Defimon: Real-Time DeFi Security with Streams

Legacy streaming data pipelines are hard to adapt to the onchain monitoring

Defimon tracks millions of wallet addresses and contract interactions in real-time. Their original setup, Apache Flink SQL pipelines running on AWS, held this watchlist in memory. As coverage expanded, out-of-memory errors became a trigger to look for the alternatives. The system couldn't scale with the scope of what needed monitoring.

$4,000 a month for 3 chains, with a team of 4 to keep it running

Infrastructure cost approximately $4,000 per month on AWS to cover just three networks and required three to four engineers: pulling RPC data manually, managing SQL schemas, debugging pipeline failures. The team's expertise was in detection logic. They were spending it on infrastructure plumbing.

Block latency that degraded alert quality

Manual RPC polling produced around two seconds of latency per block. For a product where detection timing determines whether a protocol team gets warned in time, that was a structural problem.

Defimon replaced their self-managed pipeline with Quicknode Streams. The migration was near-instant. Existing detection logic carried over, and the team was up and running without having to rebuild from scratch.

The memory problem, solved at the source

Streams' upstream filtering and native integrations with Key-Value Store lists lets Defimon define exactly which data reaches their system, by address, contract, or event type, before it ever touches their pipeline. The watchlist no longer lives in RAM as a growing, crashing list. Adding or removing monitored addresses became a configuration change, not an engineering task.

One pipeline. Eight chains.

Ethereum, BNB Smart Chain, Arbitrum, Base, Polygon, Avalanche, Optimism, and HyperEVM all run through a single Streams integration. Adding a new chain no longer means new infrastructure. It means updating a config. The team went from three chains managed across a fragmented AWS setup to eight chains managed by one person.

Push data, not polling

Replacing manual RPC calls with Streams' push model cut block latency from around two seconds to under 0.5 seconds. Telegram exploit alerts now fire in under one second.

4x faster detection

Block latency dropped from around two seconds to under 0.5 seconds per block. Telegram alerts fire in under one second from detection.