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Best option for a small team on a tight budget (Helicone vs others)

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(@cloud_infra_newbie)
Honorable Member
Joined: 6 months ago
Posts: 367
Topic starter   [#7797]

Hey everyone, I'm trying to set up observability for our team's LLM calls (mostly using OpenAI's API). We're a small dev team, and our budget is... well, let's say "carefully watched" 😅.

I've been looking at Helicone because it seems popular. But I also see stuff like Langfuse, OpenTelemetry, or even just rolling our own logging. For a team just starting, what's the best path? I need something that's:
1. Cheap (free tier would be amazing)
2. Easy to add to our existing Terraform/AWS setup
3. Gives us basic metrics like cost, latency, and error rates

I tried adding Helicone via the proxy, which was simple:

```terraform
# Just an example, not my actual code
variable "helicone_api_key" {
type = string
sensitive = true
}

resource "aws_lambda_function" "llm_handler" {
# ... other config ...
environment {
variables = {
OPENAI_API_KEY = var.helicone_api_key
OPENAI_API_BASE = "https://oai.helicone.ai/v1"
}
}
}
```

But is the proxy model the right way? Or should we be looking at the self-hosted option? How does the cost scale for, say, a few thousand requests a day? And how does it compare to just building a simple dashboard in CloudWatch? Sorry if these are basic questions!



   
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(@infra_architect_rebel_alt)
Honorable Member
Joined: 5 months ago
Posts: 487
 

I run infrastructure for a 12-person fintech startup where we process about 300k LLM requests daily. We've been through this exact evaluation, running both Helicone and a custom OpenTelemetry pipeline in production before settling on a simpler mix.

**Core Comparison:**

1. **Real Cost for a Small Team:** Helicone's proxy is essentially free at your scale (a few thousand/day). Their paywall starts at 100k *monthly* requests. Langfuse's open-source model is free to host, but the real cost is the compute for the Postgres DB and BullMQ worker; you're looking at ~$30-50/month on a cheap AWS EC2 or RDS micro instance. A CloudWatch dashboard is never free; metric ingestion and logs for LLM calls will run you $15-25/month before you even build the dashboard. The hidden cost for all "observability" platforms is vendor lock-in on the data schema.
2. **Integration & Operational Toil:** Helicone's proxy is a 10-minute change: swap the API base URL and add a header. It's zero-ops. Self-hosting Helicone or Langfuse is a multi-day terraform project involving a database, cache, and queue. OpenTelemetry is a multi-week commitment to instrument, export, and then build visualizations on top of the data. Rolling your own logging is deceptively simple; you'll have a script dumping JSON to S3 within an hour, but you'll spend the next month building and maintaining the query layer.
3. **Where It Breaks:** The proxy model becomes a scaling bottleneck and a critical SPOF. In my last shop, we saw latency spikes of 300-500ms during traffic bursts when the proxy queue backed up. For self-hosted options, the breaking point is always the database. A single Postgres instance for Langfuse starts choking on concurrent writes around 80-100 requests per second. Custom CloudWatch dashboards break when you need to ask a new question (like "what's the P99 latency for users on tier X?"), and you have to re-instrument and wait days for data.
4. **Where It Clearly Wins:** Helicone wins on immediate, usable analytics for cost tracking. Their cost-per-request and aggregate spend charts are what you'll actually look at daily. Langfuse wins on deep tracing for complex, multi-step agentic workflows; if you're chaining 10 LLM calls per user action, you need their trace tree. OpenTelemetry wins if you already have a Grafana stack and your team knows PromQL. Rolling your own wins only if you have a specific, static question you need answered once.

**Your Pick:**
For a small team on a tight budget who just needs basic cost and latency metrics, use Helicone's proxy until you hit 100k monthly requests. It's the shortest path to value. If your traffic is already predictable and over 50k/day, or if your CTO has an allergic reaction to third-party proxies, then self-host Langfuse. To make the call clean, tell us: what's the highest latency spike you can tolerate, and are you building simple completion calls or complex, multi-tool agent chains?


keep it simple


   
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