MemCached SysOps

Memcached Scaling Overview

Scaling Memcached involves two primary methods: horizontal scaling and vertical scaling. Each method serves different scaling needs and comes with its own set of processes and considerations.

Horizontal Scaling

Node Range: Memcached clusters can have between 1 and 40 nodes. This is a soft limit, implying adjustments can be made as needed.
Process: To scale horizontally, add or remove nodes from the cluster.
Auto-Discovery: Applications can automatically discover new nodes in the cluster, facilitating seamless scaling. This mechanism allows your application to dynamically adjust to the cluster's changing structure without manual configuration updates.

Vertical Scaling

Scaling Process: Vertical scaling involves changing the size of the nodes (scale up or down) to larger or smaller types.
- Step 1: Create a new cluster with the desired node type.
- Step 2: Update the application to point to the new cluster's endpoint.
- Step 3: Delete the old cluster. This step is manual and requires careful execution to avoid data loss.
Data Initialization: Unlike Redis, Memcached does not support a backup mechanism. New nodes or clusters start without any data, requiring applications to repopulate data.

Memcached Auto Discovery

Functionality: Enables clients to automatically discover and connect to nodes in a Memcached cluster.
How It Works:
1. Clients connect to a configuration endpoint, receiving the IP address of a cache node.
2. Upon connecting to the initial cache node, the client receives metadata containing IP addresses of all nodes in the cluster.
3. This information allows the client to connect to any node within the cluster, facilitating efficient data retrieval and management.

Monitoring Metrics

Metric	Description	Solution
Evictions	Number of non-expired items evicted for new writes.	Adjust eviction policy, scale up or out.
CPU Utilization	High CPU usage indicates the need for scaling.	Scale up to a larger node or add nodes.
Swap Usage	Indicates swapping activity, which can affect performance.	Scale up or out to alleviate swapping.
CurrConnections	Tracks the number of connections, highlighting potential overuse of connections.	Optimize application to manage connections efficiently.
Freeable Memory	Amount of free memory available, essential for cache operation and performance.	Monitor and adjust scaling accordingly.

Conclusion

Understanding and effectively managing horizontal and vertical scaling, along with the auto-discovery mechanism, are crucial for optimizing Memcached performance. Additionally, monitoring key metrics helps in identifying and addressing potential issues, ensuring efficient cache operation.