> ## Documentation Index
> Fetch the complete documentation index at: https://hilt.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Sizing and capacity

> Measured resource usage by host type, default limits, and ring buffer tuning.

## Measured resource usage

| Host type | RSS | CPU | Filtered noise | Events/s shipped |
| :- | :- | :- | :- | :- |
| `m6i.large` general-purpose VM | 4–6 MB | \< 1% of 1 core | \~60–75% | 50–400 |
| `r6i.xlarge` DB host | 6–8 MB | \~1% of 1 core | \~70–80% | 300–1,500 |
| EKS worker (16 pods, busy) | 5–7 MB | \< 2% of 1 core | \~70% | 800–3,000 |

## Defaults

The collector ships with conservative defaults suitable for most environments:

* **Kubernetes:** the DaemonSet requests `100m` CPU / `128Mi` memory with limits of `500m` / `512Mi`.
* **VMs:** no hard limits are applied by default, though they can be enforced during installation (e.g., `CPUQuota=20%` and `MemoryMax=512M`) if a strict ceiling is required.

## Ring buffer tuning

The default ring buffer size is 1 MB per CPU, which is sufficient for workloads up to \~5,000 events/sec per CPU. For high-throughput systems, increasing this to 8–16 MB per CPU is recommended.

The agent degrades gracefully under load: when userspace cannot drain the ring buffer fast enough, the eBPF side drops oldest events and emits a count of dropped events to the metrics stream (`metrics.c`). Dropped events never cause the agent to block the kernel.


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