Alright, let's get this started before I get dragged into another "but our dashboard shows..." meeting.
We rolled out Imperva's RASP (Runtime Application Self-Protection) agent last year across a subset of our Java services. The sales pitch was the usual: "real-time threat prevention," "no false positives," "minimal overhead." Fast forward six months, and we're pulling it out. The performance tax wasn't "minimal"—it was a constant drain that introduced more instability than the theoretical threats it blocked.
Here's what we observed:
* **Latency spikes** correlated directly with the agent's "deep inspection" mode. Average response time increased by 30-40% for endpoints with complex object graphs.
* **Memory overhead** was consistently 15-20% higher per JVM. In a containerized environment, that's a direct hit to your node density and your cloud bill.
* The most damning part? **Two production incidents** traced back to the agent deadlocking on a specific JDBC driver interaction during high concurrency. Their support's solution was to add an exclusion rule—basically, disabling protection for that call path.
```java
// Example of the kind of pattern it choked on - a simple, high-volume query
@RestController
public class WidgetController {
@GetMapping("/widgets")
public List getWidgets() {
// The RASP agent would occasionally hold the connection pool thread here
// leading to thread exhaustion under load.
return repository.findAllActiveWidgets();
}
}
```
So we paid for "protection" that we had to disable at the most critical points, while still carrying the performance burden everywhere else. The cost-benefit analysis is laughable. You're essentially trading a known, significant performance hit for a mitigation against highly theoretical, application-layer exploits that a well-hardened environment and a good WAF might already catch.
I'm curious if others have seen this, or if your teams just accept the overhead as the cost of doing security theater. Postmortems from these incidents were… enlightening, to say the least.
- Nina
- Nina
We saw the same deadlocking with a pooled connection manager. Excluding the path was their go-to fix for us too, which defeats the whole point.
The memory overhead was worse for us on services with high ephemeral object churn. It wasn't just a static 20%. G1GC pause times ballooned.
Did you measure the cost of the inspection calls? Our APM showed it was spending more time in their agent's stack than in our actual business logic for some key transactions.
Proof in production.