Are Services Interrupted During Specification Modification?
You are advised to change the instance specifications during off-peak hours because specification modification has the following impacts:
Change of the Instance Type
- Supported instance type changes:
- From single-node to master/standby: Supported by Redis 3.0 and Memcached, and not by Redis 4.0/5.0/6.0.
- From master/standby to Proxy Cluster: Supported by Redis 3.0, and not by Redis 4.0/5.0/6.0.
If the data of a master/standby DCS Redis 3.0 instance is stored in multiple databases, or in non-DB0 databases, the instance cannot be changed to the Proxy Cluster type. A master/standby instance can be changed to the Proxy Cluster type only if its data is stored only on DB0.
- From cluster types to other types: Not supported.
- Impact of instance type changes:
- From single-node to master/standby for a DCS Redis 3.0 instance:
The instance cannot be connected for several seconds and remains read-only for about 1 minute.
- From master/standby to Proxy Cluster for a DCS Redis 3.0 instance:
The instance cannot be connected and remains read-only for 5 to 30 minutes.
- From single-node to master/standby for a DCS Redis 3.0 instance:
Scaling
- The following table lists scaling options supported by different DCS instances.
Table 1 Scaling options supported by different DCS instances Cache Engine
Single-Node
Master/Standby
Redis Cluster
Proxy Cluster
Redis 3.0
Scaling up/down
Scaling up/down
N/A
Scaling out
Redis 4.0
Scaling up/down
Scaling up/down and replica quantity change
Scaling up/out, down/in, and replica quantity change
N/A
Redis 5.0
Scaling up/down
Scaling up/down and replica quantity change
Scaling up/out, down/in, and replica quantity change
N/A
Redis 6.0
Scaling up/down
Scaling up/down
N/A
N/A
Memcached
Scaling up/down
Scaling up/down
N/A
N/A
If the reserved memory of a DCS Redis 3.0 or Memcached instance is insufficient, the scaling may fail when the memory is used up.
Change the replica quantity and capacity separately.
- Impact of scaling:
- Single-node and master/standby
- A DCS Redis 4.0/5.0/6.0 instance will be disconnected for several seconds and remain read-only for about 1 minute.
- A DCS Redis 3.0 instance will be disconnected and remain read-only for 5 to 30 minutes.
- For scaling up, only the memory of the instance is expanded. The CPU processing capability is not improved.
- Data of single-node instances may be lost because they do not support data persistence. After scaling, check whether the data is complete and import data if required.
- Backup records of master/standby instances cannot be used after scaling down.
- Cluster
- If the shard quantity is not decreased, the instance can always be connected, but the CPU usage will increase, compromising performance by up to 20%, and the latency will increase during data migration.
- During scaling up, new Redis Server nodes are added, and data is automatically balanced to the new nodes.
- Nodes will be deleted if the shard quantity decreases. To prevent disconnection, ensure that the deleted nodes are not directly referenced in your application.
- Ensure that the used memory of each node is less than 70% of the maximum memory per node of the new flavor. Otherwise, you cannot perform the scale-in.
- If the memory becomes full during scaling due to a large amount of data being written, scaling will fail. Modify specifications during off-peak hours.
- Scaling involves data migration. The latency for accessing the key being migrated increases. For a Redis Cluster instance, ensure that the client can properly process the MOVED and ASK commands. Otherwise, requests will fail.
- Before scaling, perform cache analysis to ensure that no big keys (≥ 512 MB) exist in the instance. Otherwise, scaling may fail.
- Backup records created before scaling cannot be restored.
- Single-node and master/standby
- Notes on changing the number of replicas of a DCS Redis instance:
Deleting replicas interrupts connections. If your application cannot reconnect to Redis or handle exceptions, you need to restart the application after scaling.
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