I see a lot of posts about monitoring endpoints with GravityZone, but almost nothing about monitoring the *platform* itself. If your central console or relay servers go down, your entire endpoint visibility is gone.
What are you using to monitor the health of the actual GravityZone infrastructure? I'm talking about:
* Console service status (Apache, PostgreSQL, etc.)
* Network Agent / Relay reachability and load
* Database disk space and performance
* Certificate expiration for components
* Update distribution failures
GravityZone's own "Audit" logs are reactive. I need proactive alerting. I've started scraping some metrics myself.
Example: a simple script to check the Postgres backend from the console server:
```bash
#!/bin/bash
CONSOLE_IP="your-console-ip"
ssh admin@$CONSOLE_IP "sudo -u postgres psql -d gzdb -c 'SELECT 1;'"
if [ $? -ne 0 ]; then
echo "CRITICAL: GravityZone DB check failed"
exit 2
fi
```
But this is basic. Has anyone built a proper monitoring setup? Preferably something that integrates into Prometheus/Grafana or a central SIEM. What metrics are you collecting? How are you handling alerts when a relay in a remote office stops reporting?
slow pipelines make me cranky
I'm in the same boat. The Audit logs are useless for preventing an outage. We treat the GravityZone infrastructure like any other critical internal service.
We ended up using the existing Prometheus node exporter on the console/relay servers for basics (disk, CPU, memory). For application-level checks, we wrote small Python scripts that run as cron jobs and push to Prometheus via a textfile collector. They check:
* HTTP response code and content from the console login page
* PostgreSQL connections and table counts (more detailed than your SELECT 1)
* Internal certificate expiry dates parsed from the filesystem
* A "last seen" timestamp for each relay, derived from the console's own API
The relay check was the tricky part. We query the API for the relay list and their last communication time, then compare that to our monitoring system's clock. If it's stale, we alert. It's not perfect, but it gives us a 15-minute heads up instead of finding out during an incident.
Your approach with the textfile collector is practical, but I'm concerned about the fidelity gap. Scraping the API for relay last-communication time introduces a monitoring blind spot: you're only as healthy as the console's own reporting database. If Postgres slows down or a backend service hangs, your script might still get a 200 OK from the API endpoint while the actual data is stale.
We ran into this and added a synthetic transaction. We have a test endpoint in a low-risk segment that attempts to pull a policy update through a specific relay, measuring the round-trip time back to the console. This catches failures in the distribution layer that the console's internal heartbeat doesn't reflect. The metric is noisy, but the alert is valuable.
Also, are you monitoring the granularity of those PostgreSQL table counts? A sudden drop in certain event tables can indicate a failed cleanup job, leading to disk filling unexpectedly.
Trust but verify.