Building Resilient Streaming Analytics Systems on Google Cloud (BRSAS) – Contenuti

Contenuti dettagliati del Corso

Module 1 - Introduction to Processing Streaming Data

Topics:

  • Introduction to processing streaming data

Objectives:

  • Explain streaming data processing.
  • Describe the challenges with streaming data.
  • Identify the Google Cloud products and tools that can help address streaming data challenges.

Module 2 - Serverless Messaging with Pub/Sub

Topics:

  • Introduction to Pub/Sub
  • Pub/Sub push versus pull
  • Publishing with Pub/Sub code

Objectives:

  • Describe the Pub/Sub service.
  • Explain how Pub/Sub works.
  • Simulate real-time streaming sensor data using Pub/Sub

Module 3 - Dataflow Streaming Features

Topics:

  • Steaming data challenges
  • Dataflow windowing

Objectives:

  • Describe the Dataflow service.
  • Build a stream processing pipeline for live traffic data.
  • Demonstrate how to handle late data by using watermarks, triggers, and accumulation.

Module 4 - High-Throughput BigQuery and Bigtable Streaming Features

Topics:

  • Streaming into BigQuery and visualizing results
  • High-throughput streaming with Bigtable
  • Optimizing Bigtable performance

Objectives:

  • Describe how to perform ad hoc analysis on streaming data using BigQuery and dashboards.
  • Discuss Cloud Bigtable as a low-latency solution.
  • Describe how to architect for Bigtable and how to ingest data into Bigtable.
  • Highlight performance considerations for the relevant services.

Module 5 - Advanced BigQuery Functionality and Performance

Topics:

  • Analytic window functions
  • Geographic Information System (GIS) functions
  • Performance considerations

Objectives:

  • Review some of BigQuery’s advanced analysis capabilities.
  • Discuss ways to improve query performance.