Assign validators, RPC nodes, indexers, application backends, observability, and recovery roles to dedicated servers with defined CPU, memory, storage, bandwidth, regional placement, and failure domains.
Match each node or service to dedicated CPU, memory, storage I/O, bandwidth, and measurable capacity headroom.
Separate stateful, public-facing, and recovery roles when contention or a shared outage would widen operational impact.
Choose regions around peer routes, user demand, operator access, replication paths, and the planned recovery topology.
Plan reserve capacity for state growth, synchronization, re-indexing, retention, backups, and routine restore testing.
A production estate rarely behaves like one workload. Validators, RPC and API nodes, indexers, application services, observability, staging, and recovery each create different pressure on CPU, memory, storage I/O, and bandwidth. The first decision is architectural: define role boundaries, failure impact, and recovery ownership before selecting hardware.
At Melbicom, we help teams assign those roles to isolated hardware with selectable CPU, memory, storage, bandwidth, and regional placement. Ready-to-deploy configurations cover common starting points, while custom builds support topologies that need a different bill of materials. Our 24/7 technical support covers the server and network layer.
Treat that capacity as an operating model, not a server list: consolidate compatible roles to limit infrastructure overhead, isolate stateful or public-facing functions where recovery demands it, and reserve headroom for synchronization, re-indexing, retention, backups, and restore tests. Your team retains control of software, keys, data, and protocol policy.
Give validators isolated compute and storage, then keep recovery capacity outside the primary failure domain.
Separate public RPC and API traffic from stateful peers so latency, contention, and failure impact stay measurable.
Size CPU, memory, and storage I/O for sustained ingestion, re-indexing, retention, and production API query pressure.
Give dApp backends their own capacity envelope, regional placement, and rollback headroom without hiding node contention.
Keep monitoring and log retention separate to preserve telemetry during production recovery and resynchronization.
Reserve compute and scratch storage for analytics, exports, and batch jobs without competing with live node state.
Mirror production-like topology in staging so upgrades, re-indexing, and restore procedures are tested before deployment.
Keep recovery capacity independent for synchronization, data restoration, and regional failover drills under realistic load.
