This article will guide you on how to troubleshoot Azure #Cache for Redis #timeouts. Azure Cache for Redis regularly updates its server software as part of the managed service functionality that it provides.
Azure Cache for #Redis is a fully managed, in-memory cache that enables high-performance and scalable architectures. Use it to create cloud or hybrid deployments that handle millions of requests per second at sub-millisecond latency—all with the configuration, security, and availability benefits of a managed service.
This patching activity takes place largely behind the scene. During the failovers when Redis server nodes are being patched, Redis clients connected to these nodes may experience temporary timeouts as connections are switched between these nodes.
To help mitigate #Azure memory issues:
1. Upgrade the cache to a larger size so that you aren't running against memory limitations on the system.
2. Set expiration times on the keys so that older values are evicted proactively.
3. Monitor the used_memory_rss cache metric. When this value approaches the size of their cache, you're likely to start seeing performance issues. Distribute the data across multiple shards if you're using a premium cache, or upgrade to a larger cache size.
To fix #CPU bound on the server or on the client:
i. Check if you're getting bound by CPU on your client. High CPU could cause the request to not be processed within the synctimeout interval and cause a request to time out.
ii. Moving to a larger client size or distributing the load can help to control this problem.
iii. Check if you're getting CPU bound on the server by monitoring the CPU cache performance metric. Requests coming in while Redis is CPU bound can cause those requests to time out. To address this condition, you can distribute the load across multiple shards in a premium cache, or upgrade to a larger size or pricing tier.