Resilience has at all times been a prime precedence for patrons operating mission-critical Apache Kafka functions. Amazon Managed Streaming for Apache Kafka (Amazon MSK) is deployed throughout a number of Availability Zones and gives resilience inside an AWS Area. Nonetheless, mission-critical Kafka deployments require cross-Area resilience to reduce downtime throughout service impairment in a Area. With Amazon MSK Replicator, you may construct multi-Area resilient streaming functions to offer enterprise continuity, share information with companions, combination information from a number of clusters for analytics, and serve international shoppers with diminished latency. This put up explains find out how to use MSK Replicator for cross-cluster information replication and particulars the failover and failback processes whereas holding the identical subject identify throughout Areas.

MSK Replicator overview

Amazon MSK gives two cluster varieties: Provisioned and Serverless. Provisioned cluster helps two dealer varieties: Commonplace and Specific. With the introduction of Amazon MSK Specific brokers, now you can deploy MSK clusters that considerably cut back restoration time by as much as 90% whereas delivering constant efficiency. Specific brokers present as much as 3 instances the throughput per dealer and scale as much as 20 instances sooner in comparison with Commonplace brokers operating Kafka. MSK Replicator works with each dealer varieties in Provisioned clusters and together with Serverless clusters.

MSK Replicator helps an an identical subject identify configuration, enabling seamless subject identify retention throughout each active-active or active-passive replication. This avoids the chance of infinite replication loops generally related to third-party or open supply replication instruments. When deploying an active-passive cluster structure for regional resilience, the place one cluster handles stay site visitors and the opposite acts as a standby, an an identical subject configuration simplifies the failover course of. Functions can transition to the standby cluster with out reconfiguration as a result of subject names stay constant throughout the supply and goal clusters.

To arrange an active-passive deployment, it’s important to allow multi-VPC connectivity for the MSK cluster within the main Area and deploy an MSK Replicator within the secondary Area. The replicator will devour information from the first Area’s MSK cluster and asynchronously replicate it to the secondary Area. You join the shoppers initially to the first cluster however fail over the shoppers to the secondary cluster within the case of main Area impairment. When the first Area recovers, you deploy a brand new MSK Replicator to duplicate information again from the secondary cluster to the first. You should cease the shopper functions within the secondary Area and restart them within the main Area.

As a result of replication with MSK Replicator is asynchronous, there’s a chance of duplicate information within the secondary cluster. Throughout a failover, shoppers would possibly reprocess some messages from Kafka subjects. To deal with this, deduplication ought to happen on the patron facet, comparable to by utilizing an idempotent downstream system like a database.

Within the subsequent sections, we exhibit find out how to deploy MSK Replicator in an active-passive structure with an identical subject names. We offer a step-by-step information for failing over to the secondary Area throughout a main Area impairment and failing again when the first Area recovers. For an active-active setup, confer with Create an active-active setup utilizing MSK Replicator.

Answer overview

On this setup, we deploy a main MSK Provisioned cluster with Specific brokers within the us-east-1 Area. To offer cross-Area resilience for Amazon MSK, we set up a secondary MSK cluster with Specific brokers within the us-east-2 Area and replicate subjects from the first MSK cluster to the secondary cluster utilizing MSK Replicator. This configuration gives excessive resilience inside every Area by utilizing Specific brokers, and cross-Area resilience is achieved by means of an active-passive structure, with replication managed by MSK Replicator.

The next diagram illustrates the answer structure.

The first Area MSK cluster handles shopper requests. Within the occasion of a failure to speak to MSK cluster because of main area impairment, it is advisable to fail over the shoppers to the secondary MSK cluster. The producer writes to the buyer subject within the main MSK cluster, and the patron with the group ID msk-consumer reads from the identical subject. As a part of the active-passive setup, we configure MSK Replicator to make use of an identical subject names, ensuring that the buyer subject stays constant throughout each clusters with out requiring adjustments from the shoppers. The complete setup is deployed inside a single AWS account.

Within the subsequent sections, we describe find out how to arrange a multi-Area resilient MSK cluster utilizing MSK Replicator and in addition present the failover and failback technique.

Provision an MSK cluster utilizing AWS CloudFormation

We offer AWS CloudFormation templates to provision sure sources:

It will create the digital personal cloud (VPC), subnets, and the MSK Provisioned cluster with Specific brokers inside the VPC configured with AWS Id and Entry Administration (IAM) authentication in every Area. It’ll additionally create a Kafka shopper Amazon Elastic Compute Cloud (Amazon EC2) occasion, the place we will use the Kafka command line to create and consider a Kafka subject and produce and devour messages to and from the subject.

Configure multi-VPC connectivity within the main MSK cluster

After the clusters are deployed, it is advisable to allow the multi-VPC connectivity within the main MSK cluster deployed in us-east-1. It will permit MSK Replicator to hook up with the first MSK cluster utilizing multi-VPC connectivity (powered by AWS PrivateLink). Multi-VPC connectivity is simply required for cross-Area replication. For same-Area replication, MSK Replicator makes use of an IAM coverage to hook up with the first MSK cluster.

MSK Replicator makes use of IAM authentication solely to hook up with each main and secondary MSK clusters. Due to this fact, though different Kafka shoppers can nonetheless proceed to make use of SASL/SCRAM or mTLS authentication, for MSK Replicator to work, IAM authentication needs to be enabled.

To allow multi-VPC connectivity, full the next steps:

1. On the Amazon MSK console, navigate to the MSK cluster.
2. On the Properties tab, underneath Community settings, select Activate multi-VPC connectivity on the Edit dropdown menu.

3. For Authentication sort, choose IAM role-based authentication.
4. Select Activate choice.

Enabling multi-VPC connectivity is a one-time setup and it might probably take roughly 30–45 minutes relying on the variety of brokers. After that is enabled, it is advisable to present the MSK cluster useful resource coverage to permit MSK Replicator to speak to the first cluster.

5. Beneath Safety settings¸ select Edit cluster coverage.
6. Choose Embody Kafka service principal.

Now that the cluster is enabled to obtain requests from MSK Replicator utilizing PrivateLink, we have to arrange the replicator.

Create a MSK Replicator

Full the next steps to create an MSK Replicator:

1. Within the secondary Area (us-east-2), open the Amazon MSK console.
2. Select Replicators within the navigation pane.
3. Select Create replicator.
4. Enter a reputation and elective description.

5. Within the Supply cluster part, present the next info:
   1. For Cluster area, select us-east-1.
   2. For MSK cluster, enter the Amazon Useful resource Identify (ARN) for the first MSK cluster.

For cross-Area setup, the first cluster will seem disabled if the multi-VPC connectivity shouldn’t be enabled and the cluster useful resource coverage shouldn’t be configured within the main MSK cluster. After you select the first cluster, it mechanically selects the subnets related to main cluster. Safety teams usually are not required as a result of the first cluster’s entry is ruled by the cluster useful resource coverage.

Subsequent, you choose the goal cluster. The goal cluster Area is defaulted to the Area the place the MSK Replicator is created. On this case, it’s us-east-2.

6. Within the Goal cluster part, present the next info:
   1. For MSK cluster, enter the ARN of the secondary MSK cluster. It will mechanically choose the cluster subnets and the safety group related to the secondary cluster.
   2. For Safety teams, select any further safety teams.

Guarantee that the safety teams have outbound guidelines to permit site visitors to your secondary cluster’s safety teams. Additionally guarantee that your secondary cluster’s safety teams have inbound guidelines that settle for site visitors from the MSK Replicator safety teams offered right here.

Now let’s present the MSK Replicator settings.

7. Within the Replicator settings part, enter the next info:
   1. For Subjects to duplicate, we hold the subjects to duplicate as a default worth that replicates all subjects from the first to secondary cluster.
   2. For Replication beginning place, we select Earliest, in order that we will get all of the occasions from the beginning of the supply subjects.
   3. For Copy settings, choose Preserve the identical subject names to configure the subject identify within the secondary cluster as an identical to the first cluster.

This makes certain that the MSK shoppers don’t want so as to add a prefix to the subject names.

8. For this instance, we hold the Client group replication setting as default and set Goal compression sort as None.

Additionally, MSK Replicator will mechanically create the required IAM insurance policies.

9. Select Create to create the replicator.

The method takes round 15–20 minutes to deploy the replicator. After the MSK Replicator is operating, this will probably be mirrored within the standing.

Configure the MSK shopper for the first cluster

Full the next steps to configure the MSK shopper:

1. On the Amazon EC2 console, navigate to the EC2 occasion of the first Area (us-east-1) and hook up with the EC2 occasion dr-test-primary-KafkaClientInstance1 utilizing Session Supervisor, a functionality of AWS Techniques Supervisor.

After you have got logged in, it is advisable to configure the first MSK cluster bootstrap tackle to create a subject and publish information to the cluster. You may get the bootstrap tackle for IAM authentication on the Amazon MSK console underneath View Shopper Data on the cluster particulars web page.

2. Configure the bootstrap tackle with the next code:

sudo su - ec2-user

export BS_PRIMARY=<<MSK_BOOTSTRAP_ADDRESS>>

3. Configure the shopper configuration for IAM authentication to speak to the MSK cluster:

echo -n "safety.protocol=SASL_SSL
sasl.mechanism=AWS_MSK_IAM
sasl.jaas.config=software program.amazon.msk.auth.iam.IAMLoginModule required;
sasl.shopper.callback.handler.class=software program.amazon.msk.auth.iam.IAMClientCallbackHandler
" > /dwelling/ec2-user/kafka/config/client_iam.properties

Create a subject and produce and devour messages to the subject

Full the next steps to create a subject after which produce and devour messages to it:

1. Create a buyer subject:

/dwelling/ec2-user/kafka/bin/kafka-topics.sh --bootstrap-server=$BS_PRIMARY 
--create --replication-factor 3 --partitions 3 
--topic buyer 
--command-config=/dwelling/ec2-user/kafka/config/client_iam.properties

2. Create a console producer to jot down to the subject:

/dwelling/ec2-user/kafka/bin/kafka-console-producer.sh 
--bootstrap-server=$BS_PRIMARY --topic buyer 
--producer.config=/dwelling/ec2-user/kafka/config/client_iam.properties

3. Produce the next pattern textual content to the subject:

This can be a buyer subject
That is the 2nd message to the subject.

4. Press Ctrl+C to exit the console immediate.
5. Create a shopper with group.id msk-consumer to learn all of the messages from the start of the shopper subject:

/dwelling/ec2-user/kafka/bin/kafka-console-consumer.sh 
--bootstrap-server=$BS_PRIMARY --topic buyer --from-beginning 
--consumer.config=/dwelling/ec2-user/kafka/config/client_iam.properties 
--consumer-property group.id=msk-consumer

It will devour each the pattern messages from the subject.

6. Press Ctrl+C to exit the console immediate.

Configure the MSK shopper for the secondary MSK cluster

Go to the EC2 cluster of the secondary Area us-east-2 and comply with the beforehand talked about steps to configure an MSK shopper. The one distinction from the earlier steps is that you must use the bootstrap tackle of the secondary MSK cluster because the surroundings variable. Configure the variable $BS_SECONDARY to configure the secondary Area MSK cluster bootstrap tackle.

Confirm replication

After the shopper is configured to speak to the secondary MSK cluster utilizing IAM authentication, record the subjects within the cluster. As a result of the MSK Replicator is now operating, the buyer subject is replicated. To confirm it, let’s see the record of subjects within the cluster:

/dwelling/ec2-user/kafka/bin/kafka-topics.sh --bootstrap-server=$BS_SECONDARY 
--list --command-config=/dwelling/ec2-user/kafka/config/client_iam.properties

The subject identify is buyer with none prefix.

By default, MSK Replicator replicates the small print of all the patron teams. Since you used the default configuration, you may confirm utilizing the next command if the patron group ID msk-consumer can be replicated to the secondary cluster:

/dwelling/ec2-user/kafka/bin/kafka-consumer-groups.sh --bootstrap-server=$BS_SECONDARY 
--list --command-config=/dwelling/ec2-user/kafka/config/client_iam.properties

Now that we’ve verified the subject is replicated, let’s perceive the important thing metrics to watch.

Monitor replication

Monitoring MSK Replicator is essential to guarantee that replication of information is going on quick. This reduces the chance of information loss in case an unplanned failure happens. Some essential MSK Replicator metrics to watch are ReplicationLatency, MessageLag, and ReplicatorThroughput. For an in depth record, see Monitor replication.

To grasp what number of bytes are processed by MSK Replicator, you must monitor the metric ReplicatorBytesInPerSec. This metric signifies the common variety of bytes processed by the replicator per second. Knowledge processed by MSK Replicator consists of all information MSK Replicator receives. This consists of the information replicated to the goal cluster and filtered by MSK Replicator. This metric is relevant in case you use Preserve similar subject identify within the MSK Replicator copy settings. Throughout a failback situation, MSK Replicator begins to learn from the earliest offset and replicates information from the secondary again to the first. Relying on the retention settings, some information would possibly exist within the main cluster. To stop duplicates, MSK Replicator processes the information however mechanically filters out duplicate information.

Fail over shoppers to the secondary MSK cluster

Within the case of an sudden occasion within the main Area by which shoppers can’t hook up with the first MSK cluster or the shoppers are receiving sudden produce and devour errors, this might be an indication that the first MSK cluster is impacted. It’s possible you’ll discover a sudden spike in replication latency. If the latency continues to rise, it might point out a regional impairment in Amazon MSK. To confirm this, you may test the AWS Well being Dashboard, although there’s a probability that standing updates could also be delayed. When you establish indicators of a regional impairment in Amazon MSK, you must put together to fail over the shoppers to the secondary area.

For essential workloads we suggest not taking a dependency on management aircraft actions for failover. To mitigate this threat, you may implement a pilot gentle deployment, the place important parts of the stack are stored operating in a secondary area and scaled up when the first area is impaired. Alternatively, for sooner and smoother failover with minimal downtime, a sizzling standby method is really helpful. This entails pre-deploying all the stack in a secondary area in order that, in a catastrophe restoration situation, the pre-deployed shoppers may be shortly activated within the secondary area.

Failover course of

To carry out the failover, you first have to cease the shoppers pointed to the first MSK cluster. Nonetheless, for the aim of the demo, we’re utilizing console producer and shoppers, so our shoppers are already stopped.

In an actual failover situation, utilizing main Area shoppers to speak with the secondary Area MSK cluster shouldn’t be really helpful, because it breaches fault isolation boundaries and results in elevated latency. To simulate the failover utilizing the previous setup, let’s begin a producer and shopper within the secondary Area (us-east-2). For this, run a console producer within the EC2 occasion (dr-test-secondary-KafkaClientInstance1) of the secondary Area.

The next diagram illustrates this setup.

Full the next steps to carry out a failover:

1. Create a console producer utilizing the next code:

/dwelling/ec2-user/kafka/bin/kafka-console-producer.sh 
--bootstrap-server=$BS_SECONDARY --topic buyer 
--producer.config=/dwelling/ec2-user/kafka/config/client_iam.properties

2. Produce the next pattern textual content to the subject:

That is the third message to the subject.
That is the 4th message to the subject.

Now, let’s create a console shopper. It’s essential to ensure the patron group ID is strictly the identical as the patron connected to the first MSK cluster. For this, we use the group.id msk-consumer to learn the messages from the buyer subject. This simulates that we’re mentioning the identical shopper connected to the first cluster.

3. Create a console shopper with the next code:

/dwelling/ec2-user/kafka/bin/kafka-console-consumer.sh 
--bootstrap-server=$BS_SECONDARY --topic buyer --from-beginning 
--consumer.config=/dwelling/ec2-user/kafka/config/client_iam.properties 
--consumer-property group.id=msk-consumer

Though the patron is configured to learn all the information from the earliest offset, it solely consumes the final two messages produced by the console producer. It’s because MSK Replicator has replicated the patron group particulars together with the offsets learn by the patron with the patron group ID msk-consumer. The console shopper with the identical group.id mimic the behaviour that the patron is failed over to the secondary Amazon MSK cluster.

Fail again shoppers to the first MSK cluster

Failing again shoppers to the first MSK cluster is the frequent sample in an active-passive situation, when the service within the main area has recovered. Earlier than we fail again shoppers to the first MSK cluster, it’s essential to sync the first MSK cluster with the secondary MSK cluster. For this, we have to deploy one other MSK Replicator within the main Area configured to learn from the earliest offset from the secondary MSK cluster and write to the first cluster with the identical subject identify. The MSK Replicator will copy the information from the secondary MSK cluster to the first MSK cluster. Though the MSK Replicator is configured to begin from the earliest offset, it won’t duplicate the information already current within the main MSK cluster. It’ll mechanically filter out the present messages and can solely write again the brand new information produced within the secondary MSK cluster when the first MSK cluster was down. The replication step from secondary to main wouldn’t be required in case you don’t have a enterprise requirement of holding the information similar throughout each clusters.

After the MSK Replicator is up and operating, monitor the MessageLag metric of MSK Replicator. This metric signifies what number of messages are but to be replicated from the secondary MSK cluster to the first MSK cluster. The MessageLag metric ought to come down near 0. Now you must cease the producers writing to the secondary MSK cluster and restart connecting to the first MSK cluster. You also needs to permit the shoppers to learn information from the secondary MSK cluster till the MaxOffsetLag metric for the shoppers shouldn’t be 0. This makes certain that the shoppers have already processed all of the messages from the secondary MSK cluster. The MessageLag metric must be 0 by this time as a result of no producer is producing information within the secondary cluster. MSK Replicator replicated all messages from the secondary cluster to the first cluster. At this level, you must begin the patron with the identical group.id within the main Area. You possibly can delete the MSK Replicator created to repeat messages from the secondary to the first cluster. Guarantee that the beforehand current MSK Replicator is in RUNNING standing and efficiently replicating messages from the first to secondary. This may be confirmed by wanting on the ReplicatorThroughput metric, which must be larger than 0.

Failback course of

To simulate a failback, you first have to allow multi-VPC connectivity within the secondary MSK cluster (us-east-2) and add a cluster coverage for the Kafka service principal like we did earlier than.

Deploy the MSK Replicator within the main Area (us-east-1) with the supply MSK cluster pointed to us-east-2 and the goal cluster pointed to us-east-1. Configure Replication beginning place as Earliest and Copy settings as Preserve the identical subject names.

The next diagram illustrates this setup.

After the MSK Replicator is in RUNNING standing, let’s confirm there isn’t any duplicate whereas replicating the information from the secondary to the first MSK cluster.

Run a console shopper with out the group.id within the EC2 occasion (dr-test-primary-KafkaClientInstance1) of the first Area (us-east-1):

/dwelling/ec2-user/kafka/bin/kafka-console-consumer.sh 
--bootstrap-server=$BS_PRIMARY --topic buyer --from-beginning 
--consumer.config=/dwelling/ec2-user/kafka/config/client_iam.properties

This could present the 4 messages with none duplicates. Though within the shopper we specify to learn from the earliest offset, MSK Replicator makes certain the duplicate information isn’t replicated again to the first cluster from the secondary cluster.

This can be a buyer subject
That is the 2nd message to the subject.
That is the third message to the subject.
That is the 4th message to the subject.

Now you can level the shoppers to begin producing to and consuming from the first MSK cluster.

Clear up

At this level, you may tear down the MSK Replicator deployed within the main Area.

Conclusion

This put up explored find out how to improve Kafka resilience by establishing a secondary MSK cluster in one other Area and synchronizing it with the first cluster utilizing MSK Replicator. We demonstrated find out how to implement an active-passive catastrophe restoration technique whereas sustaining constant subject names throughout each clusters. We offered a step-by-step information for configuring replication with an identical subject names and detailed the processes for failover and failback. Moreover, we highlighted key metrics to watch and outlined actions to offer environment friendly and steady information replication.

For extra info, confer with What’s Amazon MSK Replicator? For a hands-on expertise, check out the Amazon MSK Replicator Workshop. We encourage you to check out this function and share your suggestions with us.

In regards to the Creator

Subham Rakshit is a Senior Streaming Options Architect for Analytics at AWS primarily based within the UK. He works with clients to design and construct streaming architectures to allow them to get worth from analyzing their streaming information. His two little daughters hold him occupied more often than not outdoors work, and he loves fixing jigsaw puzzles with them. Join with him on LinkedIn.