Some of the AWS Services give the ability to replicate between regions. e.g. S3 (CRR), RDS (Read Replica) etc.
In S3-CRR, what happens if the destination Region goes down? Does the replication catch up automatically, once the Region is backup?
EDITED
2. Can CRR be enabled both ways? e.g. active-active
Similarly for RDS-MySQL Read Replica (RR) hosted in a different region what happens when
If the RR instance/Destination Region goes down, does it affect the MASTER in the other Region?
Once the instance is either replaced or Once the region in back up, does the RR catches up on the Missed changes that the MASTER have during the gap/outage?
How Aurora will be different from RDS-MySQL in the above areas?
In S3 cross-region replication, if the destination region goes down, or connectivity is disrupted, replication of objects is delayed until the issue is resolved, then recovers.
Cross-region can be used as active/active, but there is no conflict resolution, so if you wrote different objects with the same key to both regions at about the same time, which version would be the "final current version" in each region is undefined. As long as you aren't doing that, there's no problem. What you can't do is configure more than 2 regions in a ring, because A > B > C > A would only replicate one hop. Objects created in A would replicate A > B, but not B > C, because when an object is created by the replication process, it is not replicated further. That is, objects replicated into a bucket are never also replicated out of the bucket. Objects created directly in B would replicate B > C but not C > A.
If an RDS cross-region replica fails or becomes inaccessible, the master is unaffected. Under the hood, the replica is listening to a stream of change messages from the master, but not acknowledging actually having applied the changes to its local data set, so if a replica disappears, it's a non-event from the master's perspective. Because there are sequencing/positioning pointers/markers in the replication stream, the replica knows where it left off and asks for the stream from the correct starting pointer when it reconnects.
The replica will catch up when service/connectivity is restored, but not instantaneously. The time required depends on the amount of changed data that needs to replicate, and the capacity of the replica. This is true for standard RDS as well as Aurora -- cross-region replication is asynchronous.
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I am new to redis, still reading doc, hope you could help me here.
I need a 2-stage database solution:
At local devices, there is a database cluster. It has several primaries and several replicas. To my understanding each primary or replica normally has a portion of the whole data set. This is called data sharding.
At cloud, there is another database replica. This cloud replica backs up the whole data set.
I like to use free redis for this solution, not enterprise version.
Is this achievable? From what I read so far, it seems that there is no problem if the cloud replica is just like local replica to back up a portion of data set. So I want to know whether I can use the cloud database to back up the whole cluster.
Thanks!
Nothing prevents you from having a replica hosted in the cloud, but each Redis cluster node is either a master responsible of a set of key slots (shards) or a replica of a master; in a multi-master scenario there is no way to have a single replica covering different master nodes.
With the goal of having your entire cluster data replicated in the cloud, you should configure and host there one additional Redis replica per each master node. To avoid those new replicas to ever become masters themselves, you can set their cluster-replica-no-failover configuration property accordingly in their redis.conf files:
cluster-replica-no-failover yes
In all cases, please note that replication is not a backup solution and you may want to pair your setup with a proper Redis persistence mechanism.
If I understand your questions clearly, your master dataset(in shards) are located on premise and the replicas(slave) are hosted on cloud. There is nothing preventing you from backing up your slaves(open source redis) on the cloud. Redis doesn't care where the slaves are situated provided the master can reach them. Master-slave replication is available on redis enterprise with no such restriction. You might have a little problem implementing master-master replication on redis open source but that is outside the scope of this question
According to ML 9 doco, a database is backed up onto all nodes in the cluster, but the backup process appears to backup the forests that are only local to each node. So for a database with 6 forests across 3 nodes, I may have 2 forests backup files on each node.
If I have a 3 node cluster and lose one node ( so that one node is now 100% unrecoverable ), are all my backups now effectively useless as they will be missing the back up files for 2 forests?
Or is ML smart enough to re-create the missing data from the dead node, via parity?
Thanks.
The answer is it depends.
Typically backups are made to some sort of network storage, so loosing a node doesn't affect the backups. If for some reason the backups are stored locally to the system, then it would depend on if you have HA enabled, and whether you are backing up thee replica forests along with the primary forests.
If HA is enabled, you could lose a node and keep running, giving you time to rebuild the lost node. Alternatively, if you are backing up both the primary and replica forests in your cluster, you would have a complete data set in your backups even if you lose a node.
I am very new in REDIS cache implementation.
Could you please let me know what is the replication factor means?
How it works or What is the impact?
Thanks.
At the base of Redis replication (excluding the high availability features provided as an additional layer by Redis Cluster or Redis Sentinel) there is a very simple to use and configure leader follower (master-slave) replication: it allows replica Redis instances to be exact copies of master instances. The replica will automatically reconnect to the master every time the link breaks, and will attempt to be an exact copy of it regardless of what happens to the master.
This system works using three main mechanisms:
When a master and a replica instances are well-connected, the master keeps the replica updated by sending a stream of commands to the replica, in order to replicate the effects on the dataset happening in the master side due to: client writes, keys expired or evicted, any other action changing the master dataset.
When the link between the master and the replica breaks, for network issues or because a timeout is sensed in the master or the replica, the replica reconnects and attempts to proceed with a partial resynchronization: it means that it will try to just obtain the part of the stream of commands it missed during the disconnection.
When a partial resynchronization is not possible, the replica will ask for a full resynchronization. This will involve a more complex process in which the master needs to create a snapshot of all its data, send it to the replica, and then continue sending the stream of commands as the dataset changes.
Redis uses by default asynchronous replication, which being low latency and high performance, is the natural replication mode for the vast majority of Redis use cases.
Synchronous replication of certain data can be requested by the clients using the WAIT command. However WAIT is only able to ensure that there are the specified number of acknowledged copies in the other Redis instances, it does not turn a set of Redis instances into a CP system with strong consistency: acknowledged writes can still be lost during a failover, depending on the exact configuration of the Redis persistence. However with WAIT the probability of losing a write after a failure event is greatly reduced to certain hard to trigger failure modes.
I am interested in creating backups (snapshots) for data being stored in consul. I am using it as my backend storage for my service. I found few tools like consulate, consul-backup which take snapshots for the data which consul stores on the disk. Imagine, I have a 5 node set up where consul is running on all the 5 hosts and we have a quorum of 3. One of them is going to be the leader. With different back up strategies implemented, which backup the data on every single host, does it make more sense to back up only the leader ? The leader would be expected to maintain the most latest state of data. Then why do we need to back up every single host? And if we decide to back up just the leader, then if the leadership changes while the data was being backed up, would that result into any issues ?
Mirroring is replicating data between Kafka cluster, while Replication is for replicating nodes within a Kafka cluster.
Is there any specific use of Replication, if Mirroring has already been setup?
They are used for different use cases. Let's try to clarify.
As described in the documentation,
The purpose of adding replication in Kafka is for stronger durability and higher availability. We want to guarantee that any successfully published message will not be lost and can be consumed, even when there are server failures. Such failures can be caused by machine error, program error, or more commonly, software upgrades. We have the following high-level goals:
Inside a cluster there might be network partitions (a single server fails, and so forth), therefore we want to provide replication between the nodes. Given a setup of three nodes and one cluster, if server1 fails, there are two replicas Kafka can choose from. Same cluster implies same response times (ok, it also depends on how these servers are configured, sure, but in a normal scenario they should not differ so much).
Mirroring, on the other hand, seems to be very valuable, for example, when you are migrating a data center, or when you have multiple data centers (e.g., AWS in the US and AWS in Ireland). Of course, these are just a couple of use cases. So what you do here is to give applications belonging to the same data center a faster and better way to access data - data locality in some contexts is everything.
If you have one node in each cluster, in case of failure, you might have way higher response times to go, let's say, from AWS located in Ireland to AWS in the US.
You might claim that in order to achieve data locality (services in cluster one read from kafka in cluster one) one still needs to copy the data from one cluster to the other. That's definitely true, but the advantages you might get with mirroring could be higher than those you would get by reading directly (via an SSH tunnel?) from Kafka located in another data center, for example single connections down, clients connection/session times longer (depending on the location of the data center), legislation (some data can be collected in a country while some other data shouldn't).
Replication is the basis of higher availability. You shouldn't use Mirroring to handle high availability in a context where data locality matters. At the same time, you should not use just Replication where you need to duplicate data across data centers (I don't even know if you can without Mirroring/an ssh tunnel).