Auto-scaling with Memcached involves dynamically scaling your Memcached clusters based on the load. It helps to accommodate fluctuating workloads by automatically adjusting capacity in response to changing demands.
AWS ElastiCache for Memcached provides a simple way to implement this functionality. However, it's important to note that AWS ElastiCache does not natively support auto-scaling for Memcached. Instead, one could use AWS Application Auto Scaling service to monitor and adjust ElastiCache resources as needed.
Here are the steps to set up auto-scaling for Memcached in AWS Environment:
aws iam create-role --role-name ecsAutoscaleRole --assume-role-policy-document file://trust_policy.json
AmazonElastiCacheFullAccess
policy allows the role to perform actions on ElastiCache resources.aws iam attach-role-policy --role-name ecsAutoscaleRole --policy-arn arn:aws:iam::aws:policy/AmazonElastiCacheFullAccess
aws application-autoscaling register-scalable-target --service-namespace elasticache --resource-id cache-cluster-id --scalable-dimension elasticache:nodegroup:Count --min-capacity 1 --max-capacity 10 --role-ARN ecsAutoscaleRole
aws application-autoscaling put-scaling-policy --policy-name scale-out-policy --service-namespace elasticache --resource-id cache-cluster-id --scalable-dimension elasticache:nodegroup:Count --policy-type StepScaling --step-scaling-policy-configuration AdjustmentType=ChangeInCapacity,StepAdjustments=[{MetricIntervalLowerBound=0,ScalingAdjustment=1}],Cooldown=300
In this command, we're creating a policy named 'scale-out-policy' which adds 1 node whenever the specified metric exceeds its defined threshold.
Remember, these scripts require AWS CLI and appropriate credentials configured on your machine. Also, replace 'cache-cluster-id' with your actual cluster ID where necessary.
Naturally, there are many factors to consider when setting up auto-scaling, including how quickly the loads change, how long it takes new nodes to start handling requests efficiently, and costs associated with running additional nodes.
Please note that auto-scaling isn't always the best solution for managing variable loads and can bring complexities. For non-AWS environments or tailor-made solutions, consider using consistent hashing algorithms that make adding or removing servers easier without causing significant cache invalidation.
Dragonfly is fully compatible with the Redis ecosystem and requires no code changes to implement.