I've been seeing a lot of teams lately who are hitting a wall with their observability spend, especially as data volumes grow. The conversation often seems to settle on two main paths: using a platform like New Relic's own cost optimization tools, or bringing in a specialist like Cribl LogStream to manage data before it ever reaches the observability platform.
From a community management perspective, I'm curious about the practical, long-term experiences here. Has anyone gone deep on comparing these two approaches for actual, sustained cost reduction?
Specifically, I'm thinking about:
* **Data Reduction at Source:** Cribl's strength seems to be filtering, masking, and routing data *before* it's ingested. How effective has this been for you in trimming New Relic bills, versus relying on New Relic's own data sampling and retention settings?
* **Vendor Lock-in vs. Flexibility:** Does using Cribl to normalize and route data to multiple destinations (e.g., S3 for archives, a cheaper log vendor for compliance) give you better negotiating leverage and control long-term?
* **Operational Overhead:** Introducing another piece of infrastructure isn't free. For those who chose Cribl, did the operational cost of managing it outweigh the observability savings? And for those who optimized solely within New Relic, did you feel you had enough control?
I'm particularly interested in B2B SaaS contexts where cost predictability is key. Any workflow reports or concrete before/after figures would be incredibly valuable for the community.
— Jane
— Jane
Good point about the operational overhead. That's my biggest worry too, honestly. My team's small, and I'm the only one who knows any infra-as-code. Setting up and managing another service just for log filtering sounds like a new source of on-call pain.
Has anyone run Cribl on ECS Fargate or something similar? I'm wondering if treating it as ephemeral, managed container tasks could keep that overhead lower than dedicated VMs. But then you're still managing the pipeline config.
That's such a great question, and something I'm trying to figure out too. We're just starting to feel the cost pinch. The point about vendor lock-in is really sticking with me.
We're almost entirely on New Relic right now, and I worry that just using their own tools keeps us tied to their pricing model. The idea of routing some data elsewhere, even just cold logs to S3, seems like it would give us more options later. But I have no idea what setting that up actually looks like.
For a team that's new to this, is the learning curve for something like Cribl pretty steep? Like, could I realistically learn to build a basic filter pipeline in a week, or are we talking months to get it right?
Hey there! That vendor lock-in feeling is so real, and honestly, routing to S3 is a fantastic way to ease that pressure. It's not as scary as it sounds.
> is the learning curve for something like Cribl pretty steep?
I'd say for a basic pipeline, a week is totally doable. You're basically creating a chain of "if this, then do that" rules. The UI is pretty intuitive. The real time-sink isn't the initial filter, but figuring out *what* to filter without breaking dashboards or alerts. You'll spend a day or two mapping what fields New Relic actually uses for your key metrics.
For your S3 idea, a simple starter pipeline could look like this: send all your raw logs to S3 (your cheap archive), then use a sampling rule to send only, say, 10% of DEBUG/INFO logs to New Relic, while sending 100% of ERRORs. That alone can cut volume massively. The config for that is maybe a dozen lines in a Cribl pipeline.
Just be ready for the "oops" moment when you filter out something you later need. Start with a duplicate stream where you don't drop anything, just to be safe!
Integration Ian