A typical application may rely on several independent systems.

RPC infrastructure provides access to blockchain nodes.

Indexers transform raw blockchain data into something applications can query efficiently.

Oracles bring external data such as prices, weather, or real-world events on-chain.

Data availability layers make transaction data accessible for rollups and other scaling systems.

Bridges move assets or messages between networks.

Sequencers order transactions in many Layer 2 architectures.

Each component introduces its own trust assumptions and failure modes.

This creates an interesting question: when we call an application “decentralized”, how much of its supporting infrastructure also needs to be decentralized?

An application might use decentralized smart contracts but depend on a centralized front end, centralized RPC provider, centralized sequencer, and a small oracle set.

Technically decentralized does not always mean operationally decentralized.

Which infrastructure layer do you think receives too little attention from users and developers today?

My guess would be RPC infrastructure and indexing, because most users never see those layers until something stops working.

That can become expensive later.

For a production Web3 application, I would evaluate infrastructure across several dimensions.

Reliability

Uptime is important, but failover behavior matters just as much.

Latency

For trading, gaming, wallets, and real-time applications, RPC response time can materially affect user experience.

Chain coverage

Supporting multiple networks becomes much easier if one infrastructure provider covers the entire stack.

Historical data

Some applications need archive nodes or deep historical queries, which can dramatically increase infrastructure requirements.

Rate limits and scaling

A provider that works perfectly at 10,000 requests per day may become expensive at several million.

Data consistency

Different RPC endpoints can occasionally return data at slightly different chain states.

Observability

Logs, request analytics, error tracking, and performance monitoring are underrated until something breaks.

Vendor lock-in

Building everything around proprietary APIs can make migration painful later.

For early-stage projects, simplicity probably matters more than maximum decentralization. But infrastructure decisions become much more important once real users and money are involved.

For developers here: what are the three most important factors you look at when choosing RPC or blockchain infrastructure providers?

Price, latency, reliability, decentralization, supported chains, or something else?

This is becoming one of the more interesting contradictions in Web3.

Users may interact with decentralized applications, but those applications often depend on a relatively small number of:

• cloud providers;
• RPC services;
• indexing platforms;
• node hosting companies;
• API providers;
• data availability services.

If a large percentage of an ecosystem relies on the same infrastructure providers, an outage at one company can affect dozens or hundreds of applications simultaneously.

This also creates regulatory and censorship concerns.

Imagine a network with thousands of independent validators, but most wallets and dApps query blockchain data through only a few large RPC providers. Consensus may remain decentralized, while access to the chain becomes much more concentrated.

This does not necessarily mean centralized infrastructure is bad. Economies of scale make these services faster and cheaper.

But decentralization probably needs to be evaluated across multiple layers:

consensus → hosting → RPC → indexing → front-end access.

Which layer do you think is currently the biggest centralization risk?

And are decentralized RPC networks actually becoming competitive enough to solve this problem?

Most Web3 applications start with third-party RPC providers because it is faster, cheaper, and operationally simpler than maintaining blockchain nodes internally.

That approach works well until RPC infrastructure becomes a critical dependency.

The main trade-off is straightforward.

Third-party RPC providers offer:

• fast deployment;
• global infrastructure;
• automatic scaling;
• built-in monitoring;
• support for multiple chains;
• lower DevOps overhead.

But they also introduce:

• rate limits;
• vendor dependency;
• potential censorship or filtering;
• privacy concerns;
• unpredictable costs at scale;
• a single external failure point.

Self-hosting gives much more control, but operating reliable blockchain infrastructure is not trivial. You need redundancy, monitoring, snapshots, storage planning, failover logic, and engineers who understand node behavior.

For production systems, the most sensible architecture may be hybrid: internal nodes for critical workloads, with external RPC providers as fallback or load-balancing capacity.

The question is where the threshold sits.

At what point should a Web3 project stop relying entirely on public RPC infrastructure and start running its own nodes?

Would you base that decision on traffic volume, monthly RPC costs, privacy requirements, or business criticality?