TopicWatch continuously checks the content of your Kafka topics: schema drift, null fields, malformed payloads, volume anomalies, DLQ spikes and real consumer lag. One read-only container, alerts in Slack.
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field currency changed int → string (producer: checkout-svc)
+412 msgs/h (baseline 6/h) — sample attached
amount null in 3.1% of msgs (threshold 1%)
2,140 → 87 (markers excluded)
Prometheus, Grafana and your cloud console watch brokers, partitions and lag. None of them open a single message. That's how broken data ships for days.
A field renamed upstream breaks consumers downstream — days later. TopicWatch baselines schemas per topic and alerts on every change, with a drift timeline.
Dead-letter queues fill quietly until a customer complains. Get inflow alerts with sample payloads the moment it starts.
Transactional markers inflate consumer lag and trigger ghost pages. TopicWatch reports real lag per partition.
Connects as a standard read-only Kafka consumer. No broker agents, no proxy in the data path, no code changes.
Schemas inferred automatically (JSON) or pulled from your registry (Avro/Protobuf). Baselines build themselves.
Slack, Discord, e-mail or webhook. Thresholds per topic, quiet by default.
# self-hosted: payloads and metrics never leave your network
docker run -d --name topicwatch \
-e KAFKA_BOOTSTRAP=broker1:9092 \
-e TOPICS=orders.v2,payments.events,orders.dlq \
-p 8080:8080 topicwatch/topicwatch:latest
Built for teams of 5–50 engineers. Your whole team included — adding people never raises your bill.
No. TopicWatch is self-hosted — payloads and metrics stay inside your infrastructure. The only outbound call is license validation.
It's a standard read-only consumer with its own consumer group and least-privilege ACLs. It can't produce, change configs or commit offsets for other groups.
Avro/Protobuf via Confluent, Karapace or Apicurio registries. JSON topics are inferred automatically — no registry needed.
UIs help you browse and manage. TopicWatch is monitoring: it watches message content 24/7 and tells you when something breaks — before your consumers find out.