Confluent and Sentry, Connected

Stream Sentry error events through Confluent Kafka topics to power real-time alerting, incident routing, and observability workflows across your entire stack.

What You Can Automate

Stream Sentry error events into Confluent Kafka topics for real-time incident routing

Aggregate Sentry error rates per release version using Kafka stream processing

Replay historical Sentry error events from Confluent for post-incident root cause analysis

Why Connect Confluent and Sentry

Sentry captures errors and performance issues across your applications in real time. Confluent provides a fully managed Kafka platform built for high-throughput event streaming. When you connect the two, every exception, crash report, and performance alert becomes a first-class event in your data pipeline.

This integration means your engineering and ops teams no longer need to poll Sentry dashboards or build fragile webhook chains. Error events flow directly into Kafka topics where any downstream consumer can act on them instantly.

What Neotask Makes Possible

Neotask orchestrates the connection between Confluent and Sentry without requiring custom connector code or manual infrastructure setup. Key capabilities include:

• Automatic error ingestion: Sentry issues and exceptions are published to Confluent topics as structured JSON events as soon as they trigger.
• Topic routing by severity: Route fatal, error, and warning events to separate Kafka topics, enabling different consumer groups to handle incidents at the right priority level.
• Real-time consumer integration: Downstream systems such as PagerDuty, Slack, or internal dashboards consume Kafka topics to take immediate action on new Sentry events.
• Historical replay: Kafka's durable log means you can replay Sentry error streams for post-incident analysis, anomaly detection model training, or compliance auditing.
• Cross-service correlation: Tag Kafka messages with Sentry release versions and environment metadata so consumers can correlate errors with deployments.

Common Workflow Patterns

Incident Escalation Pipeline

Sentry detects a spike in unhandled exceptions. The event publishes to a Confluent errors.critical topic. A stream processor filters events exceeding a threshold and triggers automated incident creation in your ticketing system.

Release Quality Tracking

Every Sentry event carries a release tag. Publishing these to Confluent lets a downstream consumer aggregate error rates per release version, feeding a quality gate that can halt further deployments when error budgets are exceeded.

Multi-Region Observability

Confluent's global replication replicates Sentry error topics across regions. Central observability teams get a unified view of errors from services deployed in multiple cloud regions without needing separate Sentry integrations per region.

Benefits at a Glance

• Eliminate manual polling and fragile webhook setups between Sentry and downstream systems
• Gain durable, replayable error event history through Kafka's log retention
• Scale error processing independently from your application layer using Kafka consumer groups

Getting Started

Neotask connects to both your Confluent cluster and your Sentry organization through secure credential management. Once connected, you define which Sentry projects to stream and which Confluent topics to publish to. No custom code is required to get the pipeline running.

Pro Tips

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Real-time error event streaming from Sentry into your Kafka data pipeline without custom connector code

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Durable Kafka log retention enables error replay, auditing, and downstream analytics at scale

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Decoupled architecture lets multiple consumer systems act on Sentry errors independently and simultaneously

Start automating Confluent + Sentry

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Plans

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• Confluent
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