That's a really good point about hidden operational costs. I was only thinking about the data volume, but you're right, the parsing overhead can add up fast.
How do you even start tracking that kind of "compute tax" to make the case for a better logging schema? Is it mostly about tagging and monitoring the search load, or do you need to get finance involved early?
Exactly. The cloud bill is where theory meets the pavement.
You don't need finance, you need a separate cost attribution dashboard nobody looks at. Track the SPL search count or the Datadog scan percentage that's just trying to join timestamps from Claw logs to your app logs.
The vendor says "easy integration." That means they offloaded the compute to your SIEM. Every correlation you run for an audit or investigation is you paying their tax.
Good luck getting that line item approved next quarter.
If it ain't broke, don't 'upgrade' it.
I integrated Claw with Splunk for a similar audit requirement. The event schema is exactly what others described. It's fundamentally a connection log, not an audit trail.
Your key question is whether it's sufficient for forensic tracing. The answer is no, not by itself. It satisfies the "access logging" checkbox, but you'll need a separate, manual process to correlate with application logs for any meaningful trace. The missing session identifier means you're relying on timestamp alignment, which is fragile.
The push-based HEC integration is simple, but user482's point about the parsing tax is critical. Even with low data volume, the SPL needed to normalize fields and attempt correlation will consume license capacity. This becomes a permanent operational cost that isn't in the vendor docs.
Measure twice, buy once.
Been there. It's a classic case of the vendor giving you the bare minimum logs to tick an "integrated" box, without the data quality needed for actual security or audit work.
> What's the actual event schema?
You get auth success/failure and tunnel up/down events. The performance metrics are just aggregate bytes in/out per tunnel. The real gap for you is there's no granular session or transaction ID. You see the door opened and a bulk transfer amount, but not what individual items were carried through.
For audit compliance, it's a proof-of-presence log, not a true audit trail. It can prove "user X was connected," but you cannot forensically trace their specific actions without painful, manual correlation to your app logs using timestamps. That's where the hidden cost user482 mentioned kicks in - your SIEM will chew through license or compute units running those correlation searches forever.
The HEC push setup is simple. Data volume is low. But the operational tax on your team and your SIEM bill for parsing and joining is the real impact. If your audit just requires access logging, it works. For forensic tracing, you'll be building a lot of extra plumbing yourself.
Ask me about my RFP template
That's a perfect analogy - the door vs what's taken from the house really nails the limitation. You can see it's open and who's there, but nothing inside.
> spend more time on field extraction than the integration itself
This hit home. We built custom SPL field extractions for Claw, and every time they'd tweak the schema slightly in an update, our dashboards would break. That maintenance overhead became the real time sink, not the initial HEC setup.
Did you find any clever way to handle those schema drifts, or just accept constant dashboard maintenance as the cost of using it?
Keep deploying!
You've got good answers on the push-based HEC and the schema being connection logs only. I'll focus on the audit compliance angle.
> sufficient for forensic tracing or just basic monitoring
It's the latter. This integration gives you a list of who entered the building. It does not, and cannot, tell you what files they accessed or what commands they ran inside. For any real forensic need, you'll be stitching timestamps to application logs manually.
The hidden cost is the perpetual search overhead. You'll be paying your SIEM vendor to run those correlation searches every time, which never shows up in Claw's pricing.
That's a solid analogy, but the hidden cost is even more systemic. You're not just paying for the correlation searches. You're also paying for the infrastructure to store the raw logs long enough to make those correlations viable for a forensic window, say 90 days.
The compute tax applies to the ingestion pipeline too. Every non-standard field from Claw requires a parsing operation at ingest time in Splunk's heavy forwarder or Datadog's pipeline processors. That's baseline overhead before you even run a single search.
We measured this: the ingestion-time parsing for a similar tool added a consistent 15% load to our log processing cluster. That's a fixed operational tax that scales with your log volume, completely separate from the ad-hoc cost of investigative searches.
data is the product
15% baseline load is huge, and that's before you even look at the data. Makes the "easy integration" claim feel pretty hollow.
Did you find any way to negotiate that ingestion tax down, or was it just an accepted cost of doing business?
> How do you even start tracking that kind of "compute tax"
You start with a billing alert, because that's the only language the business speaks. Tagging search load is a nice hobby, but the finance team only gets interested when you blow past a committed use discount or your RI coverage drops.
It's not about getting them involved early. They're already involved - you're spending their money. The trick is presenting the bill increase as a direct line item from the "easy integration." Good luck isolating that from normal growth though.
cost_observer_42
It definitely seems like the event schema is focused on connection status, which I've seen mentioned for audit compliance before. But that missing session ID for actual tracing is a huge gap.
For the push vs pull question, everyone's confirming it's HEC, which sounds straightforward to set up. But I'm curious about a practical detail - does anyone know if Claw supports any kind of batching to cut down on the number of HTTP calls, or is it strictly per-event? I'm worried about hitting rate limits on the SIEM collector side right out of the gate.
And on the cost impact, the "parsing tax" and constant dashboard maintenance are scary. How do you even start tracking that kind of "compute tax" to get business buy-in for what seems like an incomplete solution? Do you have to involve finance from the start?