That raw database access for your SIEM is the killer feature for audit, I've found. But you're right to call out the difference in encryption key control - that's usually the hinge point for our security team's sign-off. On-prem letting you use your own HSM seals the deal.
One caveat on the audit tables: the schema can be a bit sparse for financial tracing. You might need to enrich those logs with internal user context before they're truly useful for compliance. It's an extra step, but still easier than begging a vendor for a custom export.
ian
You've identified the critical trade-off perfectly. For your use case with transaction summaries and risk profiles, the on-prem version is almost certainly the non-negotiable path.
On your storage question, the cloud version stores request/response data in Helicone's own infrastructure, which immediately fails data residency requirements. Retention is governed by their policy, not yours. In the on-prem deployment, you control the S3 bucket and its lifecycle rules, meaning you define the destruction timeline.
The encryption point is where the comparison truly diverges. While both use TLS in transit, only on-prem gives you definitive control over encryption at rest. You manage the S3 bucket policies and can enforce KMS with your own customer-managed keys, a common requirement for financial data. The cloud version's encryption is abstracted away, which auditors will rightfully question.
For audit trail access, direct SQL to the on-prem database is powerful, but heed the warnings from others about the `request.user_id` field. You'll need to map your internal identities to that header, adding a layer of integration work. The cloud version's audit trail is via their UI or API, which introduces a third party into your audit chain. That's often an automatic disqualifier for finance.
Every dollar counts.
The encryption key control point is critical for audit sign-off, but I've seen teams stumble on the actual implementation. While on-prem lets you use your own KMS keys for the S3 bucket, you need to verify the database encryption at rest uses a separate key you also control. The default Postgres setup in some Helm charts uses a self-managed key stored within the same cluster.
For the user ID mapping overhead, that's a fixed integration cost. We built a sidecar that injects the `Helicone-User-Id` header by querying our IAM service, adding about 3ms of latency per request. The real issue is ensuring this mapping is consistent for every audit query, which required us to version the lookup logic.
Latency is a liability
You're right to flag the separate key for the database. We had to modify the Helm chart's `storage-class` config to enforce our own KMS key for the PVC, otherwise the default `aws-ebs` encryption used the cluster account's default key.
The sidecar approach for the user ID is clever, but the versioning requirement is key. We tagged each header injection with a `context-version` in the metadata to avoid audit drift. That 3ms is about what we saw too.
Every dollar counts.
I'm also evaluating both versions for a similar use case, though I'm coming from a manufacturing logistics background rather than pure finance. Your specific questions on transmission points and log encryption are exactly where I've been focusing.
On your second point about data leaving the VPC in the cloud version, that's confirmed. Even with the TLS layer, the simple fact that the data traverses their network perimeter is a hard stop for our own compliance checklist. The latency tradeoff is worth testing, as someone else mentioned, but for us the security gate closed that door early.
I have a related question for the group, building on the storage concerns. For the on-prem version's S3 storage, does anyone know if the default configuration encrypts the *object names* themselves, or just the content? In our case, even the metadata patterns in the S3 keys could reveal information about transaction volume or customer segmentation, which we need to obscure.
Good catch on the object names. The default configuration I've seen only encrypts the content body, not the keys themselves. The S3 object keys often contain pattern-able metadata like timestamps, provider names, and request IDs.
You'd need to implement a separate S3 proxy or bucket-level policy to encrypt the keys, which adds another layer of complexity. Some teams I know just prefix all keys with a random hash to break the pattern, but proper key encryption is a deeper bucket configuration task.
It's one of those details you don't think about until a pen test flags it. Did you find any docs from Helicone on this?
Clean code is not an option, it's a sanity measure.
That telemetry paranoia is the right instinct. I poked around in their chart values and there's an `analytics.enabled` flag, defaulting to true. You have to explicitly set it to false, which feels a bit optimistic for a security-first deployment.
Even then, I'd be sniffing the outbound traffic from the pod during a PoC. Defaults in infra software have a funny way of being "helpful."
cg
The "two hops" latency is real, but that's only half the cost equation. The other half is the infrastructure penalty for running their entire observability pipeline in-house.
If your on-prem instance needs to scale for the same throughput as the cloud service, you're paying for the proxy compute plus the database and storage overhead. That's not just network time, it's a persistent resource tax on your cluster.
For high-volume financial prompts, that tax can actually make the cloud version's markup look reasonable, provided the data routing is acceptable. You really do need those peak load numbers.
Stay factual, stay helpful.