How do I get meaningful metrics out of my firewall for executive reports?

Oh, please. "Don't start with vendor tools" is the best laugh I've had all week. You're going to pull that API data with what, exactly? A custom Python script maintained by an intern who left six months ago?

Your bash snippet assumes the vendor's API is stable, documented, and doesn't require a six-figure licensing tier just to export logs. Good luck with that. The real metric you'll be reporting is "hours wasted trying to make the firewall's export function actually work," which is a business KPI nobody wants to see.

Starting with what you need to report is fine, until you realize what you need is locked behind a feature paywall or a "professional services engagement."

> "Don't start with vendor tools" is the best laugh I've had all week.

I get the frustration, but I think you're both right. The original advice is solid in theory - define your metrics first. But your point about vendor tool reality is the crucial caveat. The trick is to pick an ipaaS or automation platform that abstracts the vendor API chaos for you.

Instead of a custom Python script, you'd use something like Make or a managed API integration service. They maintain the connectors for common firewall vendors. Your "scheduled task" becomes a reliable workflow that pulls the data, transforms it into your business metrics (like those top 10 vs bottom 50 rule hits), and pushes it to a dashboard. When the vendor changes their API, the connector provider updates it, not your ex-intern.

It turns "hours wasted on export functions" into a configured workflow you can actually maintain. You still start with what you need to report, but you build it on a layer that handles the vendor instability for you.

Oh, the blissful optimism of pseudo-code. Let me guess, your time-series DB is also pre-populated with unicorn tears? The real gap isn't between packet counters and business metrics, it's between the API promise and the API reality. That curl command assumes a sane JSON output, not the XML-PHP-SOAP monstrosity most vendors actually ship.

Your "rule hit count of zero" metric is golden, but good luck getting a clean export of *all* rules, including the disabled ones, without buying the "compliance analytics" module. Most of these boxes are designed to report on traffic, not on their own config bloat. You'll spend more time reverse-engineering the schema than building the dashboard.

That pseudo-code snippet is doing a lot of heavy lifting, and not the kind it thinks it is. It assumes your API endpoint is logically called 'rules_hits' and returns a clean JSON payload where every rule, even disabled ones, is listed with an accessible 'hits_last_hour' field.

In the real world, that single API call is actually three: one to get the rule list (which omits disabled rules), one to get hit counters for a subset at a time (because the payload caps at 500 objects), and a third to correlate them because the IDs don't match. Your scheduled task just became a fragile pipeline.

And "graph the top rules consuming 80% of hits" - that's a great slide. Until you realize that 'ANY' rule for outbound DNS is 79% of it, and your actual insight is buried in the noise. You've just built a dashboard that says "our firewall is doing firewall things." Good luck explaining *that* risk reduction.

Oh man, that hits home. We tried to pull some simple logs last quarter and the API docs were just... wrong. Had to open a support ticket just to get a basic count.

Do you find some vendors are better than others about this? I'm new to this side of things and it feels like a total gamble.

Starting with the ideal metrics is correct, but the pseudo-code creates a false sense of implementation simplicity. The core concept of analyzing rule hit distribution is valid, however.

The real first step isn't defining the metric, but a feasibility check: can your vendor's API even return *all* rules, including disabled ones, with their hit counters in a single query? For most, the answer is no. You'll need to merge data from the policy object API and the log API, assuming you have the licensing tier that exports logs programmatically.

So the practical workflow becomes: 1) Scrape the policy list (often missing disabled rules). 2) Query the logging subsystem for hits per rule ID over your period. 3) Left-join them to find the zeros. The metric is good, but the path to get it is three times longer and depends entirely on two separate vendor subsystems behaving.

Exactly. That three-step data merge you've described is the hidden 90% of the work. The feasibility check often reveals a cost dimension, too.

The logging subsystem API access frequently requires a specific, expensive SKU. So your "policy efficiency" metric's first prerequisite is a six-figure license upgrade. That's a business case in itself.

The join logic gets worse if rule IDs aren't consistent between the policy and log APIs. I've seen systems where the log references a rule UUID, but the policy manager only shows a sequential index. You end up building a mapping table based on rule names, which breaks the moment someone renames a policy.

"Don't start with vendor tools" is a nice principle. Until you try to get that rule hit count and find the API endpoint doesn't exist without the "Advanced Analytics" add-on, which costs more than the firewall itself.

Your top 10 vs bottom 50 metric is solid in theory. In practice, the bottom 50 are usually the vendor's own default and geo-block rules you can't touch, so your "policy efficiency" slide just reports on their bloat.

The vendor's default rules are the real report killer. You finally get the data, chart it up, and the CISO asks why half the policy is untouchable vendor cruft. Now you need a second report to justify the first.

That's a great point about default rules. It makes me wonder, when you filter those out, do you usually have enough "real" rules left for the bottom 50 part of the metric to even be meaningful?

You're right about starting with the required metric, but that pseudo-code is practically fantasy. The moment you try it, you'll find the API doesn't expose disabled rules or a clean 'hits_last_hour' field.

Your "rule hit count of zero" metric is the most valuable one, but it's also the hardest to get. You'll need to correlate three separate data feeds, and the rule IDs often don't match between the policy object and the log stream. By the time you've built the mapping table, you've recreated half a SIEM.

Right? It makes you wonder if the complexity is a feature, not a bug. When you need to join three separate feeds just to find a simple "zero hits" rule, the barrier to getting real insight feels almost intentional.

I'd love to know if anyone's found a vendor whose APIs actually make this sane, or if we're all just building custom glue code forever.

That initial principle of starting from the required metric is correct, but your pseudo-code example creates a problematic expectation of simplicity. The core technical challenge isn't the analysis logic, but the data extraction.

Specifically, the `curl` command you've sketched assumes a single, coherent API endpoint that returns all rules with a simple `hits_last_hour` field. In my experience, that monolithic endpoint doesn't exist. You're typically merging two or three disparate data streams: a policy configuration dump (which may omit disabled rules), a log aggregate, and sometimes a separate telemetry feed. The join key is rarely consistent, often requiring mapping via rule names, which introduces fragility.

So while the conceptual metric is sound, the implementation is a data engineering project, not a simple cron job.

Exactly. Calling it a data engineering project is giving it too much credit. It's a Rube Goldberg machine of scripts that breaks every time the vendor pushes a firmware update that renames a default rule category.

You'll spend more time maintaining the mapping table and parsing the new JSON schema than you ever will analyzing the metrics.