Surviving the moment the cache goes cold
PostgreSQL
KubernetesNode replacement no longer produces a database load spike, and the expiry cliffs disappeared once TTL jitter was applied. Cache maintenance moved from a change-approval event back to routine…
Overview
A digital media platform repeatedly took database outages whenever a Memcached node was replaced or a large batch of keys expired together. AceMQ provides continuous support covering the cache tier and the application patterns around it.
Challenge
Losing a node in a consistent-hashing ring remaps its share of keys, and every remapped key misses at once. With no protection against concurrent regeneration, thousands of requests would recompute the same expensive value simultaneously and saturate the database. The same happened at expiry cliffs, because keys populated together during a deployment shared an identical TTL and therefore expired together. Routine node maintenance had become a change-approval problem.
Environment
Memcached tier on AWS fronting a relational database, application servers on Kubernetes with frequent deployments.
Approach
Support here spans the cache and the application patterns that use it, since stampede protection is an application concern that the cache alone cannot solve. We work with the customer's engineers on request coalescing and TTL jitter, and make node topology changes a controlled operation rather than an event.
Solution
- 124/7 support with a 15-minute emergency SLA and named senior engineers who know the cache topology and its consumers
- 2Request coalescing added at the application layer so only one caller regenerates a missing value while others wait
- 3TTL jitter applied so keys populated together do not expire together and produce an expiry cliff
- 4Consistent hashing configuration reviewed so node changes remap the minimum possible key share
- 5Controlled node addition and removal procedure with pre-warming, replacing unplanned replacement
- 6Hit rate, eviction, and get-miss monitoring per node so a degrading node is caught before it is lost
Outcome
Node replacement no longer produces a database load spike, and the expiry cliffs disappeared once TTL jitter was applied. Cache maintenance moved from a change-approval event back to routine operations.
Technologies
PostgreSQLKubernetesRelated Use Cases
Memcached Slab Calcification and Eviction Remediation
Emergency remediation of a Memcached tier evicting hot keys while reporting free memory, traced to slab class allocation.
Memcached Caching Topology and Invalidation Design
Consulting engagement to design multi-region Memcached topology, key namespacing, and invalidation strategy for a latency-sensitive platform.
Apache Airflow DAG Parse Time Support
Fixing scheduler delay caused by DAG files that make network or database calls at parse time, blocking every DAG in the deployment.
Kong Rate Limiting Consistency Support
Fixing rate limits that allowed several times the configured quota because the plugin was using the local counter policy across a multi-node gateway.
Memcached Capacity and Hit Rate Assessment
Assessment of Memcached sizing, key distribution, and hit rate to determine whether adding capacity would actually help.
Producer Timeouts Traced to Controller-Leader Overload
A five-node Kafka cluster serving 60,000 customers was timing out producers under load. The cause was topology, not capacity.
Need Expert Memcached Support?
AceMQ's senior Memcached engineers have handled this exact type of engagement before. Whether you need architectural guidance, hands-on remediation, or an ongoing managed partnership, we're ready to help.