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aws_s3 output

Sends message parts as objects to an Amazon S3 bucket. Each object is uploaded with the path specified with the path field.

# Common config fields, showing default values
output:
  label: ""
  aws_s3:
    bucket: "" # No default (required)
    path: "${!counter()}-${!timestamp_unix_nano()}.txt"
    tags: {}
    content_type: "application/octet-stream"
    metadata:
      exclude_prefixes: []
    max_in_flight: 64
    batching:
      count: 0
      byte_size: 0
      period: ""
      check: ""

In order to have a different path for each object you should use function interpolations described in Bloblang queries, which are calculated per message of a batch.

Metadata​

Metadata fields on messages will be sent as headers, in order to mutate these values (or remove them) check out the metadata docs.

Tags​

The tags field allows you to specify key/value pairs to attach to objects as tags, where the values support interpolation functions:

output:
  aws_s3:
    bucket: TODO
    path: ${!counter()}-${!timestamp_unix_nano()}.tar.gz
    tags:
      Key1: Value1
      Timestamp: ${!meta("Timestamp")}

Credentials​

By default Expanso Edge will use a shared credentials file when connecting to AWS services. It's also possible to set them explicitly at the component level, allowing you to transfer data across accounts. You can find out more in this document.

Batching​

It's common to want to upload messages to S3 as batched archives, the easiest way to do this is to batch your messages at the output level and join the batch of messages with an archive and/or compress processor.

For example, if we wished to upload messages as a .tar.gz archive of documents we could achieve that with the following config:

output:
  aws_s3:
    bucket: TODO
    path: ${!counter()}-${!timestamp_unix_nano()}.tar.gz
    batching:
      count: 100
      period: 10s
      processors:
        - archive:
            format: tar
        - compress:
            algorithm: gzip

Alternatively, if we wished to upload JSON documents as a single large document containing an array of objects we can do that with:

output:
  aws_s3:
    bucket: TODO
    path: ${!counter()}-${!timestamp_unix_nano()}.json
    batching:
      count: 100
      processors:
        - archive:
            format: json_array

Performance​

This output benefits from sending multiple messages in flight in parallel for improved performance. You can tune the max number of in flight messages (or message batches) with the field max_in_flight.

Fields​

bucket​

The bucket to upload messages to.

Type: string

path​

The path of each message to upload.

This field supports interpolation functions.

Type: string
Default: "${!counter()}-${!timestamp_unix_nano()}.txt"

tags​

Key/value pairs to store with the object as tags.

This field supports interpolation functions.

Type: map of string
Default: {}

content_type​

The content type to set for each object.

This field supports interpolation functions.

Type: string
Default: "application/octet-stream"

content_encoding​

An optional content encoding to set for each object.

This field supports interpolation functions.

Type: string
Default: ""

cache_control​

The cache control to set for each object.

This field supports interpolation functions.

Type: string
Default: ""

content_disposition​

The content disposition to set for each object.

This field supports interpolation functions.

Type: string
Default: ""

content_language​

The content language to set for each object.

This field supports interpolation functions.

Type: string
Default: ""

website_redirect_location​

The website redirect location to set for each object.

This field supports interpolation functions.

Type: string
Default: ""

metadata​

Specify criteria for which metadata values are attached to objects as headers.

Type: object

metadata.exclude_prefixes​

Provide a list of explicit metadata key prefixes to be excluded when adding metadata to sent messages.

Type: array of string
Default: []

storage_class​

The storage class to set for each object.

This field supports interpolation functions.

Type: string
Default: "STANDARD"

Options: STANDARD, REDUCED_REDUNDANCY, GLACIER, STANDARD_IA, ONEZONE_IA, INTELLIGENT_TIERING, DEEP_ARCHIVE

kms_key_id​

An optional server side encryption key.

Type: string
Default: ""

checksum_algorithm​

The algorithm used to create the checksum for each object.

Type: string
Default: ""

Options: CRC32, CRC32C, SHA1, SHA256

server_side_encryption​

An optional server side encryption algorithm.

Type: string
Default: ""

force_path_style_urls​

Forces the client API to use path style URLs, which helps when connecting to custom endpoints.

Type: bool
Default: false

max_in_flight​

The maximum number of messages to have in flight at a given time. Increase this to improve throughput.

Type: int
Default: 64

timeout​

The maximum period to wait on an upload before abandoning it and reattempting.

Type: string
Default: "5s"

object_canned_acl​

The object canned ACL value. Leave empty to omit the ACL from upload requests, which is required for buckets that have ACLs disabled (the AWS default since 2023).

Type: string
Default: ""

Options: ``, private, public-read, public-read-write, authenticated-read, aws-exec-read, bucket-owner-read, bucket-owner-full-control

batching​

Allows you to configure a batching policy.

Type: object

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: ""

batching.check​

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

Type: string
Default: ""

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 of processor

region​

The AWS region to target.

Type: string

endpoint​

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

Type: string

tcp​

TCP socket configuration.

Type: object

tcp.connect_timeout​

Maximum amount of time a dial will wait for a connect to complete. Zero disables.

Type: string
Default: "0s"

tcp.keep_alive​

TCP keep-alive probe configuration.

Type: object

tcp.keep_alive.idle​

Duration the connection must be idle before sending the first keep-alive probe. Zero defaults to 15s. Negative values disable keep-alive probes.

Type: string
Default: "15s"

tcp.keep_alive.interval​

Duration between keep-alive probes. Zero defaults to 15s.

Type: string
Default: "15s"

tcp.keep_alive.count​

Maximum unanswered keep-alive probes before dropping the connection. Zero defaults to 9.

Type: int
Default: 9

tcp.tcp_user_timeout​

Maximum time to wait for acknowledgment of transmitted data before killing the connection. Linux-only (kernel 2.6.37+), ignored on other platforms. When enabled, keep_alive.idle must be greater than this value per RFC 5482. Zero disables.

Type: string
Default: "0s"

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

credentials.id​

The ID of credentials to use.

Type: string

credentials.secret​

The secret for the credentials being used.

Secret

This field contains sensitive information. Use a secret reference rather than a literal value.

Type: string

credentials.token​

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

Secret

This field contains sensitive information. Use a secret reference rather than a literal value.

Type: string

credentials.from_ec2_role​

Use the credentials of a host EC2 machine configured to assume an IAM role associated with the instance.

Type: bool

credentials.role​

A role ARN to assume.

Type: string

credentials.role_external_id​

An external ID to provide when assuming a role.

Type: string

When to Use​

Use aws_s3 output when you need to:

  • Archive processed data for compliance or long-term storage
  • Build a data lake with time-partitioned files for Athena/Spark
  • Store large batches cost-effectively with compression

Don't use this if:

  • You need real-time queries — send to Elasticsearch or a database
  • You're writing small, frequent updates — aggregate first or use DynamoDB
  • You want streaming append to files — use Kinesis Firehose

Common Patterns​

Time-Partitioned Data Lake​

Organize by date for efficient Athena queries:

output:
  aws_s3:
    bucket: my-data-lake
    path: 'events/${!now().ts_format("2006/01/02/15")}/batch-${!timestamp_unix()}.json'
    batching:
      count: 1000
      period: 60s

Compressed Archives​

Reduce storage costs with gzip. content_encoding only labels the object; the batching processors do the actual work: archive joins the batch into one JSON array (one object per batch instead of one per message), then compress gzips it. The unique path token stops consecutive batches from overwriting the same day's key:

output:
  aws_s3:
    bucket: my-archive
    path: 'logs/${!now().ts_format("2006-01-02")}/batch-${!uuid_v4()}.json.gz'
    content_encoding: gzip
    batching:
      byte_size: 10485760  # 10MB batches
      period: 300s         # flush incomplete batches so low-volume data isn't held
      processors:
        - archive:
            format: json_array
        - compress:
            algorithm: gzip
Production Example

See the complete Kafka to S3 pipeline with partitioning, compression, and error handling.