MAMATHA SRINATH, Principal User Assistance Developer, Oracle Corporation
Traditionally, network and security systems logging is a trade-off between detail and efficiency. At the rate data and log files are increasing, it’s impossible for administrators to correlate logging information and gain insight from it. Getting access, finding, and being able to read a variety of logs can also be a challenge.
For persistence, access or availability reasons, some services that use databases heavily write logs in the database itself. The Oracle Autonomous Database is one such database and its logs can hold key troubleshooting information. The OCI Logging Analytics now can collect and analyze this type of log data.
Oracle Autonomous Database eliminates many administration tasks to help DBAs save time and effort. However, DBAs are still provided with a comprehensive collection of logs for instances where DBA knowledge and action are necessary. In this blog I am going to show how you can leverage the Oracle Autonomous Database logs in OCI Logging Analytics to significantly reduce the time and effort to resolve issues. I will share how you can collect data continuously from the Oracle Autonomous Database tables or views by connecting Logging Analytics to an Autonomous Database, installing a management agent, and specifying the SQL queries that determine what data will be collected. Lastly, I will share four techniques to get the most out of your analysis using visualizations and other capabilities of OCI Logging Analytics.
First, before you start using the Logging Analytics service:
For more details on these tasks, see this step by step tutorial.
Now, let’s walk through the steps on getting data collected from your autonomous databases:
Set up Oracle Wallets to enable Management Agent connectivity to the autonomous database and to register with the management agent.
Map your autonomous database on OCI to a Logging Analytics entity to reference your database instance and enable log collection from it. Specify Autonomous Data Warehouse or Autonomous Transaction Processing as the entity type. Ensure to document the entity name and service name that you provide. You will need them later to register with the management agent.
For the management agent to collect logs from the autonomous database entity, you need to provide the credentials so the autonomous database can be accessed. Also, register the wallet details with the agent.
Define the parameters such as the source type, entity type, and database SQL queries for the log source. The source must be of the type Database. You can map the SQL columns to the field names that are to be displayed in the actual log records.
Best practice is to run any SQL query outside of Logging Analytics to verify the results first.
To begin collecting logs from the autonomous database, associate the autonomous database entity with the log source that you created earlier. After the association, the data starts collecting from the autonomous database entity in Logging Analytics.
For greater details on each step for collection of data collection from an autonomous database, see this tutorial.
Work With Autonomous Logs Data
After data has been collected, take a look at ways to use this data.
Visualize data in the Logging Analytics Log Explorer to gain greater insight
The Visualize panel presents search data in a form that helps you better understand and analyze it. See Visualize Data Using Charts and Controls.
Perform advanced searches of data and run queries
The Logging Analytics Log Explorer user interface enables you to easily perform advanced searches of the data or search through database using queries. Search any log and drill down to specific log entries to resolve problems quickly.
Save, reuse, automate your searches
Once you have a search setup, add them to your dashboard, automatically schedule them, and create alerts on them for reuse.
Create and use dashboards to organize, consolidate and visualize data specific ways
Create, configure and use dashboards to organize and visualize data to provide quick insight into health and performance of your database systems, and help identify outliers and take corrective action.
Learn more about Logging Analytics: