Documents compute, memory, and storage requirements for a production deployment: ~100-150M NLRI estimate, 96-128 GB RAM, 16-32 vCPU, 3-5 TB NVMe, a split-host architecture option, PostgreSQL tuning, and a BMP RIB-scope recommendation (Adj-RIB-In only initially). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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OpenBMP Production Sizing — 40 Full-Table-Edge Routers
Sizing guidance for deploying the OpenBMP stack against a production ISP
network of 40 full-table-edge routers with gNMI streaming telemetry.
Derived from the OpenBMP psql-app sizing guidance and measured lab behavior.
Workload assumptions
| Parameter | Value |
|---|---|
| Monitored routers | 40, full-table edge |
| BMP RIB scope | Adj-RIB-In (see recommendation below) |
| Full feeds per router | ~2–3 eBGP peers carrying the full DFZ |
| Routes per full feed | ~1.2M (≈1M IPv4 + ~0.2M IPv6) |
| Estimated total NLRIs | ~100–150M in Adj-RIB-In |
| Telemetry | gNMI via Telegraf → InfluxDB, ~50–200 interfaces/router, 10 s interval |
| History retention | ip_rib_log 4 weeks, LS logs 4 months, peer_event_log 1 year |
The NLRI estimate (40 × ~2.5 feeds × 1.2M) places this deployment at the top
of the OpenBMP psql-app guidance tier (150M NLRIs → 64 GB heap).
BMP RIB scope — recommendation
Deploy with Adj-RIB-In only. It is the OpenBMP default, is what every dashboard is built on, and captures the highest-value data — what each peer advertises. Alternatives and their cost:
- Loc-RIB — adds a full post-best-path converged table per router (~40 × 1.2M ≈ +48M NLRIs). Add later, selectively, only where best-path analysis is needed; verify the IOS-XR release supports Loc-RIB BMP.
- Adj-RIB-Out — multiplies further (per advertised peer). Not recommended for the initial deployment.
- Post-policy Adj-RIB-In — if inbound policy is restrictive this trims volume meaningfully; with permissive import it is similar to pre-policy.
Compute & memory
| Component | Lab today | Production target | Rationale |
|---|---|---|---|
| Total RAM | 31 GB | 96–128 GB | psql-app heap 48–64 GB + PostgreSQL shared_buffers/cache + Kafka 4–8 GB + InfluxDB + Grafana + collector |
| CPU | 8 cores | 16–32 vCPU | PostgreSQL is CPU-bound under full-table churn — lab psql already sustains ~287% (3 cores) at 18 routers |
psql-app JVM heap (MEM) |
3 GB | 48–64 GB | OpenBMP guidance: 4 GB ≈ 10M NLRIs, 64 GB ≈ 150M NLRIs |
psql-app container mem_limit |
4 GB | heap + ~8 GB | Set PSQL_APP_MEM_LIMIT above the JVM heap |
psql container mem_limit |
6 GB | 48–64 GB | Set PSQL_MEM_LIMIT; PostgreSQL wants ~25% as shared_buffers and the rest for OS cache |
kafka container mem_limit |
4 GB | 8–12 GB | Set KAFKA_MEM_LIMIT; full-table initial dumps from 40 routers are bursty |
Storage
| Store | Lab today | Production target | Notes |
|---|---|---|---|
| PostgreSQL | 25 GB | 2–4 TB NVMe SSD | ip_rib current state (~100–150M rows) + ip_rib_log history (4-week retention, the dominant grower) + base_attrs + geo_ip (~7 GB fixed). OpenBMP guidance: 500 GB main + 1 TB TimescaleDB; add headroom. |
| Kafka | 0.2 GB | 100–500 GB | 12 h retention; sized for full-table initial-dump bursts × 40 routers |
| InfluxDB (telemetry) | minimal | 50–200 GB | 40 routers × ~50–200 interfaces × 10 s gNMI × 30 d; compresses well |
| Total | — | ~3–5 TB fast NVMe | Use NVMe; PostgreSQL random-IO under churn is the bottleneck on slow disks |
Put the PostgreSQL data directory and the TimescaleDB tablespace on NVMe.
ip_rib_log 4-week retention is the main storage tuning knob — revisit once
production update volume is measured.
Architecture
A single host is viable only if large (≥128 GB RAM, ≥32 vCPU, multi-TB NVMe). Preferred: split services across hosts —
| Host | Services | Profile |
|---|---|---|
| DB host (heaviest) | postgres | — |
| Pipeline host | kafka, zookeeper, collector, psql-app | core |
| Presentation host | grafana, influxdb, telegraf, whois | core + telemetry |
Whichever layout: every service already carries a Compose mem_limit — raise
PSQL_MEM_LIMIT / PSQL_APP_MEM_LIMIT / KAFKA_MEM_LIMIT in .env for the
production hosts.
PostgreSQL tuning
shared_buffers≈ 25% of host RAM; largeeffective_cache_size.- Raise
work_mem(dashboard aggregate queries) andmaintenance_work_mem. max_wal_sizealready 10 GB — keep or raise for churn bursts.- Enable parallel query (
max_parallel_workers_per_gather). - Aggressive autovacuum on churn tables (
ip_rib,base_attrs,ip_rib_log) — applied in the lab; persist these settings in production provisioning. - TimescaleDB compression is already enabled on
ip_rib_logand thestats_*hypertables — keep it.
Reference bill of materials (single-host option)
| Resource | Spec |
|---|---|
| CPU | 32 vCPU |
| RAM | 128 GB |
| Storage | 4 TB NVMe SSD |
| Network | 1 GbE+ to the routers' BMP source network |
For the split-host option, divide per the architecture table — the DB host takes the bulk of RAM and all of the fast storage.