This post covers Elasticity.
The configuration of a distributed system is constantly
changing. The workload access characteristics shift the hotspots to different
parts of the namespace.
Elasticity represents the capability of the system to
automatically manage changes in cluster configuration and workload. The
actuators to accomplish elasticity are:
- Re-sharding: Splitting the namespace for better
load balancing across the nodes
- Re-mapping:
- Re-assigning Shard-to-node mapping: This is
typically for a subset of the namespace, and could be a result of nodes added/deleted, newly created shards due to splitting, and other configuration changes.
- Re-assigning replica-to-node mapping: Changes in
access can also affect the replica placement
- Re-assigning namespace-to-caching servers
- Auto-scaling: This is the eventual goal, where
the system can dynamically model the load and spin up/spin down service
instances, nodes, network routers on the fly.
The configuration of a distributed system is constantly
changing. The workload access characteristics shift the hotspots to different
parts of the namespace.
Elasticity represents the capability of the system to
automatically manage changes in cluster configuration and workload. The
actuators to accomplish elasticity are:
- Re-sharding: Splitting the namespace for better load balancing across the nodes
- Re-mapping:
- Re-assigning Shard-to-node mapping: This is typically for a subset of the namespace, and could be a result of nodes added/deleted, newly created shards due to splitting, and other configuration changes.
- Re-assigning replica-to-node mapping: Changes in access can also affect the replica placement
- Re-assigning namespace-to-caching servers
- Auto-scaling: This is the eventual goal, where the system can dynamically model the load and spin up/spin down service instances, nodes, network routers on the fly.
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