Redis is used in thousands of production deploys,
Redis has a proven record of stability. If it runs low on memory, it just evicts older records faster. Additionally, with ElastiCache we can place replica nodes in multiple availability zones and use a single endpoint that will seamlessly switch to a replica if a primary goes down.
2.Performant: Redis runs in memory and we configure it without disk flushes. Its read and write complexity is O(1), so it performs the same regardless of data size.
3.Scalable: Because our sessions expire, we simply set an expiry on our records in Redis and our memory usage reaches an equilibrium, currently at 5GB. If we need to scale further, we can replicate to a node with more memory and then promote it to primary.
Redis is key-value store that stores all its data in RAM.
Redis implements replication using a primary and replica where
•Writes go to the primary. Reads can go to either the primary or replica.
•Writes are replicated to the replicas by asynchronous/non-blocking replication which means that a write is “committed” without waiting to be replicated
•The primary can have multiple replicas, which in turn can have other replicas connected to them
Amazon ElastiCache is a service that provides an easy way to build a highly resilient Redis setup with primary/secondary in multiple zones with automated failover.
Use-Case
After we decided upon our technology, we needed to test and implement it in production without downtime. Building the system and then switching over to it all at once is a recipe for disaster.
we rely heavily on “dark launching”, checking new code into production and then turning on and off execution of that code through a management console for a certain percentage of requests or users.
In the first stage, we wanted to test reads and writes to Redis but still rely on the old setup. Starting at 1% of requests and ramping up to 100%, we mirrored traffic on both MySQL + Memcached and Redis. On every read to MySQL + Memcached we issued the same read request to Redis, and the same for writes. During this testing we gained a lot of knowledge about how the system performed on production traffic.
Redis has a proven record of stability. If it runs low on memory, it just evicts older records faster. Additionally, with ElastiCache we can place replica nodes in multiple availability zones and use a single endpoint that will seamlessly switch to a replica if a primary goes down.
2.Performant: Redis runs in memory and we configure it without disk flushes. Its read and write complexity is O(1), so it performs the same regardless of data size.
3.Scalable: Because our sessions expire, we simply set an expiry on our records in Redis and our memory usage reaches an equilibrium, currently at 5GB. If we need to scale further, we can replicate to a node with more memory and then promote it to primary.
Redis is key-value store that stores all its data in RAM.
Redis implements replication using a primary and replica where
•Writes go to the primary. Reads can go to either the primary or replica.
•Writes are replicated to the replicas by asynchronous/non-blocking replication which means that a write is “committed” without waiting to be replicated
•The primary can have multiple replicas, which in turn can have other replicas connected to them
Amazon ElastiCache is a service that provides an easy way to build a highly resilient Redis setup with primary/secondary in multiple zones with automated failover.
Use-Case
After we decided upon our technology, we needed to test and implement it in production without downtime. Building the system and then switching over to it all at once is a recipe for disaster.
we rely heavily on “dark launching”, checking new code into production and then turning on and off execution of that code through a management console for a certain percentage of requests or users.
In the first stage, we wanted to test reads and writes to Redis but still rely on the old setup. Starting at 1% of requests and ramping up to 100%, we mirrored traffic on both MySQL + Memcached and Redis. On every read to MySQL + Memcached we issued the same read request to Redis, and the same for writes. During this testing we gained a lot of knowledge about how the system performed on production traffic.
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