dis.io | browser based distributed computing platform | Storage library

Recently I have been using spring-boot-starter-data-redis;

I use spring-boot-version:2.3.8.RELEASE;

application.yml

I am trying to use redis with tls with a netcore application and I get an authentication error

I created a redis docker container using redis:6.2.0

docker-compose.yaml:

I am trying to create a Galaxy role for our org's internal galaxy, which I am testing first locally. In our org we use a common list of defaults across all roles.

Ansible is throwing me a "The task includes an option with an undefined variable The error was: 'redis_download_url' is undefined" error when running my playbook, despite me having defined the variable in defaults/main.yml:

Context:

I'm trying to understand the motivation behind existence of WaitBeforeForcingMasterFailover property (and the code associated with it) inside of ServiceStack.Redis.RedisSentinel.

If I interpreted the code right - the meaning behind this property seems to cover cases like:

1. We have a connection to a healthy sentinel that tells us that a master is at host X
2. When we try to establish a connection to the master at host X - we fail due to some reason.

So the logic will be - if we continuously fail to create a connection to X for WaitBeforeForcingMasterFailover period - initiate a force failover.

The failover does not need to reach a quorum and can elect a new master just with 1 sentinel available.

SENTINEL FAILOVER Force a failover as if the master was not reachable, and without asking for agreement to other Sentinels (however a new version of the configuration will be published so that the other Sentinels will update their configurations).

Source: https://redis.io/topics/sentinel#sentinel-api

The way it seems to me - this feature can be beneficial in some cases and troublesome in other cases.

For example in case of a network partition if a client is left connected to a minority of sentinels (they can't reach a quorum) and these sentinels point to a master that is no longer reachable - this force failover option will trigger a failover within reachable partition, thus potentially creating a split brain situation.

Coming from Java background I also haven't seen such features available in popular redis clients such as Jedis and Lettuce.

This got me wondering on the following questions:

1. Are there strong reasons for this feature to be enabled by default? (I understand that you can effectively disable it if you want to by setting a huge value in it). Do they really worth the risk of interfering with natural sentinels workflow and potentially introducing problems like the one I've mentioned before?

2. Will the library work fine with this option disabled? Are there are cases that I might have missed and turning this feature off will lead to problems even with some happy paths (no network partition, just regular failovers because of a deployment or a sudden node failure)?

I run redis image with docker-compose
I passed redis.conf (and redis says "configuration loaded")
In redis.conf i added user

I have a question about when it makes sense to use a Redis cluster versus standalone Redis.

Suppose one has a real-time gaming application that will allow multiple instances of the game and wish to implement real time leaderboard for each instance. (Games are created by communities of users).

Suppose at any time we have say 100 simultaneous matches running.

Based on the use cases outlined here :

https://d0.awsstatic.com/whitepapers/performance-at-scale-with-amazon-elasticache.pdf

https://redislabs.com/solutions/use-cases/leaderboards/

https://aws.amazon.com/blogs/database/building-a-real-time-gaming-leaderboard-with-amazon-elasticache-for-redis/

We can implement each leaderboard using a Sorted Set dataset in memory.

Now I would like to implement some sort of persistence where leaderboard state is saved at the end of each game as a snapshot. Thus each of these independent Sorted Sets are saved as a snapshot file.

I have a question about design choices:

1. Would a redis cluster make sense for this scenario ? Or would it make more sense to have standalone redis instances and create a new database for each game ?

As far as I know there is only a single database 0 for a single redis cluster.(https://redis.io/topics/cluster-spec) In that case, how would one be able to snapshot datasets for each leaderboard at different times work ?

https://redis.io/topics/cluster-spec

From what I can see using a Redis cluster only makes sense for large-scale monolithic applications and may not be the best approach for the scenario described above. Is that the case ?

Or if one goes with AWS Elasticache for Redis Cluster mode can I configure snapshotting for individual datasets ?

I am having a redis data store in which there are unique keys stored. Now my app server will send multiple requests to redis to get some 100 keys from start and I am planning to use LRANGE command for the same.

But my requirement is that each request should receive unique set of keys,which means that if one request goes to redis for 100 keys then those keys will never be returned to any request in future.

As I saw that redis operations are atomic, so can i assume that if there multiple requests coming from app server at same time to redis, as redis is single thrreaded, so it will execute LRANGE mylist 0 100 and once it is completed (means once 100 keys taken and removes from List), only then next request will be processed, so atomicity is inbuild,is it correct? Is it ever possible under any circumstance that two requests can get same 100 keys?

i've read this article(https://redis.io/topics/partitioning#why-partitioning-is-useful) about redis partitioning

i could find that redis offers two partitioning method options, range partitioning and hash partitioning.

for me, range partitioning seems no good compare to hash partitioning in every aspect.

I think range partitioning has some good points but I don't know what they are.

please give me some ideas about it.

I am trying to use Redis Rate limiting patter as specified in https://redis.io/commands/incr under "Pattern: Rate limiter 1". But how can I scale this in case I want to do rate limiting across multiple servers. Like I have service deployed across 5 servers behind load balancer and I want total requests per api key across 5 servers should not cross x/sec. As per redis pattern I mentioned , the problem is that if I have my rate limiter running in multiple servers itself, then the two different request to two different rate limiter servers,can do "get key" at same time and read same value, before anyone updates it, which can probably allow more requests to go.How can I handle this?I can obviously put get in MULTI block, but I think it will make things a lot more slow.