This section covers operational activities related to accessing, monitoring, scaling, and backing up Squirro.
For information on accessing the Squirro Application as well as Squirro Servers (including Redis and MariaDB), see Accessing Servers.
This includes information on logins, access, instances, and databases.
The cluster status is observable from within the Squirro UI in your browser.
See Cluster Status to learn how to view log files, the monitoring plugin, Elasticsearch status, ingester status, and scheduled tasks.
To learn more about locating and accessing log files, RHEL/CentOS service monitoring, and evaluating memory and disk usage, see Monitoring.
For information on data collected as part of user interactions with Squirro, see Activity Tracking.
Elasticsearch is used for storage nodes where indexed data is persisted. To learn more about tools to support Elasticsearch operations, monitoring, and troubleshooting, see Elasticsearch Management.
Squirro consists of several services that are started and stopped individually. To learn more, including how to interact with services and run Squirro Services in Python, see Services.
How Squirro Scales#
To learn how Squirro can scale from a single host to a massive multi-node cluster, see How Squirro Scales.
Business Continuity Planning#
To learn how Squirro can be run as a clustered application across multiple hosts to provide high availability and horizontal scaling, see Business Continuity Planning.
Backing Up and Restoring Databases#
For information on backing up and restoring the Squirro MySQL/MariaDB database, see Database Backup and Restore.
Fixing MySQL/MariaDB Replication#
If a replication fails on a multi-node Squirro deployment, see Fixing MySQL/MariaDB Replication for more information.