Practical guide to enterprise Solana RPC infrastructure

TL;DR

• Cloud VPS is a poor fit for Solana. Virtualisation introduces jitter that breaks performance on sub-second block times.
• Consistency beats peak speed. For production workloads, p99 latency matters more than a one-off low ping.
• High-performance Solana RPC requires premium bare metal servers with high-spec CPUs, RAM, NVMe, and networking for blockchain sync and stability.
• Credit and CU systems make costs hard to forecast and even harder to control at scale.
• You need deep product and method-level overview dashboards to diagnose and fix issues quickly.
• Hybrid setups are most common for enterprise needs. Shared infrastructure works great for most tasks, while dedicated nodes are used for ultra-low latency streaming.
• Mitigate vendor lock-in, stick to open-source standards and standard APIs for easy provider switching.

Solana is increasingly positioning itself as the de facto execution layer for Internet Capital Markets. The continued engagement from industry giants like PayPal, BlackRock, and Visa demonstrates that the network is successfully bridging the gap between traditional finance requirements and blockchain performance.

Once that decision is made, the question changes from “Why Solana?” to “How do we run this without crashing?”

Building a dApp in 2026 is straightforward; scaling it for millions of users, or high-frequency trading, is an engineering challenge. At the enterprise level, your RPC provider becomes either a bottleneck or an ally – never in the middle.

If an RPC node becomes unavailable, or falls behind the chain, the effects are hard to ignore:

• Wallets display stale balances, or fail to refresh state.
• Transactions fail to propagate, or confirm within expected time bounds.
• Indexers lag the tip of the chain and require backfilling.
• Trading systems see worse fills and higher slippage.

Every week, we speak with engineering teams expanding into the Solana ecosystem, some starting from scratch, while others migrate after discovering that their existing infrastructure did not hold up under production traffic.

This guide’s purpose is to help you understand what actually matters in Solana RPC infrastructure, and avoid common pitfalls when choosing a provider.

Hardware fundamentals for Solana RPC

The physical infrastructure behind your RPCs is crucial for high-throughput chains like Solana.

Its short block times, parallel execution model, and high throughput place sustained pressure on CPU scheduling, memory bandwidth, disk I/O, and network latency. If any of these are unstable, performance degrades quickly.

There are a few key things to ensure in hardware, which we break down below.

Bare metal vs cloud

If you are coming from EVM chains, cloud infrastructure can appear sufficient, but on Solana, it usually isn’t.

VPS environments are virtualised. CPU time, memory bandwidth, and network queues are shared between tenants. Under load, this causes unpredictable latency spikes when neighbouring workloads burst, resulting in missed shreds, stale reads, and failed sends.

That’s why all Solana-native RPC providers operate on bare metal. Direct access to CPU cores, NVMe storage, and network interfaces is non-negotiable here.

Baseline server requirements

High-traffic workloads need premium bare metal servers with sufficient CPU, memory, NVMe storage, and network capacity to stay in sync with the tip of the chain. For example, an average Triton RPC node uses a gen4/5 AMD CPU, 768 GB RAM, 4× gen4/5 NVMe, and 2×25 Gbps networking.

Providers should also include built-in load balancing, GeoDNS routing, automatic failover, and intelligent abuse prevention to keep throughput and latency stable under spikes.

Global distribution

Premium hardware is not enough without validator proximity and global distribution. Solana performance depends on 2 paths: client-to-RPC and RPC-to-validator. That is why Triton runs in 20+ top-tier data centres across 15+ cities where most validators operate, and lets you deploy dedicated nodes close to your users.

Performance and reliability

People often see latency as the #1 enemy. And while reducing it matters, the real enemies for most workloads are jitter, downtime, and ineffective support.

Minimal jitter

Latency is the time from A to B, while jitter is the variability in that time. A provider’s “20 ms average latency” claim is meaningless if jitter is high. For most workloads, consistent 50 ms latency is better than 20–100 ms fluctuations, because predictable behaviour lets you optimise code, set reliable timeouts, and build retry logic.

99.9% uptime

Look for a 99.9% (or higher) uptime SLA on dedicated setups, with defined incident response, automatic failover, clear escalation paths, and a clear maintenance and health-checks policy. Uptime is what protects you from missed execution and degraded UX during volatile markets.

Direct engineering support

Evaluate who you speak to when something breaks. Support should be a direct channel for configuration guidance, integration debugging, and urgent troubleshooting, not a generic ticket loop. With Triton, you get it directly from the engineers who built the stack Solana relies on (Yellowstone gRPC, Old Faithful).

Ultra-low latency

For latency-sensitive systems, the goal is lower tail latency and fewer hops, not just a good average. Triton reduces end-to-end delay with global placement close to validator clusters, plus gRPC streaming for real-time data. Dragon’s Mouth streams updates as soon as the node begins receiving shreds for a slot, before replay finishes, so you see events earlier than polling-based approaches.

Tooling and features beyond JSON-RPC

JSON-RPC endpoints are the baseline, but you should also consider the need for additional tooling to optimise your workload and remove bottlenecks.

gRPC streaming

For real-time data ingestion, polling is slow and becomes expensive at scale. Streaming pushes updates immediately as state changes, giving you a 400ms+ advantage. Most of the ecosystem’s streaming layer is built on Yellowstone gRPC, (an open-source standard authored by Triton) which allows you to easily switch between providers.

Improved priority fees

Solana’s default getRecentPrioritizationFees method reflects recent minimums (often 0), making it an unreliable signal for landing, especially during congestion. Improved calculation APIs provide more actionable estimates, helping you set fees more accurately and reduce failed, or delayed, transactions.

Custom indexes

If your app relies on heavy reads like getProgramAccounts, overall performance will often depend on removing that bottleneck. Look for providers that build indexes tailored to your query patterns (like Triton’s Steamboat), so common filtered requests return dramatically faster.

Dashboards

You need enough visibility into your RPC performance to diagnose issues fast and rule out RPC causes early. Look for method-level metrics across every product you use, including real-time RPS, error rates, latency percentiles, and real-time streaming health.

Turnkey access to advanced APIs

Many “hard problems” already have production-grade APIs. For retrieving NFTs and assets, a DAS API can replace complex indexer work with a single call. For swaps, routing APIs like Metis and Titan can simulate, quote, and return ready-to-sign transactions. The main job is knowing what you need, and ensuring your provider supports it.

Archive depth

If you require historical transactions, compliance audits, analytics, or backtesting, ensure your provider offers full-chain archival access, not a limited lookback window. For example, Triton’s Old Faithful (the only complete, verified, and public Solana history archive) exposes both standard JSON-RPC and gRPC interfaces for Solana history. Faithful Streams lets you replay the ledger sequentially as a high-speed, high-throughput feed, making it perfect for backfills and state rebuilds.

Pricing models and cost control

This is where many teams get confused. Credit and compute unit systems look simple at first, but make it near-impossible to forecast spend. Fixed tiers represent the opposite trap: they create painful overage cliffs, often forcing you to over-provision capacity by 2x or 3x just to absorb a single traffic spike without triggering punitive rates.

Credits and CUs problem

Many providers bill in credits or compute units, where a basic call costs 1 credit and a filtered query might cost 100. That means “50 million credits” shrinks to a small fraction of that in real requests if you rely on program account queries or historical reads. For enterprise teams, the biggest risk is unpredictability, and surprise overage bills when traffic spikes.

Transparent billing

Look for pricing that maps to real cost drivers, like bandwidth and compute complexity, with rates you can model. Usage-based billing stays predictable when the dimensions are simple, and overages are billed at the same base rate. The goal is to know what will happen before you ship, not after you are already in production.

Avoid vendor lock-in.

Proprietary SDKs and non-standard APIs create hidden switching costs. Once your code depends on provider-specific behaviour, switching can turn into a multi-month engineering project. Stick to providers that use standard APIs and open-source tooling, so you keep control and can change providers without rewriting your stack.

Shared vs dedicated RPC infrastructure

The hybrid model

Most enterprises run on both dedicated and shared infrastructure.
Dedicated nodes are used for critical backend workloads such as streaming and indexing, while shared RPCs handle user-facing traffic and standard reads.

Final takeaway

On Solana, your infrastructure decisions directly shape user experience. An unreliable RPC is visible immediately through lag, errors, failed transactions, or lost profits.

That’s why you must choose infrastructure that delivers consistent performance, mission-critical reliability, and fast engineering support, not just attractive benchmarks.