7e5abd504f
Add three DBOS SDK skills with reference documentation for building reliable, fault-tolerant applications with durable workflows. Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
1.3 KiB
1.3 KiB
title, impact, impactDescription, tags
| title | impact | impactDescription | tags |
|---|---|---|---|
| Keep Workflows Deterministic | CRITICAL | Non-deterministic workflows cannot recover correctly | workflow, determinism, recovery, reliability |
Keep Workflows Deterministic
Workflow functions must be deterministic: given the same inputs and step return values, they must invoke the same steps in the same order. Non-deterministic operations must be moved to steps.
Incorrect (non-deterministic workflow):
import random
@DBOS.workflow()
def example_workflow():
# Random number in workflow breaks recovery!
choice = random.randint(0, 1)
if choice == 0:
step_one()
else:
step_two()
Correct (non-determinism in step):
import random
@DBOS.step()
def generate_choice():
return random.randint(0, 1)
@DBOS.workflow()
def example_workflow():
# Random number generated in step - result is saved
choice = generate_choice()
if choice == 0:
step_one()
else:
step_two()
Non-deterministic operations that must be in steps:
- Random number generation
- Getting current time
- Accessing external APIs
- Reading files
- Database queries (use transactions or steps)
Reference: Workflow Determinism