Advanced Analytics

A private Grafana workspace for your dedicated node. It shows how your node is used in real time.

Advanced Analytics is a private Grafana workspace for your dedicated node. It records every request the node handles and turns that raw activity into a clear picture of how your node is used, in real time. Without it, a dedicated node is a black box: it serves your traffic, but you cannot see the shape of that traffic or where it strains. It shows request counts, latencies, and errors.

You see the data as time-series charts, which gives you a more readable and understandable in-depth analysis. You can tell which requests consume more compute units(CU).

How it works

The add-on measures every request and stores it as a time series. It then lets you view that data along three dimensions:

1. by RPC method,

2. by access key,

3. and by region

So you can move from a high-level number down to the exact cause behind it.

Three core signals sit at the center of the workspace:

• Request volume: how many calls the node receives over time.

• Latency: shown as percentiles (p50, p95, p99) rather than a single average. An average hides the slow requests; percentiles expose the tail where real problems live.

• Error rate: the share of requests that fail.

The per-method view shows which calls cost you the most; heavy methods such as debug_traceTransaction and eth_getLogs stand out here. The per-key view shows which client or service drives your traffic. The per-region view shows where your users connect from.

The value comes from following one signal to its source. Say your p99 latency jumps at 14:00. You open the per-method view, filter to that window, and find that eth_getLogs latency tripled while everything else held steady. You now know exactly what to optimize, and you never had to guess.

Benefits

• Cost attribution. Assign traffic to a team, a customer, or a feature by looking at the per-key view.

• Real capacity planning. Size the node from measured traffic rather than an estimate.

• Faster debugging. Trace a latency spike to the method behind it in a single view.

• Abuse detection. Spot a key that starts sending abnormal traffic, with the data to prove it.

When to use it

• You want to attribute cost to a team, a customer, or a feature.

• You plan capacity and need real numbers.

• You debug latency spikes and need to find their cause quickly.

• You suspect one key is behaving abnormally and want evidence.

Limitations

Analytics gives you visibility, not control. It shows you what is happening; it does not block or shape traffic. When you need to act on what you see — to restrict access or stop abuse — pair it with the IP Allowlist. And because it works from real traffic, a node with very low, steady volume gains little from it.