If your cluster is used for distributed storage or processing (e.g., Hadoop, distributed databases, or storage clusters), having different storage capacities on each node can affect data distribution and data redundancy strategies. You need to plan accordingly to ensure data can be distributed and replicated effectively across nodes.
Different machines with varying storage capacities may also have different workloads or roles within the cluster. For example, a machine with more storage might be used for data storage, while a machine with less storage might be used for compute tasks. This can be a valid configuration if your workload supports it.