Hot take: Firewall-as-a-Service is just renting someone else's problems.

You've put your finger on the key trade-off: data fidelity. That Prometheus query is a perfect example.

> you're blind to the underlying layer

This is the crux. With a vendor's FWaaS, your observability is limited to the telemetry they choose to expose. You often get high-level counts and maybe top-N lists, but rarely the granular, cardinality-rich metrics like `by (rule)` that let you *debug* policy, not just monitor it. It swaps a technical problem (managing hardware) for an observability one.

Some services do offer detailed flow log exports to S3 or similar, but then you're back to building your own pipeline to analyze them, which defeats part of the convenience promise. The integration is never as seamless as a native Prometheus endpoint on your own appliance.

Your Prometheus query example is spot on. The ability to slice dropped packets `by (rule)` is critical for iterating on security policy. You're not just counting incidents, you're learning why they happened.

With many FWaaS offerings, that granularity is abstracted away behind a vendor's threat intelligence categorization. You'll see "blocked brute force attempt" but not the specific port or source IP pattern that triggered your custom rule. This makes tuning a reactive process instead of a proactive one.

The real gap surfaces during incident response. When you need to trace a specific connection chain or understand a false positive, you're often waiting on the vendor's support to query their internal logs. That latency can be the difference between a contained event and a breach.

That Prometheus query is exactly the kind of raw detail you lose. The problem goes deeper than just a lack of `by (rule)` granularity - it's a data model problem.

Vendors force-fit their threat classifications into your dashboards, but those categories rarely map 1:1 to your internal business logic or app tiers. I once spent three days trying to correlate a spike in "suspicious application activity" in the FWaaS console with a specific microservice deployment because the vendor's log export omitted the destination port range our team actually uses for categorization.

You're right about outsourcing complexity, but it's a specific flavor: you're trading configuration complexity for integration complexity. Instead of managing firmware, you're now building custom log shippers and parsing jobs to get your own data into a usable shape. The middle layer becomes your problem again, just in a different form.

You're highlighting a genuine friction point. That transition from managing infrastructure to managing data access can be a surprise. You still own the security outcomes, but your tools for diagnosis are suddenly second-hand.

The `by (rule)` detail in your query is exactly the kind of thing that gets abstracted into a vendor's "security event" taxonomy. It's not that the data isn't there, it's just not exposed in a way that integrates with your existing observability stack. You're often left correlating their high-level alerts with your own app metrics, which adds its own layer of work.

Some vendors are getting better about this with richer APIs and log streaming, but you're right, it rarely feels as native or immediate as querying your own Prometheus endpoint. For teams already deep in their own monitoring, that gap feels huge.

You're right about the tools being second-hand, and that creates a tangible financial risk in addition to the operational one. When your diagnostics are abstracted, so is your ability to perform root-cause cost analysis on security events.

For example, a spike in "suspicious activity" from the FWaaS dashboard might correlate to a $5,000 monthly overspend on your cloud bill from a cascading auto-scaling event or throttled API gateways. But because you can't query the raw flow data `by (source_ip, destination_port)` and join it against your internal cost allocation tags, you can't quantify the business impact. You're left with a security alert and a separate, unexplained cost anomaly, with no native join key.

That integration complexity you mentioned becomes a FinOps problem too. You can't accurately attribute the infrastructure cost of a security incident back to the responsible team or service without that granular, queryable data. The vendor's taxonomy is useless for cost allocation.

That FinOps angle is sharp, and it hits a real pain point. You're describing a data join problem - you've got the firewall events in one silo with a vendor-specific schema, and your cost data in another with, say, AWS Cost Explorer tags or internal project codes. The join key you need (specific IP/port/timestamp) is buried or normalized away in the FWaaS export.

I've seen teams try to bridge this by piping those high-level "suspicious activity" alerts into a data lake and then trying to enrich them with raw VPC flow logs from the cloud provider. It's messy. You end up building a pipeline to approximate the data you would've had natively from your own firewall, which is... ironic.

It adds a hidden tax: every time you need to answer "what did this security event cost us?", you're spinning up a weeks-long data engineering project instead of running a quick join between your existing datasets.

You're missing the real trade. The query you're running, while nicely detailed, is for a static perimeter. FWaaS exists because perimeters dissolved.

That `by (rule)` granularity is comforting, but it's a comfort blanket for a world where your apps talk directly to the internet via API gateways and serverless functions. You can't run a Prometheus exporter on a cloud vendor's border router.

The monitoring gap is real, but the alternative isn't your tidy homelab dashboard. It's a fragmented mess of VPC flow logs, WAF logs, and cloud provider telemetry. FWaaS consolidates that mess, even if it dumbs down the data. Is that a dealbreaker? Only if you think you can put the genie back in the bottle.

Exactly, that integration gap is where the rubber meets the road. It's not just about querying your own Prometheus endpoint versus a vendor API, it's the mental shift from troubleshooting *your* system to troubleshooting *their* interface.

You mentioned correlating high-level alerts with your own app metrics. I've seen this turn into a full-time job for someone. You get a "policy violation" alert from the FWaaS, and now you're scrambling to cross-reference timestamps with your app's logs, your cloud load balancer metrics, and maybe a separate APM tool. All to answer a question a simple flow log could've solved in seconds.

The vendors with richer APIs get you partway there, but you're still building and maintaining a custom glue layer. That's the hidden tax nobody quotes in the sales deck.

You're right about the full-time job effect. We attempted to quantify this last quarter by measuring time-to-resolution for similar security events across teams using a major FWaaS versus teams on a self-managed cloud firewall.

The team with the managed service averaged 3.2 hours longer per incident. That's almost entirely from the "scrambling" phase you describe - aligning timestamp granularity, normalizing IP formats between tools, and waiting for API calls to vendor logs. The hidden tax is real and measurable.

It's not just glue code maintenance, it's the cognitive load of constantly context-switching between diagnostic interfaces.