Using Lambda with Amazon MSK - Amazon Lambda
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Using Lambda with Amazon MSK

Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that you can use to build and run applications that use Apache Kafka to process streaming data. Amazon MSK simplifies the setup, scaling, and management of clusters running Kafka. Amazon MSK also makes it easier to configure your application for multiple Availability Zones and for security with Amazon Identity and Access Management (IAM). Amazon MSK supports multiple open-source versions of Kafka.

Amazon MSK as an event source operates similarly to using Amazon Simple Queue Service (Amazon SQS) or Amazon Kinesis. Lambda internally polls for new messages from the event source and then synchronously invokes the target Lambda function. Lambda reads the messages in batches and provides these to your function as an event payload. The maximum batch size is configurable. (The default is 100 messages.)

For an example of how to configure Amazon MSK as an event source, see Using Amazon MSK as an event source for Amazon Lambda on the Amazon Compute Blog. For a complete tutorial, see Amazon MSK Lambda Integration in the Amazon MSK Labs.

For Kafka-based event sources, Lambda supports processing control parameters, such as batching windows and batch size. For more information, see Batching behavior.

Lambda reads the messages sequentially for each partition. After Lambda processes each batch, it commits the offsets of the messages in that batch. If your function returns an error for any of the messages in a batch, Lambda retries the whole batch of messages until processing succeeds or the messages expire.

Lambda can run your function for up to 14 minutes. Configure your function timeout to be 14 minutes or less (the default timeout value is 3 seconds). Lambda may retry invocations that exceed 14 minutes.

Lambda sends the batch of messages in the event parameter when it invokes your function. The event payload contains an array of messages. Each array item contains details of the Amazon MSK topic and partition identifier, together with a timestamp and a base64-encoded message.

{ "eventSource":"aws:kafka", "eventSourceArn":"arn:aws:kafka:sa-east-1:123456789012:cluster/vpc-2priv-2pub/751d2973-a626-431c-9d4e-d7975eb44dd7-2", "records":{ "mytopic-0":[ { "topic":"mytopic", "partition":0, "offset":15, "timestamp":1545084650987, "timestampType":"CREATE_TIME", "value":"SGVsbG8sIHRoaXMgaXMgYSB0ZXN0Lg==", "headers":[ { "headerKey":[ 104, 101, 97, 100, 101, 114, 86, 97, 108, 117, 101 ] } ] } ] } }

MSK cluster authentication

Lambda needs permission to access the Amazon MSK cluster, retrieve records, and perform other tasks. Amazon MSK supports several options for controlling client access to the MSK cluster.

Unauthenticated access

If no clients access the cluster over the internet, you can use unauthenticated access.

SASL/SCRAM authentication

Amazon MSK supports Simple Authentication and Security Layer/Salted Challenge Response Authentication Mechanism (SASL/SCRAM) authentication with Transport Layer Security (TLS) encryption. For Lambda to connect to the cluster, you store the authentication credentials (user name and password) in an Amazon Secrets Manager secret.

For more information about using Secrets Manager, see User name and password authentication with Amazon Secrets Manager in the Amazon Managed Streaming for Apache Kafka Developer Guide.

Amazon MSK doesn't support SASL/PLAIN authentication.

IAM role-based authentication

You can use IAM to authenticate the identity of clients that connect to the MSK cluster. To create and deploy IAM user or role-based policies, use the IAM console or API. For more information, see IAM access control in the Amazon Managed Streaming for Apache Kafka Developer Guide.

To allow Lambda to connect to the MSK cluster, read records, and perform other required actions, add the following permissions to your function's execution role.

{ "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": [ "kafka-cluster:Connect", "kafka-cluster:DescribeGroup", "kafka-cluster:AlterGroup", "kafka-cluster:DescribeTopic", "kafka-cluster:ReadData", "kafka-cluster:DescribeClusterDynamicConfiguration" ], "Resource": [ "arn:aws:kafka:region:account-id:cluster/cluster-name/cluster-uuid", "arn:aws:kafka:region:account-id:topic/cluster-name/cluster-uuid/topic-name", "arn:aws:kafka:region:account-id:group/cluster-name/cluster-uuid/group-name" ] } ] }

You can scope these permissions to a specific cluster, topic, and group. For more information, see the Amazon MSK Kafka actions in the Amazon Managed Streaming for Apache Kafka Developer Guide. The group name that IAM uses is equivalent to the event source mapping's UUID.

Mutual TLS authentication

Mutual TLS (mTLS) provides two-way authentication between the client and server. The client sends a certificate to the server for the server to verify the client, and the server sends a certificate to the client for the client to verify the server.

For Amazon MSK, Lambda acts as the client. You configure a client certificate (as a secret in Secrets Manager) to authenticate Lambda with the brokers in your MSK cluster. The client certificate must be signed by a CA in the server's trust store. The MSK cluster sends a server certificate to Lambda to authenticate the brokers with Lambda. The server certificate must be signed by a certificate authority (CA) that's in the Amazon trust store.

For instructions on how to generate a client certificate, see Introducing mutual TLS authentication for Amazon MSK as an event source.

Amazon MSK doesn't support self-signed server certificates, because all brokers in Amazon MSK use public certificates signed by Amazon Trust Services CAs, which Lambda trusts by default.

For more information about mTLS for Amazon MSK, see Mutual TLS Authentication in the Amazon Managed Streaming for Apache Kafka Developer Guide.

Configuring the mTLS secret

The CLIENT_CERTIFICATE_TLS_AUTH secret requires a certificate field and a private key field. For an encrypted private key, the secret requires a private key password. Both the certificate and private key must be in PEM format.

Note

Lambda supports the PBES1 (but not PBES2) private key encryption algorithms.

The certificate field must contain a list of certificates, beginning with the client certificate, followed by any intermediate certificates, and ending with the root certificate. Each certificate must start on a new line with the following structure:

-----BEGIN CERTIFICATE----- <certificate contents> -----END CERTIFICATE-----

Secrets Manager supports secrets up to 65,536 bytes, which is enough space for long certificate chains.

The private key must be in PKCS #8 format, with the following structure:

-----BEGIN PRIVATE KEY----- <private key contents> -----END PRIVATE KEY-----

For an encrypted private key, use the following structure:

-----BEGIN ENCRYPTED PRIVATE KEY----- <private key contents> -----END ENCRYPTED PRIVATE KEY-----

The following example shows the contents of a secret for mTLS authentication using an encrypted private key. For an encrypted private key, you include the private key password in the secret.

{ "privateKeyPassword": "testpassword", "certificate": "-----BEGIN CERTIFICATE----- MIIE5DCCAsygAwIBAgIRAPJdwaFaNRrytHBto0j5BA0wDQYJKoZIhvcNAQELBQAw ... j0Lh4/+1HfgyE2KlmII36dg4IMzNjAFEBZiCRoPimO40s1cRqtFHXoal0QQbIlxk cmUuiAii9R0= -----END CERTIFICATE----- -----BEGIN CERTIFICATE----- MIIFgjCCA2qgAwIBAgIQdjNZd6uFf9hbNC5RdfmHrzANBgkqhkiG9w0BAQsFADBb ... rQoiowbbk5wXCheYSANQIfTZ6weQTgiCHCCbuuMKNVS95FkXm0vqVD/YpXKwA/no c8PH3PSoAaRwMMgOSA2ALJvbRz8mpg== -----END CERTIFICATE-----", "privateKey": "-----BEGIN ENCRYPTED PRIVATE KEY----- MIIFKzBVBgkqhkiG9w0BBQ0wSDAnBgkqhkiG9w0BBQwwGgQUiAFcK5hT/X7Kjmgp ... QrSekqF+kWzmB6nAfSzgO9IaoAaytLvNgGTckWeUkWn/V0Ck+LdGUXzAC4RxZnoQ zp2mwJn2NYB7AZ7+imp0azDZb+8YG2aUCiyqb6PnnA== -----END ENCRYPTED PRIVATE KEY-----" }

Managing API access and permissions

In addition to accessing the Amazon MSK cluster, your function needs permissions to perform various Amazon MSK API actions. You add these permissions to the function's execution role. If your users need access to any of the Amazon MSK API actions, add the required permissions to the identity policy for the IAM user or role.

Required Lambda function execution role permissions

Your Lambda function's execution role must have the following permissions to access the MSK cluster on your behalf. You can either add the Amazon managed policy AWSLambdaMSKExecutionRole to your execution role, or create a custom policy with permission to perform the following actions:

Adding permissions to your execution role

Follow these steps to add the Amazon managed policy AWSLambdaMSKExecutionRole to your execution role using the IAM console.

To add an Amazon managed policy

  1. Open the Policies page of the IAM console.

  2. In the search box, enter the policy name (AWSLambdaMSKExecutionRole).

  3. Select the policy from the list, and then choose Policy actions, Attach.

  4. On the Attach policy page, select your execution role from the list, and then choose Attach policy.

Granting users access with an IAM policy

By default, IAM users and roles don't have permission to perform Amazon MSK API operations. To grant access to users in your organization or account, you can add or update an identity-based policy. For more information, see Amazon MSK Identity-Based Policy Examples in the Amazon Managed Streaming for Apache Kafka Developer Guide.

Using SASL/SCRAM authentication

Amazon MSK supports Simple Authentication and Security Layer/Salted Challenge Response Authentication Mechanism (SASL/SCRAM) authentication with TLS encryption. You can control access to your Amazon MSK clusters by setting up user name and password authentication using an Amazon Secrets Manager secret. For more information, see Username and password authentication with Amazon Secrets Manager in the Amazon Managed Streaming for Apache Kafka Developer Guide.

Note that Amazon MSK does not support SASL/PLAIN authentication.

Authentication and authorization errors

If any of the permissions required to consume data from the Amazon MSK cluster are missing, Lambda displays one of the following error messages in the event source mapping under LastProcessingResult.

Cluster failed to authorize Lambda

For SASL/SCRAM or mTLS, this error indicates that the provided user doesn't have all of the following required Kafka access control list (ACL) permissions:

  • DescribeConfigs Cluster

  • Describe Group

  • Read Group

  • Describe Topic

  • Read Topic

For IAM access control, your function's execution role is missing one or more of the permissions required to access the group or topic. Review the list of required permissions in IAM role-based authentication.

When you create either Kafka ACLs or an IAM policy with the required Kafka cluster permissions, specify the topic and group as resources. The topic name must match the topic in the event source mapping. The group name must match the event source mapping's UUID.

After you add the required permissions to the execution role, it might take several minutes for the changes to take effect.

SASL authentication failed

For SASL/SCRAM, this error indicates that the provided user name and password aren't valid.

For IAM access control, the execution role is missing the kafka-cluster:Connect permission for the MSK cluster. Add this permission to the role and specify the cluster's Amazon Resource Name (ARN) as a resource.

You might see this error occurring intermittently. The cluster rejects connections after the number of TCP connections exceeds the Amazon MSK service quota. Lambda backs off and retries until a connection is successful. After Lambda connects to the cluster and polls for records, the last processing result changes to OK.

Server failed to authenticate Lambda

This error indicates that the Amazon MSK Kafka brokers failed to authenticate with Lambda. This can occur for any of the following reasons:

  • You didn't provide a client certificate for mTLS authentication.

  • You provided a client certificate, but the brokers aren't configured to use mTLS.

  • A client certificate isn't trusted by the brokers.

Provided certificate or private key is invalid

This error indicates that the Amazon MSK consumer couldn't use the provided certificate or private key. Make sure that the certificate and key use PEM format, and that the private key encryption uses a PBES1 algorithm.

Network configuration

Lambda must have access to the Amazon Virtual Private Cloud (Amazon VPC) resources associated with your Amazon MSK cluster. We recommend that you deploy Amazon PrivateLink VPC endpoints for Lambda and Amazon Security Token Service (Amazon STS). If authentication is required, also deploy a VPC endpoint for Secrets Manager.

Alternatively, ensure that the VPC associated with your MSK cluster includes one NAT gateway per public subnet. For more information, see Internet and service access for VPC-connected functions.

Configure your Amazon VPC security groups with the following rules (at minimum):

  • Inbound rules – Allow all traffic on the Amazon MSK broker port (9092 for plaintext, 9094 for TLS, 9096 for SASL, 9098 for IAM) for the security groups specified for your event source.

  • Outbound rules – Allow all traffic on port 443 for all destinations. Allow all traffic on the Amazon MSK broker port (9092 for plaintext, 9094 for TLS, 9096 for SASL, 9098 for IAM) for the security groups specified for your event source.

  • If you are using VPC endpoints instead of a NAT gateway, the security groups associated with the VPC endpoints must allow all inbound traffic on port 443 from the event source's security groups.

Note

Your Amazon VPC configuration is discoverable through the Amazon MSK API. You don't need to configure it during setup using the create-event-source-mapping command.

For more information about configuring the network, see Setting up Amazon Lambda with an Apache Kafka cluster within a VPC on the Amazon Compute Blog.

Adding Amazon MSK as an event source

To create an event source mapping, add Amazon MSK as a Lambda function trigger using the Lambda console, an Amazon SDK, or the Amazon Command Line Interface (Amazon CLI).

This section describes how to create an event source mapping using the Lambda console and the Amazon CLI.

Prerequisites

  • An Amazon MSK cluster and a Kafka topic. For more information, see Getting Started Using Amazon MSK in the Amazon Managed Streaming for Apache Kafka Developer Guide.

  • An execution role with permission to access the Amazon resources that your MSK cluster uses.

Adding an Amazon MSK trigger (console)

Follow these steps to add your Amazon MSK cluster and a Kafka topic as a trigger for your Lambda function.

To add an Amazon MSK trigger to your Lambda function (console)

  1. Open the Functions page of the Lambda console.

  2. Choose the name of your Lambda function.

  3. Under Function overview, choose Add trigger.

  4. Under Trigger configuration, do the following:

    1. Choose the MSK trigger type.

    2. For MSK cluster, select your cluster.

    3. For Batch size, enter the maximum number of messages to receive in a single batch.

    4. For Topic name, enter the name of a Kafka topic.

    5. (Optional) For Starting position, choose Latest to start reading the stream from the latest record. Or, choose Trim horizon to start at the earliest available record.

    6. (Optional) For Authentication, choose the secret key for authenticating with the brokers in your MSK cluster.

    7. To create the trigger in a disabled state for testing (recommended), clear Enable trigger. Or, to enable the trigger immediately, select Enable trigger.

  5. To create the trigger, choose Add.

Adding an Amazon MSK trigger (Amazon CLI)

Use the following example Amazon CLI commands to create and view an Amazon MSK trigger for your Lambda function.

Creating a trigger using the Amazon CLI

The following example uses the create-event-source-mapping Amazon CLI command to map a Lambda function named my-kafka-function to a Kafka topic named AWSKafkaTopic. The topic's starting position is set to LATEST.

aws lambda create-event-source-mapping \ --event-source-arn arn:aws-cn:kafka:us-west-2:arn:aws-cn:kafka:us-west-2:111111111111:cluster/my-cluster/fc2f5bdf-fd1b-45ad-85dd-15b4a5a6247e-2 \ --topics AWSKafkaTopic \ --starting-position LATEST \ --function-name my-kafka-function

For more information, see the CreateEventSourceMapping API reference documentation.

Viewing the status using the Amazon CLI

The following example uses the get-event-source-mapping Amazon CLI command to describe the status of the event source mapping that you created.

aws lambda get-event-source-mapping \ --uuid 6d9bce8e-836b-442c-8070-74e77903c815

Auto scaling of the Amazon MSK event source

When you initially create an Amazon MSK event source, Lambda allocates one consumer to process all partitions in the Kafka topic. Each consumer has multiple processors running in parallel to handle increased workloads. Additionally, Lambda automatically scales up or down the number of consumers, based on workload. To preserve message ordering in each partition, the maximum number of consumers is one consumer per partition in the topic.

In one-minute intervals, Lambda evaluates the consumer offset lag of all the partitions in the topic. If the lag is too high, the partition is receiving messages faster than Lambda can process them. If necessary, Lambda adds or removes consumers from the topic. The scaling process of adding or removing consumers occurs within three minutes of evaluation.

If your target Lambda function is overloaded, Lambda reduces the number of consumers. This action reduces the workload on the function by reducing the number of messages that consumers can retrieve and send to the function.

To monitor the throughput of your Kafka topic, view the Offset lag metric Lambda emits while your function processes records.

To check how many function invocations occur in parallel, you can also monitor the concurrency metrics for your function.

Amazon CloudWatch metrics

Lambda emits the OffsetLag metric while your function processes records. The value of this metric is the difference in offset between the last record written to the Kafka event source topic, and the last record that Lambda processed. You can use OffsetLag to estimate the latency between when a record is added and when your function processes it.

An increasing trend in OffsetLag can indicate issues with your function. For more information, see Working with Lambda function metrics.

Amazon MSK configuration parameters

All Lambda event source types share the same CreateEventSourceMapping and UpdateEventSourceMapping API operations. However, only some of the parameters apply to Amazon MSK.

Event source parameters that apply to Amazon MSK
Parameter Required Default Notes

BatchSize

N

100

Maximum: 10,000

Enabled

N

Enabled

EventSourceArn

Y

Can set only on Create

FunctionName

Y

SourceAccessConfigurations

N

No credentials

VPC information or SASL/SCRAM authentication credentials for your event source

StartingPosition

Y

TRIM_HORIZON or LATEST

Can set only on Create

Topics

Y

Kafka topic name

Can set only on Create