When a 50k TPS batch of AEPS disbursements stalls, the problem isn’t the database – it’s a sprawling micro‑service mesh that lost the core settlement signal.
Fix the signal path first; everything else is just noise.
Why a Event‑Sourced Core Beats a Chained Microservice Stack
In production, we saw a Tier‑2 bank’s BBPS gateway collapse under a 30% traffic surge because each service added its own retry layer. The result: duplicated state and exponential back‑off storms.
Event sourcing keeps the immutable ledger as the single source of truth, letting downstream services replay without re‑querying the DB.
- Write once to an append‑only log (Kafka, Pulsar)
- Read side‑cars subscribe only to relevant event types
- Replayability reduces hot‑spot contention by 70%
Never let a retry policy become a retry storm – cap retries at three and let the event log handle eventual consistency.
How to Wire AEPS and BBPS for 50k+ TPS
Start with a dedicated event hub, shard by transaction type, and bind each shard to a stateless processing pool.
Step‑by‑step implementation
- Deploy a Kafka cluster with 12 partitions per region.
- Use Go microservices with net/http and gRPC for low‑latency RPC.
- Persist events to a Cassandra table keyed by transaction_id.
- Enable back‑pressure via Reactive Streams to avoid queue overflow.
Our own AEPS and Aadhaar payment infrastructure runs this stack and consistently delivers 55k TPS during peak settlement windows.
What the Monitoring Dashboard Should Actually Show
Forget generic latency graphs. Show three metrics:
- Event lag per partition – must stay under 200 ms.
- Settlement signal integrity – a checksum of the core ledger.
- Retry count per service – spikes indicate architecture drift.
When any of these cross thresholds, cut traffic and trigger the fail‑over path.
Is Horizontal Scaling Enough?
No. Adding more instances of a broken service just spreads the bug.
We default to a domain‑driven design where each bounded context owns its own event stream. That isolates failures and lets you scale independently.
Can I reuse the same architecture for other fintech APIs?
Absolutely. The same event‑sourced pattern powers our instant payout and disbursement APIs and scales without rewrites.
How do I ensure compliance with RBI’s AEPS guidelines?
Store all event logs immutably for 12 months and encrypt at rest. Use tokenized Aadhaar numbers – never raw IDs.
What’s the simplest way to get started?
Reach out for a technical deep‑dive; we’ll provision a sandbox with our technical consultation and get your first event flow running in a week.
Bottom line: lock the settlement signal in an immutable event stream, cap retries, and let micro‑services stay truly stateless. That’s the only way to guarantee high‑concurrency for AEPS and BBPS.