Time in Distributed Systems
Learn how to manage time and sequence events across multiple machines, a fundamental challenge in building scalable, reliable distributed systems.
When an application runs on a single server, it is easy to tell the order of events.
The server’s clock gives a clear timeline. However, when an application runs on multiple servers in different locations, this becomes challenging. For example, imagine two friends sending messages in a chat app simultaneously. How can the system decide which message should appear first?
Relying solely on the local clocks of machines is not a safe approach.
Network delays and inaccurate clocks can cause errors, such as messages appearing in the wrong order or even data being lost. Ensuring events are ordered correctly is one of the primary challenges in distributed System Design.
To solve this, we do not depend only on physical time. Instead, we use logical time, which tracks the order of events across the system rather than relying on wall-clock time.
Why is time challenging in distributed systems?
In a distributed system, there is no single source of truth for time.
Each computer, or node, has its own local clock. While protocols like the
The primary issues that complicate time synchronization include:
Network latency: The time it takes for a message to travel from one node to another is variable and unpredictable. For example, a message sent at 10 o’clock might reach its destination half a second later or even a full second later, depending on network conditions.
Clock drift: Physical clocks on different machines run at slightly different rates. Over time, even clocks that were once synchronized will drift apart. A few milliseconds of drift per hour can accumulate quickly, resulting in significant discrepancies.
Unreliable synchronization: Clock synchronization mechanisms can fail or introduce their own delays, making it unsafe to assume that all nodes share the same view of time.
These challenges directly impact a system’s ability to maintain consistency, coordinate actions between nodes, and debug problems.
For instance, if two nodes process conflicting updates, the system must have a way to decide which update occurred first. Without a reliable global clock, this decision becomes ambiguous. The following diagram illustrates how, in distributed systems,
To overcome these physical limitations, engineers developed logical clocks, which focus on the order in which events happen relative to each other, rather than depending on each node’s local clock to timestamp events.
Logical clocks and event ordering
Because local clocks cannot be fully trusted to order events accurately in a distributed system, we need an alternative mechanism.
Logical clocks offer a way to reason about event ordering without relying on a shared, synchronized physical clock. A logical clock assigns a timestamp—a simple numerical value—to each event. This number does not represent real-world time; instead, it captures the ...