AutoNOC 2.5 User Guide
Preface
Acknowledgements
System Requirements
Legal

Part 1 - Introduction
1.1 The Ideal Difference
1.2 Automated Operations
1.3 Services & Scaler
1.4 Acquisition Stacks
1.5 Portal Deployment
1.6 Discovery and Crawler
1.7 Monitoring Agents
1.8 Recoiling Database
1.9 Multiple Languages
1.10 Security

Part 2 - NOC Views
2.1 Investigate
2.2 Observe
2.3 Visualize
2.4 Alarms
2.5 Analyze
2.6 Design
2.7 Configure

Part 3 - Model Design
3.1 Object Model
3.2 Devices
3.3 Sets
3.4 Set Criteria
3.5 Probes
3.6 Logs & Events
3.7 Alarms
3.8 Actions
3.9 Reports
3.10 Users
3.11 Polling
3.12 Service Levels
3.13 Dependencies
3.14 Performance

Part 4 - Developer Features
4.1 Adding SNMP MIBs
4.2 Variables
4.3 OSP API
4.4 Probe Template
4.5 Log Template
4.6 Device Template
4.7 Interface Template
4.8 Rebranding

Part 5 - Troubleshooting
5.1 General Issues
5.2 Linux
5.3 Windows

Appendix
A.1 OSP API Functions
A.2 Variables
A.3 Object Reference

1.1 The Ideal Difference
Let’s take a moment and dramatically simplify network operations, problem detection, root cause, correlation, and every other aspect of monitoring down to some simple bullet points.

What exactly does AutoNOC do and how does it work? AutoNOC does the following:

  • AutoNOC Makes Data Management & Acquisition Very Easy
    AutoNOC acquires, manages, and maintains representative network models faster, better, and more cost effectively than any other product before it. AutoNOC integrates and consistently simplifies all of the related complex steps so that the user does not have to worry about them.
  • AutoNOC Helps You to Build an Ideal Model
    The integrated Web GUI, AutoNOC Interpreter, service levels, object templates, built-in pre-defined service levels, and many other fast, lean, and clean features make it practical for you to build the right operations model for your network without spending lots of money on consultants.
  • AutoNOC Compares the Data to Your Ideal Model
    AutoNOC takes your data model and compares the information live, on the fly, to the ideal or 'healthy' values. The software includes thousands of ideal value settings and makes it very easy to change these or tune them.
  • AutoNOC Flags Any Variations from the Ideal as Problems
    Whenever incoming data is outside of the ideal values and healthy data ranges, that means that either the model needs to be adjusted or an issue has been detected, i.e., a 'problem'. The AutoNOC operations core then shows you these problems using a variety of different views..

AutoNOC acquires lots of data, compares it all to what should be ideal, and whenever the data differs from the ideal, the good health condition is falsified and the problem condition rises to the top.

It provides a simple, very precise, no nonsense methodology that makes it easy to detect and instantly identify problems within real world IT environments.

AutoNOC's design was influenced by the works of Karl Popper (Popperian Logic) and his Theories of Demarcation and Falsification. Popper's theories were used to show that Einstein's Special and General Theory was a better theory than Newton's Law of Gravitation for instance.

Most people would probably agree that troubleshooting some networking issues is a lot like particle physics (or at least as challenging)!

Popper's falsification approach (assume everything is true and search for that which disproves this theory) is one of many things that make AutoNOC The Ideal Difference for people in real world systems and network operations environments.

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