Is it possible to implement idempotency in my Rails webhook consumer when Genesys Cloud EventBridge sends duplicate events? I observe identical event_id values arriving seconds apart, causing Sidekiq to process the same interaction twice. This breaks my state machine logic.
My current Faraday middleware verifies signatures but ignores duplicates. Should I check the x-gc-event-id header against a Redis cache before queuing the ActiveJob? Or is there a server-side deduplication setting I am missing?
Check your event_id handling in the middleware. Don’t just ignore duplicates; validate the signature first, then use a Redis set with a short TTL (e.g., 5 minutes) to track processed IDs. This prevents Sidekiq from re-queueing the same job. Here is the Node.js pattern I use for this exact issue:
Yep, this is a known issue… especially when dealing with high-volume interaction streams. I see the previous suggestion focuses on Redis, which is solid, but if you are already using Sidekiq, you can leverage its built-in deduplication mechanisms to avoid adding external Redis complexity.
In my PagerDuty SLA escalation pipeline, I use the sidekiq-unique-jobs gem. It allows you to define uniqueness constraints directly on the job class. You can set the unique: :until_executed option and use the x-gc-event-id as the lock key. This ensures that if the same event ID arrives during processing or within a configured lock timeout, Sidekiq will not enqueue a duplicate job.
Here is how I configure the ActiveJob wrapper for Genesys Cloud events:
class ProcessGenesysEventJob < ApplicationJob
queue_as :default
sidekiq_options lock: :until_executed, lock_ttl: 300 # 5 minutes TTL
def perform(event_payload)
event_id = event_payload['id']
# Ensure the job is uniquely identified by the Genesys Cloud event ID
self.class.unique_args(event_id)
# Your business logic here
end
end
This approach keeps your middleware lightweight. You still verify the x-gc-signature header first, but the deduplication happens at the queue level. It works reliably for our webhook consumers in São Paulo, handling the occasional retry bursts from the Genesys Cloud EventBridge without breaking our state machines. Just ensure your lock_ttl covers the maximum expected processing time plus a buffer for network latency.
This is actually a known issue… The Redis approach is correct, but you must set the TTL to match your EventBridge retry window, typically 5 minutes, to avoid premature cache eviction.
redis.setex("gc_event:#{event_id}", 300, 1)
Sidekiq deduplication adds unnecessary latency for high-throughput WFM syncs. Stick to the header check.
It’s worth reviewing at the race condition inherent in the SADD + EXPIRE pattern when scaling beyond a few hundred events per second. While Redis is fast, the network round-trip for every single event adds latency that your Vue dashboard’s real-time queue metrics will expose as jitter. If you are building a high-throughput consumer, you are better off using a Lua script to atomically check and insert the ID. This ensures that even if two identical events arrive within the same millisecond tick, only one is processed.
Here is a robust Lua implementation for the deduplication logic:
local event_id = KEYS[1]
local ttl = ARGV[1]
local exists = redis.call('EXISTS', event_id)
if exists == 1 then
return 0
end
redis.call('SET', event_id, 1, 'EX', ttl)
return 1
In your Rails middleware, execute this via redis.eval(script, keys: [event_id], args: [300]). If it returns 0, you know it’s a duplicate. If it returns 1, proceed to queue the Sidekiq job. This removes the TOCTOU (Time-of-Check to Time-of-Use) vulnerability present in standard SISMEMBER checks.
Also, be careful with the x-gc-event-id header. It is not always present on legacy integration events. Always fallback to generating a hash of the payload body if the header is missing, otherwise you will miss legitimate retransmissions.
Warning: Do not set the TTL too high. 300 seconds is sufficient for EventBridge retries. Setting it to 24 hours will cause memory bloat in Redis and false positives for recurring daily reports.