As EKS SLA, a 99.9% avialbility is committed by Amazon.
How I can increase that to 99.99% (or even 99.999%)? Would it help if I add master/slave nodes?
Thanks.
I don't think there is a way to do this and still call your setup an AWS EKS Cluster. It is defined in the EKS SLA that an EKS Cluster means that the control plane would be run by AWS. Three masters in different AZs provide pretty much good HA.
A workaround may be introducing a queue between the control plane (i.e. the k8s api) and your requests. The queue can retain the requests which were not successful due to availability issues and can again send the request based on some priority or time-based logic. This won't increase the HA for real-time tasks, but wouldn't let requests made from asynchronous use cases go to waste.
Related
I've read https://github.com/redisson/redisson
And I found out that there are several
Redis Replicated setup (including support of AWS ElastiCache and Azure Redis Cache)
Redis Cluster setup (including support of AWS ElastiCache Cluster and Azure Redis Cache)
Redis Sentinel setup
Redis with Master with Slave only
I am not a big expert in clusters and I don't understand the difference between these setups.
Could you beiefly explain the differences ?
Disclaimer I am an AWS employee.
I do not know how Redis Replicated Setup is different from Redis in Master-Slave mode. Maybe they mean cross-region replication?
In any case, I can try and explain setups I know about:
Redis with Master with Slave only - is a single shard setup where you create a primary replica together with one or more secondary (slave) replicas (let's hope PC police won't arrest me). This setup is used to improve the durability of your in-memory store. It's not advised to use your secondaries for reads because such setup has eventual consistency guarantees and your replica reads may be stale (depending on the replication lag).
Redis Cluster setup - the setup supported by cloud provides such as AWS Elasticache. In this setup your workload can be spread horizontally across multiple shards and each shard may have its own secondary replicas. Your client library must support this setup since it requires maintaining multiple connections to several nodes at a client level. Moreover, there are some locality rules you need to follow in order to use cluster mode efficiently:
Keys with foo{<shard>}bar notation will be routed to their shard according to what is stored inside curly brackets.
You can not use mset, mget and other multi-key commands across shards. You can still use these commands if their keys contain the same {shard} part.
There are additional cluster mode admin commands that are exposed by Redis but they are usually hijacked and hidden from users by cloud providers since cloud provides use them in order to manage redis cluster themselves.
Redis cluster have an ability to migrate part of your workload between shards. However, it still obliged to preserve correctness with respect to {shard} notation. Since your client library is responsible to fetch data from specific shard it must handle "moved" response when a shard might redirect it to another node.
Redis Sentinel setup - using an additional server that provides service discovery functionality for Redis clusters. Not strictly required and I believe is less popular across users. It serves as a single source of truth regarding each node's health and state. It provides monitoring, management, and service discovery functions for managing your Redis cluster. Many Redis client libraries provide the option of connecting to Redis sentinel nodes in order to achieve automatic service discovery and seamless failover flow. One of the reasons why this setup is less popular is because cloud companies like AWS Elasticache provide this service out of the box.
I need an HA redis solution instead of a single instance. Should I use cluster or Sentinel? I have tried to find out the difference between them, there is no official document about this, thanks a lot.
Well, for a HA redis solution , it depends upon the number of nodes you want to configure.
According to offical Redis documentation on Redis-cluster and Redis-sentinel both provides HA Solution but.....
Redis Sentinel provides high availability for Redis. In practical terms this means that using Sentinel you can create a Redis deployment that resists without human intervention to certain kind of failures.
Redis Cluster provides a way to run a Redis installation where data is automatically sharded across multiple Redis nodes.
Redis Cluster also provides some degree of availability during partitions, that is in practical terms the ability to continue the operations when some nodes fail or are not able to communicate. However the cluster stops to operate in the event of larger failures (for example when the majority of masters are unavailable).
For more information please refer the official docs :)
Cheers
I am currently setting up an infrastructure for an App in AWS. App is written in Django and is using Redis for some transactions. High availability is key for this application and I am having a hard time trying to get my head around how to configure Redis for High availability.
Application level changes are not an option.
Ideally I would like to have a redis setup, to which I can write and read and replicate and scale when required.
Current Setup is a Redis Fail-over scenario with HAProxy --> Redis Master --> Replica Slave.
Could someone guide me understand various options ? and how to scale redis for high availability !
Use AWS ElastiCache Redis Cluster with Multi-AZ. They provides automatic fail-over. It provides endpoint to access master node.
If master goes down AWS route your endpoint to another node. everything happens automatically, you don't have to do anything.
Just make sure that if you are doing DNS to IP caching in your application, its set to 60 seconds or so instead of default.
http://docs.aws.amazon.com/AmazonElastiCache/latest/UserGuide/AutoFailover.html
Thanks,
KS
I see there are multiple modes of operation for Redis (cluster, sentinel, master-slave, etc?). I don't fully understand the implications of each, but my question is this:
If I have a web application that requires distributed session persistence, which configuration of Redis makes the most sense? The main reason I'm using redis is to achieve some level of fault tolerance. If one of my frontend servers fails, I want the sessions to be available for other nodes to pickup the workload. If a redis node goes down, I don't want this to affect the user experiences, and I don't want to have to wake up a developer at midnight to correct the matter.
From everything I've read, Redis Sentinel is the way to go for fault tolerance.
this is a use case question on RabbitMQ clustering. In the past, I have clustered RabbitMQ to make queues highly available (HA). I understand you can cluster RabbitMQ nodes without making HA queues but why would you do that? From a message consumer's POV, clustering in itself buys you nothing unless the queues are made HA (or so I feel). What kind of use-cases can you cite for make a non-HA RabbitMQ cluster?
By having more servers you can get more throughput, be able to accept more connected clients and so on. The non HA cluster is able to see resources in all nodes in the clusters, despite of where the resources were declared.