Geetha Anne
Exploring Durable Execution with Python
#1about 5 minutes
The challenge of managing modern distributed systems
Modern distributed systems are powerful but their complexity makes them prone to failures that are difficult to recover from.
#2about 2 minutes
Introducing Temporal for durable execution
Temporal.io is an open-source framework that simplifies complex systems and improves reliability through a concept called durable execution.
#3about 6 minutes
Understanding Temporal workflows and activities
Applications are built using deterministic workflows for business logic and activities for executing individual, potentially fallible tasks.
#4about 4 minutes
How durable execution handles process failures
Durable execution captures the complete state of a function, allowing it to be seamlessly migrated and resumed on another server after a crash.
#5about 4 minutes
Exploring the key capabilities of the Temporal framework
The framework includes built-in features like auto-save, native retries, durable timers, schedules, and signals for human-in-the-loop processes.
#6about 4 minutes
Understanding the architecture of a Temporal application
Developers deploy code to workers that poll the Temporal server for tasks, which in turn captures and stores the complete execution state.
#7about 5 minutes
Implementing a workflow with the Python SDK
A practical example shows how to define a workflow, create activities, implement worker logic, and use a client to send signals.
#8about 4 minutes
Using durable primitives with asyncio in Python
The Python SDK provides durable versions of asyncio primitives like timers, tasks, and cancellations that survive process crashes.
#9about 2 minutes
Advanced SDK features and activity execution styles
The Python SDK is backed by a Rust core and supports multiple activity styles including async, threaded, and multi-process executors for different use cases.
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