at the entire environment from the entire server stack, virtualization and cloud infrastructure, network, storage, the applications themselves to web servers, middleware, messaging software, databases, and operating systems. Evolven looks at the entire environment.

Evolven looks at all the different types of changes:

  • Changes to the files (whether it’s Windows or registry)
  • Changes in the data base schema:
    • Are properties of my table correct?
    • Do I have a new view?
    • What are the compositions of the new view?
  • Changes to the master application data inside the data base tables
    • Are they any changes in the field of the master data?

Evolven gets information through

  • System commands
  • API calls
  • HTTP requests
  • SNMP
  • imports from existing tools (where available)

No matter from where there is a source of a change, Evolven can actually use a rule for this change and extract critical information.

Down to the Most Granular Level

It is also very important is to break down this information to the most granular level. For example if a file changes - what it actually means - is that inside this file a value for a configuration parameter was changed from 1 to 10. A lot can be ascertained about this change! The change value can actually be analyzed for many different aspects: how critical is this configuration parameter, what is the history of this configuration parameter, does this change value look reasonable, does it actually match what is in the rest of the environment and so on.

Evolven breaks down information from such sources as:

  • The configuration
  • Parts file down to the individual parameters
  • Data base changes to specific attributes of the schema
  • Store procedures
  • Data base for global instance configuration parameters
  • Operating system will get in to the kernel parameters
  • Properties of the servers
  • Drivers
  • Printers
  • In Windows all the INI files, for example, Evolven parses them and see what configuration changes are there.

Evolven looks at the entire environment - end to end - pulling in all possible types of changes and breaking them down to the most granular level to make change-centric analytics more efficient.

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About the Author
Sasha Gilenson
Sasha Gilenson enjoyed a long and successful career at Mercury Interactive (acquired by HP), having led the company's QA organization, participating in establishing Mercury's Software as a Service (SaaS), as well as leading a Business Unit in Europe and Asia.

Sasha played a key role in the development of Mercury'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's top "guru" in quality processes and IT practices domain. In this capacity, Sasha has advised numerous Fortune 500 companies on technology and process optimization, and in turn, acquired a comprehensive and rare knowledge of the market and industry practices.

Sasha holds an M.Sc. in Computer Science from Latvian University and MBA from London Business School.