Introduction
Idempotency is a crucial property in the world of APIs, ensuring that operations can be applied multiple times without changing the result.
In this post, we’ll explore six effective strategies to achieve idempotency in your API, drawing inspiration from real-world examples and distributed systems principles.
Idempotency Explained
The light switch analogy is often used to explain idempotence.
Consider a light switch in a room. The operation of turning the light switch on or off is idempotent. If the light is initially off and you flip the switch to turn it on, flipping it again won’t turn the light off again—it stays on.
Similarly, if the light is already on and you flip the switch to turn it on, flipping it again won’t change the fact that the light is already on—it stays on.
In this analogy:
- Turning the light on is an idempotent operation because repeating it doesn’t change the state if the light is already on.
- Turning the light off is also idempotent because repeating it doesn’t change the state if the light is already off.
How to Deal with Idempotency
We’ll now explore six strategies to achieve idempotency in your API.
Natural Idempotency
Designing Operations with Inherent Idempotence
Some operations can be naturally designed to be idempotent. Consider the command “Turn On The Light.” This command is idempotent by default, as it produces the same result regardless of whether the lights were on or off to begin with. Designing operations with inherent idempotence simplifies the implementation and ensures consistent behavior.
Side Effect Checks
Mitigating Side Effects in Real-Time
In certain scenarios, checking for indirect side effects of a command can be a powerful strategy. For instance, before executing the command “Turn On The Light,” you might check if the temperature is already above a certain threshold (e.g., 65°C). If the temperature condition is met, there’s no need to perform the command, preventing unnecessary operations and potential risks.
Version and Validate
Managing State with Versioning
A more sophisticated approach involves adding versioning information to state or aggregates. This can be in the form of timestamps or sequence numbers. Commands intending to alter the state include expected version information. If the version information on the target exceeds that in the incoming command, the command can be safely discarded. This strategy adds a layer of validation to ensure the consistency of state changes.
Identify and Deduplicate
Tracking Commands with Unique Identifiers
Assigning a unique identifier to each command and maintaining a list of recently performed commands allows for effective deduplication. When a command is received, its identifier is checked against the list of recent commands. If the identifier is found, the command is discarded to prevent duplicate execution. This approach is particularly useful in scenarios where commands can be replayed.
Partner State Machines
Coordinating Distributed Systems
In distributed systems, the concept of partner state machines, introduced by Pat Helland in the paper ‘Life Beyond Distributed Transactions,’ can be valuable. Each partner maintains a state machine representing the progression of its communication with another partner. State machines ensure that only valid state transitions occur, preventing conflicts and guaranteeing that each command is executed only once.
Accept Uncertainty
Dealing with Duplicates at the Business Level
Sometimes, it’s acceptable to live with a certain level of uncertainty. From a business perspective, duplicate data might be tolerable if there are processes in place to correct such scenarios. For instance, in the case of a duplicate payment, issuing a credit note can serve as a deduplication mechanism, correcting the situation at the business level.
Conclusion
In conclusion, achieving idempotency in your API requires careful consideration of the nature of your operations and the potential risks associated with repeated execution.
Whether you opt for natural idempotency, side effect checks, versioning, deduplication, partner state machines, or acceptance of uncertainty, each strategy comes with its own set of advantages and considerations.
Choose the approach that aligns best with your system’s requirements and characteristics.