Temporal Workflow Orchestration FAQs

Question 1

What is the primary difference between a Workflow and an Activity?

Accepted Answer

Workflows handle orchestration logic and must be deterministic (same input always equals same output), while Activities handle external interactions like API calls or database writes which can be non-deterministic.

Question 2

How does the skill ensure external API calls are safe?

Accepted Answer

It guides you in wrapping API calls within Activities and implementing idempotency logic, ensuring that if a call is retried due to a network failure, it does not result in duplicate side effects.

Question 3

Is this skill suitable for high-scale data processing?

Accepted Answer

While Temporal is highly scalable, this skill is optimized for orchestration and business logic. For pure data pipelines or streaming, tools like Airflow or Kafka are typically more appropriate.

Question 4

How does this skill handle distributed transaction failures?

Accepted Answer

It implements the Saga pattern, where each forward action has a corresponding compensation action registered. If a step fails, the workflow automatically executes compensations in reverse order to maintain consistency.

Question 5

Why can't I use standard system time or random numbers in a Workflow?

Accepted Answer

Temporal recovers state by replaying workflow code. If non-deterministic functions like datetime.now() are used, the replay will produce different results than the original execution, causing a non-determinism error.

Temporal Workflow Orchestration

Temporal Workflow Orchestration

Key Features

Use Cases

Key Features

Use Cases