Amazon MSK FAQs

• Apache Kafka stores streaming data in a fault-tolerant way as a continuous series of records and preserves the order in which the records were produced.
  
• Apache Kafka acts as a buffer between data producers and data consumers. Apache Kafka allows many data producers (e.g. websites, IoT devices, Amazon EC2 instances) to continuously publish streaming data and categorize this data using Apache Kafka topics. Multiple data consumers (e.g. machine learning applications, Lambda functions) read from these topics at their own rate, similar to a message queue or enterprise messaging system.
• Data consumers process data from Apache Kafka topics on a first-in-first-out basis, preserving the order data was produced.

Q: What are the key concepts of Apache Kafka?

Q: What is Apache Kafka Connect?

Kafka Connect, an open source component of Apache Kafka, is a framework for connecting Apache Kafka with external systems such as databases, key-value stores, search indexes, and file systems.

Q: What is a connector?

A connector integrates external systems including Amazon Web Services services with Apache Kafka by continuously copying streaming data from a data source into an Apache Kafka topic, or continuously copying data from an Apache Kafka topic into a data sink. A connector may perform lightweight logic such as transformation, format conversion, or filtering data before the data is delivered to a destination. Source connectors pull data from a data source and push this data into Apache Kafka, while sink connectors pull data from Apache Kafka and push this data into a data sink.

Q: Where can I get connectors?

MSK Connect runs any connector that implements the Kafka Connect interfaces. There are many sources of connectors, including from our partners, open source projects like Debezium, and from commercial connector vendors like Confluent and lenses.io.

Q: Does MSK Connect support non-MSK Apache Kafka clusters?

MSK Connect works with Amazon MSK clusters, other Apache Kafka and compatible clusters including self-managed clusters in EC2 or non-Amazon Web Services environments, subject to Amazon VPC connectivity.

Q: Can I use Apache Kafka APIs to get data in and out of Apache Kafka?

Yes, Amazon MSK supports the native Apache Kafka producer and consumer APIs. Your application code does not need to change when clients begin to work with clusters within Amazon MSK.


Q: Can I use Apache Kafka Connect, Apache Kafka Streams, or any other ecosystem component of Apache Kafka with Amazon MSK?

Yes, you can use any component that leverages the Apache Kafka producer and consumer APIs, and the Apache Kafka Admin Client. Tools that upload .jar files into Apache Kafka clusters are currently not compatible with Amazon MSK, including Confluent Control Center, Confluent Auto Data Balancer, and Uber uReplicator.

Q: What are Standard brokers?

Standard brokers for MSK Provisioned offer the high flexibility to configure your cluster's performance. You can choose from a wide range of cluster configurations, to achieve the availability, durability, throughput, and latency characteristics required for your applications. You can also provision storage capacity and increase it as and when needed. Amazon MSK handles the hardware maintenance of Standard brokers and attached storage resources, automatically repairing hardware issues that may arise.

Q: What are Express brokers?

Express brokers for MSK Provisioned make Apache Kafka simpler to manage, more cost-effective to run at scale, and more elastic with the low latency you expect. Brokers include pay-as-you-go storage that scales automatically and requires no sizing, provisioning, or proactive monitoring. Depending on the instance size selected, each broker node can provide up to 3x more throughput per broker, scale up to 20x faster, and recover 90% quicker compared to standard Apache Kafka brokers. Express brokers come pre-configured with Amazon MSK’s best practice defaults and enforce client throughput quotas to minimize resource contention between clients and Kafka’s background operations.

Q: What are the key benefits of Express brokers?

• No storage management: Express brokers eliminate the need to provision or manage any storage resources. You get elastic, virtually unlimited, pay-as-you-go, and fully managed storage. For high throughput use cases, you do not need to reason about the interactions between compute instances and storage volumes and the associated throughput bottlenecks. These capabilities simplify cluster management and eliminate storage management operational overhead.
• Faster scaling: Express brokers allow you to scale your cluster and move partitions faster than on Standard brokers. This capability is crucial when you need to scale out your cluster to handle upcoming load spikes or scale in your cluster to reduce cost. See the sections on expanding your cluster, removing brokers, reassigning partitions, and setting up LinkedIn’s Cruise Control for rebalancing for more details on scaling your cluster.
• Higher throughput: Express brokers offer up to 3x more throughput per broker than Standard brokers. For example, you can safely write data at up to 500 MBps with each m7g.16xlarge sized Express broker compared to 153.8 MBps on the equivalent Standard broker (both numbers assume sufficient bandwidth allocation towards background operations, such as replication and rebalancing).
• Configured for high resilience: Express brokers automatically offer various best practices pre-configured to improve your cluster’s resilience. These include guardrails on critical Apache Kafka configurations, throughput quotas, and capacity reservation for background operations and unplanned repairs. These capabilities make it safer and easier to run large scale Apache Kafka applications. See the sections on Express broker configurations and Amazon MSK Express broker quota for more details.
• No Maintenance windows: There are no maintenance windows for Express brokers. Amazon MSK automatically updates your cluster hardware on an ongoing basis. See Amazon MSK Express brokers for more details.

Q: How can I optimize my cost with Express brokers?

Express brokers provide more throughput per broker, so you can create clusters with fewer brokers for the same workload. Additionally, once your cluster is up and running, you can monitor the use of your cluster resources and right-size capacity faster than with Standard brokers. You can, therefore, provision resources that are fit for the capacity you need and scale faster to meet any changes in demand.

Q: Which Apache Kafka APIs and tools can I use with Express brokers?

Clusters with Express brokers work with Apache Kafka APIs and tools that use the standard Apache Kafka client.

Q: Which Kafka configurations do I need to customize for Express brokers?

Express brokers come preconfigured with Amazon MSK best practice defaults that optimize for availability and durability. You may customize some of these configurations to further fine-tune the performance of your clusters. Read more about Express broker configurations in the Amazon MSK Developer Guide.

Q: Which encryption options are available with Express brokers?

Just as for Standard brokers, Amazon MSK integrates with Amazon Key Management Service (Amazon KMS) to offer transparent server-side encryption for the storage in Express brokers. When you create an MSK cluster with Express brokers, you can specify the Amazon KMS key that you want Amazon MSK to use to encrypt your data at rest. If you don't specify a KMS key, Amazon MSK creates an Amazon Web Services managed key for you and uses it on your behalf. Amazon MSK also uses TLS to encrypt data in transit for Express brokers, as it does for Standard brokers.

Q: What are the Amazon MSK feature differences between Standard and Express brokers?

Most MSK Provisioned features and capabilities that work on Standard brokers also work with clusters that use Express brokers. Some differences include: storage management, instance type availability, and supported versions. See table comparing Standard and Express brokers under MSK Provisioned highlights some key similarities and differences.

Q: Can I move my existing Kafka workload to Express brokers?

Yes, you can migrate the data in your Kafka cluster to a cluster comprising of Express brokers using MirrorMaker 2 or Amazon MSK Replicator, which copies both the data and the metadata of your cluster to a new cluster. You can learn more about using Migrate to an Amazon MSK Cluster and MSK Replicator in the Amazon MSK Developer Guide.

Q: How should I choose between Standard and Express MSK Provisioned broker types?

Express brokers increase your price performance, provide higher resiliency, and lower operational overhead, making it the ideal choice for all Apache Kafka workloads on MSK Provisioned. However, you can choose Standard broker types if you want to control more of your brokers’ configurations and settings. With Standard brokers, you can customize a wider set of Kafka configurations, including replication factor, size of log files, and leader election policies, which gives you more flexibility over your cluster settings.

Q: Does Amazon MSK run in an Amazon VPC?

Yes, Amazon MSK always runs within an Amazon VPC managed by the Amazon MSK service. Amazon MSK resources will be available to your own Amazon VPC, subnet, and security group you select when the cluster is setup. IP addresses from your VPC are attached to your Amazon MSK resources through elastic network interfaces (ENIs), and all network traffic stays within the Amazon network and is not accessible to the internet by default.

Q: How will the brokers in my Amazon MSK cluster be made accessible to clients within my VPC?

The brokers in your cluster will be made accessible to clients in your VPC through ENIs appearing in your account. The Security Groups on the ENIs will dictate the source and type of ingress and egress traffic allowed on your brokers.

Q: Is it possible to connect to my cluster over the public Internet?

Yes, Amazon MSK offers an option to securely connect to the brokers of Amazon MSK clusters running Apache Kafka 2.6.0 or later versions over the internet. By enabling public access, authorized clients external to a private Amazon Virtual Private Cloud (VPC) can stream encrypted data in and out of specific Amazon MSK clusters. You can enable public access for MSK clusters after a cluster has been created at no additional cost, but standard Amazon data transfer costs for cluster ingress and egress apply. To learn more about turning on public access, see the public access documentation.

Q: Is the connection between my clients and an Amazon MSK cluster private?

By default, the only way data can be produced and consumed from an Amazon MSK cluster is over a private connection between your clients in your VPC and the Amazon MSK cluster. However, if you turn on public access for your Amazon MSK cluster and connect to your MSK cluster using the public bootstrap-brokers string, the connection, though authenticated, authorized and encrypted, is no longer considered private. We recommend that you configure the cluster's security groups to have inbound TCP rules that allow public access from your trusted IP address and make these rules as restrictive as possible if you turn on public access.

Q: How do I connect to my Amazon MSK cluster over the internet?

The easiest way is to turn on public connectivity over the internet to the brokers of MSK clusters running Apache Kafka 2.6.0 or later versions. For security reasons, you can't turn on public access while creating an MSK cluster. However, you can update an existing cluster to make it publicly accessible. You can also create a new cluster and then update it to make it publicly accessible. To learn more about turning on public access, see the public access documentation. 

Q: How do I connect to my Amazon MSK cluster from inside Amazon Web Services China network but outside the cluster’s Amazon VPC?

You can connect to your MSK cluster from any VPC or Amazon Web Services account different than your MSK cluster’s by turning on the multi-VPC private connectivity for MSK clusters running Apache Kafka versions 2.7.1. or later versions. You can only turn on private connectivity after cluster creation for any of the supported authentication schemes (IAM authentication, SASL SCRAM and mTLS authentication). Amazon MSK uses Amazon PrivateLink technology to enable private connectivity and you should configure your clients to connect to the cluster using Amazon PrivateLink endpoints. To learn more about setting up private connectivity, see Access from within Amazon Web Services documentation.

Q: How do I control cluster authentication and Apache Kafka API authorization?

Amazon MSK offers three options for controlling authentication (AuthN) and authorization (AuthZ). 1) IAM Access Control for both AuthN/Z (recommended), 2) TLS certificate authentication (CA) for AuthN and access control lists for AuthZ, and 3) SASL/SCRAM for AuthN and access control lists for AuthZ. Amazon MSK recommends using IAM Access Control. It’s the easiest to use and because it defaults to least privilege access, the most secure option.

Q: How does authorization work in Amazon MSK?

If you are using IAM Access Control, Amazon MSK uses the policies you write and its own authorizer to authorize actions. If you are using TLS certificate authentication or SASL/SCRAM, Apache Kafka uses access control lists (ACLs) for authorization. To enable ACLs you must enable client authentication using either TLS certificates or SASL/SCRAM.

Q: How can I authenticate and authorize a client at the same time?

If you are using IAM Access Control, Amazon MSK will authenticate and authorize for you without any additional set up. If you are using TLS authentication, you can use the Dname of clients TLS certificates as the principal of the ACL to authorize client requests. If you are using SASL/SCRAM, you can use the username as the principal of the ACL to authorize client requests.

Q: How do I control service API actions?

You can control service API actions using Amazon IAM.

Q: Can I enable IAM Access Control for an existing cluster?

No, however a feature that would allow you to update your authentication settings is coming soon.

Q: Can I use IAM Access Control outside of Amazon MSK?

No, IAM Access Control is only available for Amazon MSK clusters.

Q: Can I update authentication settings on my cluster?

You can enable or disable authentication modes for your clusters from the console or through the update-security API. When using the API, the authentication modes that are explicitly declared will be modified accordingly, while those that are omitted will be maintained as is. For example, if your cluster uses mTLS for authentication and you enable IAM Access Control by calling the update-security API, both mTLS and IAM Access Control will be enabled on your cluster.

Q: Can I enable multiple authentication modes on my cluster?

Yes, you can add multiple authentication modes to your cluster, both during creation and updates. The brokers within the cluster have dedicated ports for each authentication mode, and your clients that connect to Kafka through these ports must have the corresponding authentication mode enabled.

Q: Can I disable an authentication mode on my cluster?

Yes, you can disable an authentication mode. To ensure that your clients do not lose connectivity with the brokers, do not disable any existing authentication modes until all the clients have been updated to use other available authentication modes.

Q: Can I track clients using an authentication mode with my cluster?

Yes, you can track the number of open connections by authentication mode using the ClientConnectionCount metric published to Amazon CloudWatch metrics.

Q: How do I provide cross-account access permissions to a Kafka client in an Amazon Web Services account different from Amazon MSK’s to connect privately to my Amazon MSK cluster? 

You can attach a cluster policy to your Amazon MSK cluster to provide your cross-account Kafka client permissions to set up private connectivity to your Amazon MSK cluster. When using IAM client authentication, you can also use the cluster policy to granularly define the Kafka data plane permissions for the connecting client. To learn more about cluster policies, see the cluster policy documentation. 

Q: How do I monitor the performance of my clusters or topics?

You can monitor the performance of your clusters using the Amazon MSK console, Amazon CloudWatch console, or you can access JMX and host metrics using Open Monitoring with Prometheus, an open source monitoring solution.

Q: What is the cost for the different CloudWatch monitoring levels?

The cost of monitoring your cluster using Amazon CloudWatch is dependent on the monitoring level and the size of your Apache Kafka cluster. Amazon CloudWatch charges per metric per month and includes a free tier; see Amazon CloudWatch pricing for more information. For details on the number of metrics exposed for each monitoring level, see Amazon MSK monitoring documentation.

Q: What monitoring tools are compatible with Open Monitoring with Prometheus?

Tools that are designed to read from Prometheus exporters are compatible with Open Monitoring, like: Datadog, Lenses, New Relic, Sumologic, or a Prometheus server. For details on Open Monitoring, see Amazon MSK Open Monitoring documentation.

Q: How do I monitor the health and performance of clients?

You can use any client-side monitoring supported by the Apache Kafka version you are using.

Q: Can I tag Amazon MSK resources?

Yes, you can tag Amazon MSK clusters from the Amazon CLI or Console.

Q: How do I monitor consumer lag?
Topic level consumer lag metrics are available as part of the default set of metrics that Amazon MSK publishes to Amazon CloudWatch for all clusters. No additional setup is required to get these metrics. To get partition level metrics (partition dimension), you can enable enhanced monitoring (PER_PARTITION_PER_TOPIC) on your cluster. Alternatively, you can enable Open Monitoring on your cluster, and use a Prometheus server, to capture partition level metrics from the brokers in your cluster. Consumer lag metrics are available at port 11001, just as other Kafka metrics.

Q: How much does it cost to publish the consumer lag metric to Amazon CloudWatch?
Topic level metrics are included in the default set of Amazon MSK metrics, which are free of charge. Partition level metrics are charged as per Amazon CloudWatch pricing.

Q: How do I access Apache Kafka broker Logs?

You can enable broker log delivery for new and existing Amazon MSK clusters. You can deliver broker logs to Amazon CloudWatch Logs, Amazon S3, and Kinesis Data Firehose. Kinesis Data Firehose supports Amazon Elasticsearch Service among other destinations. To learn how to enable this feature, see the Amazon MSK Logging Documentation. To learn about pricing refer to CloudWatch Logs and Kinesis Data Firehose pricing pages.

Q: What is the logging level for broker logs?

Amazon MSK provides INFO level logs for all brokers within a cluster.

Q: How do I access Apache ZooKeeper Logs?

You can request Apache ZooKeeper logs through a support ticket.

Q: Can I log the use of Apache Kafka resource APIs, like create topic?

Yes, if you use IAM Access Control, the use of Apache Kafka resource APIs is logged to Amazon CloudTrail. 

Q: What is Apache ZooKeeper?

From https://zookeeper.apache.org/: “Apache ZooKeeper is a centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services. All of these kinds of services are used in some form or another by distributed applications,” including Apache Kafka.

Q: Does Amazon MSK use Apache ZooKeeper?

Yes, Amazon MSK uses Apache ZooKeeper and manages Apache ZooKeeper within each cluster as a part of the Amazon MSK service. Apache ZooKeeper nodes are included with each cluster at no additional cost.

Q: How do my clients interact with Apache ZooKeeper?

Your clients can interact with Apache ZooKeeper through an Apache ZooKeeper endpoint provided by the service. This endpoint is provided in the Amazon Web Services management console or using the DescribeCluster API.

Q: What Amazon Web Services does Amazon MSK integrate with?

Amazon MSK integrates with:

• Amazon VPC for network isolation and security
  
• Amazon CloudWatch for metrics
  
• Amazon KMS for storage volume encryption
  
• Amazon IAM for authentication and authorization of Apache Kafka and service APIs. 
  
• Amazon Lambda for MSK event sourcing
  
• Amazon IoT for IoT event sourcing
  
• Amazon Glue Schema Registry for controlling the evolution of schemas used by Apache Kafka applications
  
• Amazon CloudTrail for Amazon API logs
  
• Amazon Certificate Manager for Private CAs used for client TLS authentication
  
• Amazon CloudFormation for describing and provisioning Amazon MSK clusters using code
  
• Amazon Kinesis Data Analytics for fully managed Apache Flink applications that process streaming data
  
• Amazon Secrets Manager for client credentials used for SASL/SCRAM authentication
  

Q: How can I scale up storage in my cluster?

You can scale up storage in your provisioned clusters using the Amazon Management Console or the Amazon CLI. You can also use tiered storage to virtually store unlimited data on your cluster without having to add brokers for storage. In serverless clusters, storage is scaled seamlessly based on your usage.

Q. How can I automatically expand storage in my cluster?

You can create an auto scaling policy for storage using the Amazon Web Services Management console or by creating an Amazon Web Services Application Auto scaling Policy using the Amazon CLI or APIs.

Q. Can I scale a broker instance size in an existing cluster?

Yes. You can choose to scale to a smaller or larger broker type on your Amazon MSK clusters.

Q: How do I balance partitions across brokers?

You can use Cruise Control for automatically rebalancing partitions to manage I/O heat. See the Cruise Control documentation for more information. Alternatively, you can use the Kafka Admin API kafka-reassign-partitions.sh to reassign partitions across brokers.

Q: How does tiered storage work?

Apache Kafka stores data in files called log segments. As each segment is complete, based on the size configured at cluster or topic level, it is copied to the low-cost storage tier. Data is held in performance optimized storage for a specified retention time, or size, and then deleted. There is a separate time and size limit setting for the low-cost storage, which will be longer than the primary storage tier. If clients request data from segments stored in the low-cost tier, the broker will read the data from it and serve the data in the same way as if it is being served from the primary storage.

Q: How does Amazon MSK pricing work?

Pricing is per broker-hour and per GB-month of storage provisioned. Amazon Web Services data transfer rates apply for data transfer in and out of Amazon MSK. For more information, visit our pricing page.

Q: Do I pay for data transfer as a result of data replication?

No, all in-cluster data transfer is included with the service at no additional charge.

Q: How does data transfer pricing work?

You will pay standard Amazon Web Services data transfer charges for data transferred in and out of an Amazon MSK cluster. You will not be charged for data transfer within the cluster in a region, including data transfer between brokers and data transfer between brokers and Apache ZooKeeper nodes.