Outage in Iterable
Customers on c102 are experiencing degraded performance
Resolved MinorIncident Report
Summary AI Generated
Iterable's c102 Elasticsearch cluster went into a red state, causing widespread API 500 errors, failed searches, and near-zero data ingestion rates with up to 20-minute delays across multiple pipelines. Customers experienced failures across multiple API endpoints and search functionality. Engineering restored the cluster to green state and cleared all backlogs within 1.3 hours, returning all services to normal operation.
We are currently investigating an issue for one of ES clusters - c102 - The cluster is in a red state, leading to very slow ingestion and widespread API 500 errors.
Customers are experiencing failed searches and errors on multiple API endpoints. Ingestion rates are near zero, with lag up to 20 minutes and increasing for internal, realtime, and bulk data pipelines.
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Latest Updates ( sorted recent to last )
RESOLVED
19 minutes ago - at 03/17/2026 07:21PM
We have fully caught up with any backlog on C102 and all queries and activity through C102 are functioning normally. If you continue to experience any issues please contact Support.
MONITORING
39 minutes ago - at 03/17/2026 07:00PM
Engineering has restored C102 back to a "green" state and ingestion and API calls are succeeding again for this cluster. We will continue to monitor until we are fully through the accumulated backlog. Next update at 1 PM PDT or sooner.
INVESTIGATING
about 1 hour ago - at 03/17/2026 06:43PM
Engineering is continuing to investigate this issue. At this time there is no improvement yet to any customers on C102. Next Update at 12:15 PDT or sooner.
INVESTIGATING
about 2 hours ago - at 03/17/2026 06:07PM
We are currently investigating an issue for one of ES clusters - c102 - The cluster is in a red state, leading to very slow ingestion and widespread API 500 errors.
Customers are experiencing failed searches and errors on multiple API endpoints. Ingestion rates are near zero, with lag up to 20 minutes and increasing for internal, realtime, and bulk data pipelines.
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