You're responsible for data pipelines that ingest customer integration data and need a way to spot issues early. Different integrations may arrive through APIs, file drops, or scheduled extracts, so failures can show up as missing data, malformed records, or delayed processing.
How would you design a process to monitor customer integrations and catch failures quickly?
Expected file or API payload never arrivesData arrives late and misses downstream SLA windowsSchema changes break parsing or loadingVolume drops or spikes indicate partial deliveryDuplicates appear after retries or replayIngestion events in TruIQ Data Ingestion ServicesKafka topic lag and DLQ growthSpark validation and processing metricsSnowpipe load audit tables in SnowflakeCurated health dashboards in TruIQ