One of the biggest challenges in distributed systems is making consistent decisions across the entire system. When designing your Kubernetes cluster, one of the most critical decisions you'll face is determining the number of master nodes. This number directly impacts the reliability and stability of your cluster.
So, how many nodes are required at a minimum to ensure high availability, and what factors influence this decision? Let’s explore the answers to these questions through two fundamental concepts of distributed systems.
The Concept of Quorum:
In distributed systems, the minimum number of nodes required to make consistent decisions is called a quorum. This number is calculated using a simple yet effective formula:
Quorum = (N / 2) + 1
Where N is the total number of nodes.
Using this formula, we get the following results:
In a 2-node system, quorum = 2
In a 3-node system, quorum = 2
In a 5-node system, quorum = 3
At first glance, a 2-node system might seem sufficient. However, distributed systems theory shows us that this setup is risky: if one node goes down, quorum cannot be achieved, and the entire cluster becomes non-functional.
With a minimum of 3 nodes, quorum can still be maintained even if one node is lost, allowing the system to continue operating. Depending on your needs, 5 or more nodes may also be a preferred choice for higher resilience.
Leader Election Mechanism: RAFT
Kubernetes uses the RAFT protocol to achieve consensus among master nodes. This protocol manages leadership and decision-making in distributed systems through three main scenarios:
1. Normal Operation
In a stable state, one node acts as the leader and regularly sends heartbeat messages to the other nodes to indicate, “I’m still here.” The other nodes operate as followers, passively keeping track of the leader's status.
But what happens if the leader fails?
2. Leader Failure Scenario
When the leader node goes down, an automatic recovery process is triggered:
- Followers detect the absence of heartbeat messages.
- A democratic election process begins.
- A candidate node requests votes from the others.
- The node that gains the majority (quorum) becomes the new leader.
3. Split-Brain Scenario
One of the most critical issues in distributed systems is the split-brain condition, and this is where the importance of having at least 3 (preferably odd-numbered) nodes becomes evident:
- In a 2-node system:
If a network partition occurs, both nodes may believe they are the leader. This creates two conflicting "truths" (i.e., a split-brain situation) and the system loses consistency.
- In a 3-node system:
Even if the network is split, two nodes (a majority) remain on one side. The minority node (just one) cannot declare itself leader. Thus, system consistency is preserved.
In Summary
Determining the number of master nodes in a Kubernetes cluster is directly tied to the system’s tolerance for failure and its scalability requirements. For high availability (HA), 3 master nodes is the minimum recommended setup. This number aligns with the quorum formula (N/2 + 1) and the RAFT protocol’s need to prevent split-brain scenarios.
However, for large-scale or mission-critical systems, using 5 or more master nodes (always an odd number) is often preferred to further increase fault tolerance and decision-making stability.
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