Once you’re in production, you’ll want to set up some monitoring. This page may serve as a starting point for you but you are encouraged to share your ideas with the Dataverse community!
Contents:
In production you’ll want to monitor the usual suspects such as CPU, memory, free disk space, etc. There are a variety of tools in this space but we’ll highlight Munin below because it’s relatively easy to set up.
http://munin-monitoring.org says, “A default installation provides a lot of graphs with almost no work.” From RHEL or CentOS 7, you can try the following steps.
Enable the EPEL yum repo (if you haven’t already):
yum install https://dl.fedoraproject.org/pub/epel/epel-release-latest-7.noarch.rpm
Install Munin:
yum install munin
Start Munin:
systemctl start munin-node.service
Configure Munin to start at boot:
systemctl enable munin-node.service
Create a username/password (i.e. “admin” for both):
htpasswd /etc/munin/munin-htpasswd admin
Assuming you are fronting your app server with Apache, prevent Apache from proxying “/munin” traffic to the app server by adding the following line to your Apache config:
ProxyPassMatch ^/munin !
Then reload Apache to pick up the config change:
systemctl reload httpd.service
Test auth for the web interface:
curl http://localhost/munin/ -u admin:admin
At this point, graphs should start being generated for disk, network, processes, system, etc.
HTTP traffic can be monitored from the client side, the server side, or both.
HTTP traffic for web clients that have cookies enabled (most browsers) can be tracked by Google Analytics (https://www.google.com/analytics/) and Matomo (formerly “Piwik”; https://matomo.org/) as explained in the Web Analytics Code section of the Installation Guide.
To track analytics beyond pageviews, style classes have been added for end user action buttons, which include:
btn-compute, btn-contact, btn-download, btn-explore, btn-export, btn-preview, btn-request, btn-share
There are a wide variety of solutions available for monitoring HTTP traffic from the server side. The following are merely suggestions and a pull request against what is written here to add additional ideas is certainly welcome! Are you excited about the ELK stack (Elasticsearch, Logstash, and Kibana)? The TICK stack (Telegraph InfluxDB Chronograph and Kapacitor)? GoAccess? Prometheus? Graphite? Splunk? Please consider sharing your work with the Dataverse community!
AWStats is a venerable tool for monitoring web traffic based on Apache access logs. On RHEL/CentOS 7, you can try the following steps.
Enable the EPEL yum repo:
yum install https://dl.fedoraproject.org/pub/epel/epel-release-latest-7.noarch.rpm
Install AWStats:
yum install awstats
Assuming you are using HTTPS rather than HTTP (and you should!), edit /etc/awstats/awstats.standalone.conf and change LogFile="/var/log/httpd/access_log" to LogFile="/var/log/httpd/ssl_access_log". In the same file, change LogFormat=1 to LogFormat=4. Make both of these changes (LogFile and LogFormat in /etc/awstats/awstats.localhost.localdomain.conf as well.
Process the logs:
/usr/share/awstats/tools/awstats_updateall.pl now
Please note that load balancers (such as Amazon’s ELB) might interfer with the LogFormat mentioned above. To start troubleshooting errors such as AWStats did not find any valid log lines that match your LogFormat parameter, you might need to bump up the value of NbOfLinesForCorruptedLog in the config files above and re-try while you interate on your Apache and AWStats config.
Please note that the Dataverse team has attempted to parse Glassfish/Payara logs using AWStats but it didn’t seem to just work and posts have been made at https://stackoverflow.com/questions/49134154/what-logformat-definition-does-awstats-require-to-parse-glassfish-http-access-logs and https://sourceforge.net/p/awstats/discussion/43428/thread/9b1befda/ that can be followed up on some day.
https://github.com/IQSS/dataverse/issues/2595 contains some information on enabling monitoring of app servers, which is disabled by default. It’s a TODO to document what to do here if there is sufficient interest.
There is a database table called actionlogrecord that captures events that may be of interest. See https://github.com/IQSS/dataverse/issues/2729 for more discussion around this table.
Changes made to draft versions of datasets are logged in a folder called logs/edit-drafts. See https://github.com/IQSS/dataverse/issues/5145 for more information on this logging.
Failures occurring during the indexing of dataverses and datasets are logged in a folder called logs/process-failures. This logging will include instructions for manually re-running the failed processes. It may be advantageous to set up a automatic job to monitor new entries into this log folder so that indexes could be re-run.
Should you be interested in monitoring the EJB timers, this script may be used as an example:
#!/usr/bin/env bash
# example monitoring script for EBJ timers.
# currently assumes that there are two timers
# real monitoring commands should replace the echo statements for production use
r0=`curl -s http://localhost:8080/ejb-timer-service-app/timer`
if [ $? -ne 0 ]; then
echo "alert - no timer service" # put real alert command here
fi
r1=`echo $r0 | grep -c "There are 2 active persistent timers on this container"`
if [ "1" -ne "$r1" ]; then
echo "alert - no active timers" # put real alert command here
fi