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aws_kinesis

Receive messages from one or more Kinesis streams.

Introduced in version 3.36.0.

# Common config fields, showing default values
input:
label: ""
aws_kinesis:
streams: []
dynamodb:
table: ""
create: false
checkpoint_limit: 1
commit_period: 5s
start_from_oldest: true
region: eu-west-1
batching:
count: 0
byte_size: 0
period: ""
check: ""

Consumes messages from one or more Kinesis streams either by automatically balancing shards across other instances of this input, or by consuming shards listed explicitly. The latest message sequence consumed by this input is stored within a DynamoDB table, which allows it to resume at the correct sequence of the shard during restarts. This table is also used for coordination across distributed inputs when shard balancing.

Benthos will not store a consumed sequence unless it is acknowledged at the output level, which ensures at-least-once delivery guarantees. However, this also means that by default messages of a given shard cannot be processed concurrently. In order to increase the number of shard messages that can be processed concurrently increase the field checkpoint_limit.

Table Schema#

It's possible to configure Benthos to create the DynamoDB table required for coordination if it does not already exist. However, if you wish to create this yourself (recommended) then create a table with a string HASH key StreamID and a string RANGE key ShardID.

Batching#

Use the batching fields to configure an optional batching policy. Each stream shard will be batched separately in order to ensure that acknowledgements aren't contaminated. Any other batching mechanism will stall with this input due its sequential transaction model.

Fields#

streams#

One or more Kinesis data streams to consume from. Shards of a stream are automatically balanced across consumers by coordinating through the provided DynamoDB table. Multiple comma separated streams can be listed in a single element. Shards are automatically distributed across consumers of a stream by coordinating through the provided DynamoDB table. Alternatively, it's possible to specify an explicit shard to consume from with a colon after the stream name, e.g. foo:0 would consume the shard 0 of the stream foo.

Type: array
Default: []

dynamodb#

Determines the table used for storing and accessing the latest consumed sequence for shards, and for coordinating balanced consumers of streams.

Type: object

dynamodb.table#

The name of the table to access.

Type: string
Default: ""

dynamodb.create#

Whether, if the table does not exist, it should be created.

Type: bool
Default: false

dynamodb.billing_mode#

When creating the table determines the billing mode.

Type: string
Default: "PAY_PER_REQUEST"
Options: PROVISIONED, PAY_PER_REQUEST.

dynamodb.read_capacity_units#

Set the provisioned read capacity when creating the table with a billing_mode of PROVISIONED.

Type: int
Default: 0

dynamodb.write_capacity_units#

Set the provisioned write capacity when creating the table with a billing_mode of PROVISIONED.

Type: int
Default: 0

checkpoint_limit#

The maximum gap between the in flight sequence versus the latest acknowledged sequence at a given time. Increasing this limit enables parallel processing and batching at the output level to work on individual shards. Any given sequence will not be committed unless all messages under that offset are delivered in order to preserve at least once delivery guarantees.

Type: int
Default: 1

commit_period#

The period of time between each update to the checkpoint table.

Type: string
Default: "5s"

rebalance_period#

The period of time between each attempt to rebalance shards across clients.

Type: string
Default: "30s"

lease_period#

The period of time after which a client that has failed to update a shard checkpoint is assumed to be inactive.

Type: string
Default: "30s"

start_from_oldest#

Whether to consume from the oldest message when a sequence does not yet exist for the stream.

Type: bool
Default: true

region#

The AWS region to target.

Type: string
Default: "eu-west-1"

endpoint#

Allows you to specify a custom endpoint for the AWS API.

Type: string
Default: ""

credentials#

Optional manual configuration of AWS credentials to use. More information can be found in this document.

Type: object

credentials.profile#

A profile from ~/.aws/credentials to use.

Type: string
Default: ""

credentials.id#

The ID of credentials to use.

Type: string
Default: ""

credentials.secret#

The secret for the credentials being used.

Type: string
Default: ""

credentials.token#

The token for the credentials being used, required when using short term credentials.

Type: string
Default: ""

credentials.role#

A role ARN to assume.

Type: string
Default: ""

credentials.role_external_id#

An external ID to provide when assuming a role.

Type: string
Default: ""

batching#

Allows you to configure a batching policy.

Type: object

# Examples
batching:
byte_size: 5000
count: 0
period: 1s
batching:
count: 10
period: 1s
batching:
check: this.contains("END BATCH")
count: 0
period: 1m

batching.count#

A number of messages at which the batch should be flushed. If 0 disables count based batching.

Type: int
Default: 0

batching.byte_size#

An amount of bytes at which the batch should be flushed. If 0 disables size based batching.

Type: int
Default: 0

batching.period#

A period in which an incomplete batch should be flushed regardless of its size.

Type: string
Default: ""

# Examples
period: 1s
period: 1m
period: 500ms

batching.check#

A Bloblang query that should return a boolean value indicating whether a message should end a batch.

Type: string
Default: ""

# Examples
check: this.type == "end_of_transaction"

batching.processors#

A list of processors to apply to a batch as it is flushed. This allows you to aggregate and archive the batch however you see fit. Please note that all resulting messages are flushed as a single batch, therefore splitting the batch into smaller batches using these processors is a no-op.

Type: array
Default: []

# Examples
processors:
- archive:
format: lines
processors:
- archive:
format: json_array
processors:
- merge_json: {}