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Oracle Explorer Data Collector Implementation Best Practice (Doc ID 1006990.1)

Last updated on AUGUST 27, 2024

Applies to:

Explorer Data Collector - Version 5.11 and later
Sun Hardware - Generic - Version All Versions and later
Sun Software - Generic - Version All Versions and later
All Platforms

Goal

Oracle Explorer Data Collector is a diagnostic data collection tool. It collects data on hardware, storage, network, Operating System, system configuration, and most importantly log files and error messages. Collecting and transferring this data to Oracle is one of the fundamental prerequisites for troubleshooting any number of product issues.

When the Explorer output is analyzed with the Proactive Analysis Center(PAC) knowledge engine, a risk exposure report can be generated. Besides being used as reactive diagnostic tool, Oracle can use the Explorer output to detect potential product issues and identify affected customers proactively.

The Oracle Explorer Data Collector is comprised of UNIX shell scripts and a few binary executables to capture data. This data is human-readable (i.e. collected in ASCII format), and is compressed and packed into a single file named explorer..-YYYY.MM.DD.HH.MM.tar.gz for easy transfer to Oracle, or to internal archiving systems.

Oracle recommends installing Explorer on every Solaris system and running it at least once every 3 months. Optimal running of Explorer should be every month. Whenever possible, make Explorer part of every standard build and always run before and after any changes to the system. Collecting and archiving Explorer snapshots, at Oracle or at the customer site, makes it easy to:

  1. Document the initial setup of a system after installation.
  2. Document any changes on a system's configuration by comparing the deltas of two Explorer snapshots.
  3. Analyze potential problems by looking for changes made at the affected system.
  4. Recover well known working system configuration files (e.g. /etc/path_to_inst, /etc/system, VxVM configuration) if they are accidentally removed or destroyed
  5. Automatically identify customer systems impacted by known issues, resulting in a quicker resolution of product quality issues
  6. Speed up analysis of arising new product quality issues.  Explorer data, amongst other data sources, are analyzed to help in root cause analysis.
  7. Calculate a systems operational risk (Operational Risk Index, ORI) - the potential chance of a system to go out of service due to hardware, software and administrative issues.

All the above-mentioned actions are targeted to improve availability and stability of the customer's environment, and to help, directly or indirectly, customers to run their business with fewer interruptions.

Solution

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