☁️ Real-Time Streaming: Pub/Sub, Dataflow Prime & Apache Beam | The Google Cloud Podcast

!Wday' episode,host Bitu explores modern event-riven stream processing and real-ime data pipelines on Google Cloud Platform (CP:•/:-/,(/),,-()•&:,,,-("-")•,&:,,,--,, .)gerstni yltcerid noitsegni lacitylana gnimaerts ecno-yltcaxe dna maertsataD htiw CDC lanoitcasnart dnoces-buS :IPA etirW egarotS & )CDC( erutpaC ataD egnahC • !,, :• oWelcome to The Google Cloud Podcast! In today's episode, host Bitu explores modern event-driven stream processing and real-time data pipelines on Google Cloud Platform (GCP). Key Topics Covered: • Google Cloud Pub/Sub: Global event ingestion at multi-GB/s scale, schema enforcement (Protobuf/Avro), message ordering keys, and dead-letter queues (DLQ) • Dataflow Prime & Apache Beam: Unified streaming model, dynamic work rebalancing, liquid sharding, and stage-level vertical autoscaling ("Right-fitting") • Event Time, Watermarks & Windowing: Fixed, Sliding, and Session windows, managing out-of-order data, allowed lateness, and Accumulating vs Retracting triggers • Change Data Capture (CDC) & Storage Write API: Sub-second transactional CDC with Datastream and exactly-once streaming analytical ingestion directly into BigQuery • Certification Insights: Essential streaming pipeline patterns and common traps for the Google Cloud Professional Data Engineer and Cloud Architect exams Subscribe to The Google Cloud Podcast for regular GCP architectural breakdowns, practical engineering tutorials, and cloud certification strategies!