I've been looking for a simple observability layer for our production LLM calls, and LLM Pulse keeps coming up. Their free tier looks generous on paper for a small team like ours, but I've learned there's often a catch with "unlimited" logging or tracing.
Before I sign up and start instrumenting our workflows, I wanted to see if anyone here has gone through their onboarding process. Specifically:
* Is the 1,000 monthly trace limit on the free plan hard or soft? Does it just stop logging, or does it queue/drop data?
* Are there any core features (like cost breakdowns or specific latency metrics) that are gated behind the first paid tier?
* How smooth is the initial integration? I'm particularly curious about their support for non-OpenAI providers, as we use a mix of Anthropic and open-source models via Together AI.
My main goal is to get basic tracing for cost attribution and to spot latency regressions. If the free tier covers that for a few key workflows, it could be a great starting point.
The 1,000 trace limit is a hard cut-off. Once you exceed it, the SDK simply stops sending data for the remainder of the calendar month. No queuing, no partial sampling, it's just silent. This is fine for evaluation but can create blind spots if you have a sudden spike in usage.
Their cost breakdowns are indeed gated. The free tier gives you latency, error rates, and basic request/response logging, but the per-token cost attribution and the provider comparison charts require the "Team" plan. For your mix of providers, the instrumentation is smooth. Their SDK uses a wrapper approach, so it works with Anthropic, Together, and even local Ollama instances as long as you can intercept the HTTP calls. The main integration gotcha is that their default dashboard aggregates all providers together; separating them for a clear view requires manual tagging of your traces, which is possible but adds a bit of overhead.
If your goal is purely cost attribution, you'll hit the paid tier wall quickly. For latency regressions alone, the free tier is sufficient. I'd suggest instrumenting a single, high-value workflow first to see if the granularity meets your needs before committing to a broader rollout.
infrastructure is code
Thanks for asking about this, I've been looking at LLM Pulse for our migration project too. The hard cut-off on the 1,000 traces is a bit concerning, especially if we have a burst of activity. Did they mention if the counter resets at the start of the month, or is it a rolling 30-day window? That could make a big difference for budgeting the free tier.
On the integration side, hearing it works with Anthropic and Together is a relief. We're in a similar boat with a multi-provider setup. My nervousness is about the wrapper approach - have you found it adds any noticeable overhead to your calls, or is it pretty negligible?
The gated cost breakdowns are a shame, that's exactly what I was hoping to see. I guess the free tier is really just for tracing and errors, not for the financial insights. Might still be worth it to get started though.
One step at a time
The monthly limit resets on the calendar month, not a rolling window, so your blindness after a spike will last until the first of the next month. That's a great way to miss a critical failure just because you had a successful day.
You mentioned cost attribution as a goal. That's the exact feature they hold back. The free tier shows you *that* a call happened and how long it took, but it won't tell you *what* it cost. For a multi-provider setup, you're flying blind on the finance side, which seems counter to your stated purpose.
The wrapper approach is fine for overhead, negligible in my tests. But don't be fooled by "unlimited" logging - the 1,000 trace cap is the real product. It's a teaser that stops working right when you need it most.
Your k8s cluster is 40% idle.
Based on your specific mix of providers, the integration should actually be one of the smoother parts. The wrapper they use for Anthropic and Together is quite lightweight, and I haven't seen any meaningful latency overhead, maybe 5-10ms tops.
For your goal of cost attribution though, you're going to hit a wall. The free tier shows latency and errors, but it completely anonymizes the cost data. You'll see a trace for a call to Anthropic's Claude, but you won't see the dollar amount attached. It's frustrating because that's often the primary reason to set this up.
The 1,000 trace hard cut-off is real, and with a multi-provider setup, you might burn through that faster than you think just testing different models. It really is just a teaser to get you to rely on the dashboard before it goes quiet.
Spreadsheets > opinions
I think the points raised so far about the hard monthly cutoff and the gated cost features are spot on, and directly address your questions. You mentioned your main goal is cost attribution, and that's the single biggest limitation you'll face. The free tier will help you spot latency regressions, but it completely obscures the actual dollar amounts.
Given that specific goal, you might be better served by a different approach. The free tier is essentially a feature-limited trial, not a sustainable way to monitor costs. It's great for getting a feel for their tracing, but you'll likely outgrow it quickly if financial insight is the priority. Have you considered any other tools that bake cost analysis into their free offering?
Keep it civil, keep it real
Totally agree it's more of a trial than a sustainable free tier. I tried using it for a cost-forecasting side project and hit that exact wall - you can't budget what you can't see.
> you might be better served by a different approach
If cost attribution is the non-negotiable, I've had a decent experience with the free tier of LangWatch for this. It gives token counts and estimated costs across providers, which is enough for a basic monthly report. Might be a better fit while you're evaluating.
Automate the boring stuff.
The hard cut-off's been covered, but a sneaky detail is how they count those 1,000 traces. Concurrent or batched requests? Each one's a trace. A single user flow hitting three different models in a chain burns three of your slots. For cost attribution, you're completely out of luck - they blur the dollar amounts like a censored document. You'll see the call but not the cost.
Integration's the one bright spot. Their wrapper for Anthropic and Together is genuinely painless, adds negligible overhead. But that just makes the feature gating more frustrating. It feels like they built a solid tracing engine, then deliberately removed the financial optics to make the free tier feel incomplete.
LangWatch's free tier, as mentioned, will actually show you token costs. For your stated goal, LLM Pulse's free plan is a demo that ends right when you ask "so how much is this costing us?"
Demos are just theater. Show me the real workflow.
That monthly calendar reset is the killer. Even if you're careful, one good demo day or a burst of marketing traffic can burn through your allowance. You're then completely in the dark for the rest of the month, right when you'd want data on that new traffic pattern.
And you're spot on about it being a teaser. It's engineered to stop working right when you start to depend on it. Feels like a classic freemium trap.
For OP's cost goals, this mismatch between "it traces everything" and "it hides the costs" makes the free tier almost a red herring.
✌️