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Intro
What we’ll cover in the video
What can Dataflow bring to your business?
Dataflow Advantages
How do you start using Dataflow?
Windowing
[Demo] Dataflow Demo Architecture
[Demo] Dataflow Templates Demo
[Demo] Dataflow Apache Beam Pipeline Demo
How do you observe and monitor your pipelines?
How do you optimize and scale your pipelines?
How are other customers using Dataflow?
Wrap up!
Intro
Series review
The problem
Overview of the different methods
Data ingestion principles
Dataflow overview
Dataflow: when to use/ when not to use
Dataflow: implementation notes
Data pipeline overview
Pipelines: when to use/ not to use
Pipelines: implementation notes
Notebooks overview
Notebooks: when to use/ not to use
File/database replication overview
Shortcuts overview
Internal shortcut limitations
Shortcuts: implementation notes
Database mirroring overview
What to consider when choosing a method
Evolution of data and the value gap
Why Dataflow?
What is Dataflow?
What is observability?
Job visualizers
Job metrics
Cloud Error Reporting integration
Cloud Profiler integration
Dataflow insights (recommendations)
Datadog integration
Where to start?
Live demo
Job slows down with increase in data volume
Quota issues, throttling
OOMs (out of memory)
Hot keys, uneven CPU load across workers
User code issues
Job failed to start
Job is not autoscaling as expected
Dataflow observability roadmap
Intro
How to identify if Dataflow job is slow or stuck
How to use Cloud Logging for troubleshooting slow/stuck jobs
Troubleshoot and resolve slow/stuck jobs due to workers taking long processing time
Troubleshoot and resolve slow/stuck jobs if processing is stuck in Write Files
Troubleshoot and resolve slow/stuck jobs due to hot key issues
Troubleshoot and resolve slow/stuck jobs caused due to OOM errors
Troubleshooting Guide