Everyone obsesses over shaving microseconds off a single RPC call. Kernel bypass stacks. Custom codecs. Hand-rolled gRPC pipelines. RPC Fast watches this obsession closely because it misses the real problem. Those optimizations matter for each Solana RPC API, but they’re only a tiny slice of the latency story.
In production, your trading strategy lives or dies not by “RPC latency” alone, but by how your network behaves when everything is on fire.
Latency Is Not One Number
Here’s what most people get wrong about latency in trading. They think it’s the time from “event” to “execution.” That’s true, but it’s built from multiple pieces:
- Propagation: How long it takes bits to travel from A to B. Physics. The speed of light in fiber is about 4.9 microseconds per kilometer. You can’t optimize this much.
- Processing: How long does your CPU and network card take to handle the data? This is where code matters.
- Queueing: How long your packet waits in a buffer because the link is busy. This is where everyone fails.
- Serialization: How long it takes to put bits on the wire. Message size divided by link speed.
Most engineers focus on propagation and processing. They ignore queueing. That’s the mistake.
Microbursts Will Destroy Your Latency
Here’s a real example from Arista’s HFT research. A BATS exchange feed has:
- One-second average bandwidth: 86 Mb/s
- One-millisecond microburst: 382 Mb/s
On a 1 GbE link, that 382 Mb/s burst is already 38% of your total capacity in that instant. What happens? Queues grow. Packets wait in buffers. Your delay grows from microseconds to milliseconds. You miss the trade.
On a 10 GbE link, the same burst is only 3.8% of capacity. Still there, but you have headroom. Packets don’t queue. Latency stays low.
| Link speed | Burst as % of capacity | Queueing risk | Latency impact |
| 1 GbE | 38% | High | Severe |
| 10 GbE | 3.8% | Low | Minimal |
| 25 GbE | 1.5% | Very low | Negligible |
The lesson: high bandwidth doesn’t make each packet faster. It prevents congestion, which is what ruins latency during real events.
RPC Is Fast. What about the Network?
When engineers say “our RPC is fast,” they mean:
- Services are colocated in the same datacenter
- The stack uses kernel bypass or tuned TCP
- Payloads are small
- Benchmarks run under low load between two nodes
All true. All irrelevant in production. In a real trading system, you have:
- Multiple market-data feeds coming in
- Orders, cancels, and modifies going out
- Internal pub/sub distribution to strategies and risk engines
- Telemetry and monitoring streams
During a volatility spike, these flows converge on specific network cards, switches, and uplinks. If a critical link runs near saturation, queues form. Your RPC packets wait in line. The RPC implementation hasn’t changed. The environment around it has.
This is why serious trading networks focus on microburst behavior, buffer sizing, and link utilization at sub-millisecond granularity—not just average Mbps.
How to Actually Fix This
Overspec your critical links. Market-data ingest, internal backbones, order gateways—these need 10/25/40 GbE, even when average utilization looks modest. You’re buying headroom, not throughput.
Choose your switches carefully. Cut-through switches minimize per-hop latency but have smaller buffers. Deep-buffer switches handle big bursts better but can introduce queueing delays when hot. You design topology to match your risk tolerance.
Optimize inside the server. Place network cards and processes in a NUMA-aware way so packets don’t bounce across memory controllers. Use multiple RX/TX queues to scale packet handling across cores. For hot paths, consider kernel-bypass stacks (DPDK) or on-NIC processing to reduce latency and increase sustainable message rates.
A mis-pinned process or an overloaded PCIe lane can quietly add hundreds of microseconds to your apparent “RPC latency,” even if the wire-time is tiny.
Colocate and use direct cross-connects. Minimize propagation delay and reduce intermediate hops. For inter-city latency, microwave links can beat fiber on propagation, but at lower bandwidth. Capacity planning becomes even more important.
Measure under the Real Conditions
To know whether your bandwidth and topology are actually working, measure end-to-end latency under realistic load, not idle-time benchmarks.
Track P50, P95, P99, and P99.9 latency for critical paths. Especially during market open, market close, and major macro events. Replay historical burst patterns rather than uniform traffic. Use GPS-synchronized clocks; NTP alone is rarely accurate enough at microsecond resolution.
Example targets:
| Metric | Target |
| Mean end-to-end latency | < 500 μs |
| P99 (normal load) | < 1 ms |
| P99 (burst periods) | < 2–3× mean |
| Packet loss on critical feeds | ~0 |
Once queueing and throughput dominate, further micro-optimizations of your RPC code yield diminishing returns. Amdahl’s Law applies.
What You Have to Consider Further
You don’t just need fast RPC. You need RPC that stays fast when the network is on fire. That only happens when bandwidth and topology are engineered as first-class citizens, not afterthoughts.
RPC Fast understands this. We don’t just supply bare RPC. We engineer infrastructure that keeps your latency low when it matters most—during the moments when everyone else’s network is melting.
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