Hey folks, been diving deep into our Imperva WAF logs lately and felt the native reporting was a bit limiting for our real-time ops needs. Since we're already a Grafana shop, I decided to pipe those metrics into our dashboards. The result is a custom dashboard that's been super helpful for spotting trends and troubleshooting.
I set up a small Go service that polls the Imperva API (their `visits-last-visits` endpoint is key) and writes the data to a Postgres table with a TimescaleDB extension. The service aggregates counts by status code, security action, and country over configurable intervals. Then it's just a matter of Grafana connecting to the DB.
Here’s the core of the aggregation query that powers the main time-series panel:
```sql
SELECT
time_bucket('5 minutes', timestamp) AS bucket,
status_code,
COUNT(*) as request_count
FROM imperva_visit_data
WHERE $__timeFilter(timestamp)
GROUP BY bucket, status_code
ORDER BY bucket;
```
The dashboard currently has:
* A time-series graph of requests, color-coded by HTTP status (4xx spikes are immediately visible)
* A top-N table showing countries generating the most blocked requests
* A bar chart breaking down security actions (challenge, captcha, block, etc.)
* A stat panel showing total blocked requests vs. passed for the selected period
It's been great for correlating traffic patterns with our deployments. I noticed we had a sharp uptick in challenges right after a major UI release—turned out our new client-side routing was confusing the bot detection. Seeing it visually made the connection obvious.
I'm thinking of adding a panel for average request processing latency from the logs next. Has anyone else done something similar? Curious if you're pulling different metrics or using a different stack (maybe directly via Telegraf?).
--builder
Latency is the enemy, but consistency is the goal.
So you're paying Imperva's premium price tag and then burning your own developer hours to build the reporting they should provide out of the box. Classic.
What's the total cost of ownership on that Go service, including maintenance? And are you locked into their visits-last-visits API staying stable? I've seen that rug pulled before.
Neat project, but it feels like you're just building a more expensive, fragile version of something a proper log shipper and open source WAF could do for you from the start.
Buyer beware.
That's a fair critique on vendor lock-in and API stability. However, from a configuration management perspective, there's operational value in standardizing on a single pane of glass. Our runbooks and incident response procedures are built around Grafana, so bringing Imperva data into that system reduces context switching and training overhead. The maintenance cost of the Go service is documented as a known trade-off in our internal change log, weighed against the efficiency gained.
I'd be interested to know if you've established a formal process for monitoring the upstream API for breaking changes. We version-control the service configuration and treat the Imperva API schema as a tracked dependency. A scheduled job validates the endpoint format weekly, and any drift triggers a change request. It adds a layer of process but mitigates the "rug pull" scenario you mentioned.
That said, the point about a more open-source-centric approach is valid for greenfield projects. When dealing with an existing, entrenched Imperva deployment, this integration often represents a pragmatic step toward unified observability, not necessarily an endorsement of the vendor's shortcomings.