General and Streaming ETL Concepts

Q: What is Streaming ETL?

Streaming ETL is the processing and movement of real-time data from one place to another. ETL is short for the database functions extract, transform, and load. Extract refers to collecting data from some source. Transform refers to any processes performed on that data. Load refers to sending the processed data to a destination, such as a warehouse, a datalake, or an analytical tool.

Q: What is Amazon Kinesis Data Firehose?

Kinesis Data Firehose is a streaming ETL solution. It is the easiest way to load streaming data into data stores and analytics tools. It can capture, transform, and load streaming data into Amazon S3, Amazon Redshift, Amazon Elasticsearch Service, and Splunk, enabling near real-time analytics with existing business intelligence tools and dashboards you’re already using today. It is a fully managed service that automatically scales to match the throughput of your data and requires no ongoing administration. It can also batch, compress, and encrypt the data before loading it, minimizing the amount of storage used at the destination and increasing security.

Q: What is a source in Kinesis Data Firehose?

A source is where your streaming data is continuously generated and captured. For example, a source can be a logging server running on Amazon EC2 instances, an application running on mobile devices, or a sensor on an IoT device. You can connect your sources to Kinesis Data Firehose using 1) Amazon Kinesis Data Firehose API, which uses the AWS SDK for Java, .NET, Node.js, Python, or Ruby. 2) Kinesis Data Stream, where Kinesis Data Firehose reads data easily from an existing Kinesis data stream and load it into Kinesis Data Firehose destinations. 3) AWS natively supported Service like AWS Cloudwatch, AWS EventBridge, AWS IOT, or AWS Pinpoint. For complete list, see the Amazon Kinesis Data Firehose developer guide. 4) Kinesis Agents, which is a stand-alone Java software application that continuously monitors a set of files and sends new data to your stream. 5) Fluentbit, which an open source Log Processor and Forwarder. 6) AWS Lambda, which is a serverless compute service that lets you run code without provisioning or managing servers. You can use write your Lambda function to send traffic from S3 or DynamoDB to Kinesis Data Firehose based on a triggered event.

Q: What is a destination in Kinesis Data Firehose?

A destination is the data store where your data will be delivered. Kinesis Data Firehose currently supports Amazon S3, Amazon Redshift, Amazon Elasticsearch Service, Splunk, Datadog, NewRelic, Dynatrace, Sumologic, LogicMonitor, MongoDB, and HTTP End Point as destinations.

Q: What does Kinesis Data Firehose manage on my behalf?

Kinesis Data Firehose manages all underlying infrastructure, storage, networking, and configuration needed to capture and load your data into Amazon S3, Amazon Redshift, Amazon Elasticsearch Service, or Splunk. You do not have to worry about provisioning, deployment, ongoing maintenance of the hardware, software, or write any other application to manage this process. Kinesis Data Firehose also scales elastically without requiring any intervention or associated developer overhead. Moreover, Kinesis Data Firehose synchronously replicates data across three facilities in an AWS Region, providing high availability and durability for the data as it is transported to the destinations.

Q: How do I use Kinesis Data Firehose?

After you sign up for Amazon Web Services, you can start using Kinesis Data Firehose with the following steps:

  • Create an Kinesis Data Firehose delivery stream through the Firehose Console or the CreateDeliveryStream operation. You can optionally configure an AWS Lambda function in your delivery stream to prepare and transform the raw data before loading the data.
  • Configure your data producers to continuously send data to your delivery stream using the Amazon Kinesis Agent or the Firehose API.
  • Firehose automatically and continuously loads your data to the destinations you specify.

Q: What is a delivery stream in Kinesis Data Firehose?

A delivery stream is the underlying entity of Kinesis Data Firehose. You use Firehose by creating a delivery stream and then sending data to it. You can create an Kinesis Data Firehose delivery stream through the Firehose Console or the CreateDeliveryStream operation. For more information, see Creating a Delivery Stream.

Q: What is a record in Kinesis Data Firehose?

A record is the data of interest your data producer sends to a delivery stream. The maximum size of a record (before Base64-encoding) is 1024 KB.

Q: What are the limits of Kinesis Data Firehose?

For information about limits, see Amazon Kinesis Data Firehose Limits in the developer guide.

Data Sources

Q: What programming languages or platforms can I use to access Kinesis Data Firehose API?

Kinesis Data Firehose API is available in Amazon Web Services SDKs. For a list of programming languages or platforms for Amazon Web Services SDKs, see Tools for Amazon Web Services.

Q: What is Amazon Kinesis Agent?

Kinesis Agent is a pre-built Java application that offers an easy way to collect and send data to your delivery stream. You can install the agent on Linux-based server environments such as web servers, log servers, and database servers. The agent monitors certain files and continuously sends data to your delivery stream. Amazon Kinesis Agent currently supports Amazon Linux, Red Hat Enterprise Linux, and Microsoft Windows. For more information, see Writing with Agents.

Q: Where do I get Amazon Kinesis Agent?

You can download and install Kinesis Agent using the following command and link:

  • On Amazon Linux: sudo yum install –y aws-kinesis-agent
  • On Red Hat Enterprise Linux: sudo yum install –y https://s3.amazonaws.com/streaming-data-agent/aws-kinesis-agent-latest.amzn1.noarch.rpm
  • From GitHub: awlabs/amazon-kinesis-agent
  • On Windows: https://docs.aws.amazon.com/kinesis-agent-windows/latest/userguide/getting-started.html#getting-started-installation

Q: What is the difference between PutRecord and PutRecordBatch operations?

You can add data to an Kinesis Data Firehose delivery stream through Kinesis Agent or Firehose’s PutRecord and PutRecordBatch operations. PutRecord operation allows a single data record within an API call and PutRecordBatch operation allows multiple data records within an API call. For more information, see PutRecord and PutRecordBatch.

Q: How do I add data to my Kinesis Data Firehose delivery stream from my Kinesis Data Stream?

When you create or update your delivery stream through AWS console or Firehose APIs, you can configure a Kinesis Data Stream as the source of your delivery stream. Once configured, Firehose will automatically read data from your Kinesis Data Stream and load the data to specified destinations.

Q: How often does Kinesis Data Firehose read data from my Kinesis stream?
Kinesis Data Firehose calls Kinesis Data Streams GetRecords() once every second for each Kinesis shard.

Q: From where does Kinesis Data Firehose read data when my Kinesis Data Stream is configured as the source of my delivery stream?

Kinesis Data Firehose starts reading data from the LATEST position of your Kinesis Data Stream when it’s configured as the source of a delivery stream. For more information about Kinesis Data Stream position, see GetShardIterator in the Kinesis Data Streams Service API Reference.

Q: Can I configure my Kinesis Data Stream to be the source of multiple Kinesis Data Firehose delivery streams?

Yes, you can. However, note that the GetRecords() call from Kinesis Data Firehose is counted against the overall throttling limit of your Kinesis shard so that you need to plan your delivery stream along with your other Kinesis applications to make sure you won’t get throttled. For more information, see Kinesis Data Streams Limits in the Kinesis Data Streams developer guide.

Q: Can I still add data to delivery stream through Kinesis Agent or Firehose’s PutRecord and PutRecordBatch operations when my Kinesis Data Stream is configured as source?

No, you cannot. When a Kinesis Data Stream is configured as the source of a Kinesis Data Firehose delivery stream, Firehose’s PutRecord and PutRecordBatch operations will be disabled. You should add data to your Kinesis Data Stream through the Kinesis Data Streams PutRecord and PutRecords operations instead.

Q: How do I add data to my delivery stream from AWS IoT?

You add data to your delivery stream from AWS IoT by creating an AWS IoT action that sends events to your delivery stream. For more information. See Writing to Amazon Kinesis Data Firehose Using AWS IoT in the Kinesis Data Firehose developer guide.

Q: How do I add data to my delivery stream from CloudWatch Logs?

You add data to your Kinesis Data Firehose delivery stream from CloudWatch Logs by creating a CloudWatch Logs subscription filter that sends events to your delivery stream. For more information, see Using CloudWatch Logs Subscription Filters in Amazon CloudWatch user guide.

Q: How do I add data to my Kinesis Data Firehose delivery stream from CloudWatch Events?

You add data to your Kinesis Data Firehose delivery stream from CloudWatch Events by creating a CloudWatch Events rule with your delivery stream as target. For more information, see Writing to Amazon Kinesis Data Firehose Using CloudWatch Events in the Kinesis Data Firehose developer guide.

Q: How do I add data to my Amazon Kinesis Data Firehose delivery stream from AWS Eventbridge?

You add data to your Kinesis Data Firehose delivery stream from AWS EventBridge console. For more information, see AWS EventBridge documentation.

Q: What kind of encryption can I use?

Kinesis Data Firehose allows you to encrypt your data after it’s delivered to your Amazon S3 bucket. While creating your delivery stream, you can choose to encrypt your data with an AWS Key Management Service (KMS) key that you own. For more information about KMS, see AWS Key Management Service.

Q: What is the IAM role that I need to specify while creating a delivery stream?

Kinesis Data Firehose assumes the IAM role you specify to access resources such as your Amazon S3 bucket and Amazon Elasticsearch domain. For more information, see Controlling Access with Kinesis Data Firehose in the Kinesis Data Firehose developer guide.

Data Transformation and Format Conversion

Q: How do I prepare and transform raw data in Kinesis Data Firehose?

Kinesis Data Firehose supports built-in data format conversion from data raw or Json into formats like Apache Parquet and Apache ORC required by your destination data stores, without having to build your own data processing pipelines. Kinesis Data Firehose also allows you to dynamically partition your streaming data before delivery to S3 using static or dynamically defined keys like “customer_id” or “transaction_id”. Kinesis Data Firehose groups data by these keys and delivers into key-unique S3 prefixes, making it easier for you to perform high performance, cost efficient analytics in S3 using Athena, EMR, and Redshift Spectrum.

In addition to the built-in format conversion option in Amazon Kinesis Data Firehose, you can also use an AWS Lambda function to prepare and transform incoming raw data in your delivery stream before loading it to destinations. You can configure an AWS Lambda function for data transformation when you create a new delivery stream or when you edit an existing delivery stream. Amazon has created multiple Lambda Blue prints that you can choose from for quick start. For complete list, see the Amazon Kinesis Data Firehose developer guide.

Q: What compression format can I use?

Amazon Kinesis Data Firehose allows you to compress your data before delivering it to Amazon S3. The service currently supports GZIP, ZIP, and SNAPPY compression formats. Only GZIP is supported if the data is further loaded to Amazon Redshift.

Q: How does compression work when I use the CloudWatch Logs subscription feature?

You can use CloudWatch Logs subscription feature to stream data from CloudWatch Logs to Kinesis Data Firehose. All log events from CloudWatch Logs are already compressed in gzip format, so you should keep Firehose’s compression configuration as uncompressed to avoid double-compression. For more information about CloudWatch Logs subscription feature, see Subscription Filters with Amazon Kinesis Data Firehose in the Amazon CloudWatch Logs user guide.

Q: How do I return prepared and transformed data from my AWS Lambda function back to Amazon Kinesis Data Firehose?

All transformed records from Lambda must be returned to Firehose with the following three parameters; otherwise, Firehose will reject the records and treat them as data transformation failure.

  • recordId: Firehose passes a recordId along with each record to Lambda during the invocation. Each transformed record should be returned with the exact same recordId. Any mismatch between the original recordId and returned recordId will be treated as data transformation failure.
  • result: The status of transformation result of each record. The following values are allowed for this parameter: “Ok” if the record is transformed successfully as expected. “Dropped” if your processing logic intentionally drops the record as expected. “ProcessingFailed” if the record is not able to be transformed as expected. Firehose treats returned records with “Ok” and “Dropped” statuses as successfully processed records, and the ones with “ProcessingFailed” status as unsuccessfully processed records when it generates SucceedProcessing.Records and SucceedProcessing.Bytes metrics.
  • data: The transformed data payload after based64 encoding.

Q: What is error logging?

If you enable data transformation with Lambda, Firehose can log any Lambda invocation and data delivery errors to Amazon CloudWatch Logs so that you can view the specific error logs if Lambda invocation or data delivery fails. For more information, see Monitoring with Amazon CloudWatch Logs.

Q: What is source record backup?

If you use data transformation with Lambda, you can enable source record backup, and Amazon Kinesis Data Firehose will deliver the un-transformed incoming data to a separate S3 bucket. You can specify an extra prefix to be added in front of the “YYYY/MM/DD/HH” UTC time prefix generated by Firehose.

Built-in Data Transformation for Amazon S3

Q: When should I use Kinesis Data Firehose dynamic partitioning?

Kinesis Data Firehose dynamic partitioning eliminates the complexities and delays of manual partitioning at the source or after storing the data, and enables faster analytics for querying optimized data sets. This makes the data sets immediately available for analytics tools to run their queries efficiently and enhances fine-grained access control for data. For example, marketing automation customers can partition data on-the-fly by customer id, allowing customer-specific queries to query optimized data sets and deliver results faster. IT operations or security monitoring customers can create groupings based on event timestamp embedded in logs so they can query optimized data sets and get results faster. This feature combined with Amazon Kinesis Data Firehose's existing JSON-to-parquet format conversion feature makes Amazon Kinesis Data Firehose an ideal streaming ETL option for S3.

Q: How do I setup dynamic partitioning with Kinesis Data Firehose?

You can setup Kinesis Data Firehose data partitioning capability through the AWS Management Console, CLIs or SDKs. When you create or update a Kinesis Data Firehose delivery stream, select Amazon S3 as the delivery destination for the delivery stream and enable dynamic partitioning. You can specify keys or create an expression that will be evaluated at runtime to define keys used for partitioning. For example, you can select a data field in the incoming stream such as customer id and define an S3 prefix expression such as customer_id=!{partitionKey:customer_id}/, that will be evaluated in runtime based on the ingested records to define to which S3 prefix deliver the records.

Q: What kind of transformations and data processing can I do with dynamic partitioning and with partitioning keys?

Kinesis Data Firehose supports parquet/orc conversion out of the box when you write your data to Amazon S3. Kinesis Data Firehose also integrates with Lambda function, so you can write your own transformation code. Kinesis Data Firehose also has built-in support for extracting the key data fields from records that are in JSON format. Kinesis Data Firehose also supports the JQ parsing language to enable transformations on those partition keys. To learn more, see the Kinesis Data Firehose developer guide.

Data Delivery and Destinations

Q: Can I keep a copy of all the raw data in my S3 bucket?

Yes, Kinesis Data Firehose can back up all un-transformed records to your S3 bucket concurrently while delivering transformed records to destination. Source record backup can be enabled when you create or update your delivery stream.

Q: How often does Kinesis Data Firehose deliver data to my Amazon S3 bucket?

The frequency of data delivery to Amazon S3 is determined by the S3 buffer size and buffer interval value you configured for your delivery stream. Kinesis Data Firehose buffers incoming data before delivering it to Amazon S3. You can configure the values for S3 buffer size (1 MB to 128 MB) or buffer interval (60 to 900 seconds), and the condition satisfied first triggers data delivery to Amazon S3. If you have Apache parquet or dynamic partitioning enabled, then your buffer size is in MBs and ranges from 64MB to 128MB for Amazon S3 destination, with is 128MB being the default value. Note that in circumstances where data delivery to the destination is falling behind data ingestion into the delivery stream, Kinesis Data Firehose raises the buffer size automatically to catch up and make sure that all data is delivered to the destination.

Q: How is buffer size applied if I choose to compress my data?

Buffer size is applied before compression. As a result, if you choose to compress your data, the size of the objects within your Amazon S3 bucket can be smaller than the buffer size you specify.

Q: What privilege is required for the Amazon Redshift user that I need to specify while creating a delivery stream?

The Amazon Redshift user needs to have Redshift INSERT privilege for copying data from your Amazon S3 bucket to your Redshift cluster.

Q: What do I need to do if my Amazon Redshift cluster is within a VPC?

If your Amazon Redshift cluster is within a VPC, you need to grant Amazon Kinesis Data Firehose access to your Redshift cluster by unblocking Firehose IP addresses from your VPC. For information about how to unblock IPs to your VPC, see Grant Firehose Access to an Amazon Redshift Destination in the Amazon Kinesis Data Firehose developer guide.

Q: Why do I need to provide an Amazon S3 bucket while choosing Amazon Redshift as destination?

For Amazon Redshift destination, Amazon Kinesis Data Firehose delivers data to your Amazon S3 bucket first and then issues Redshift COPY command to load data from your S3 bucket to your Redshift cluster.

Q: What is index rotation for Amazon Elasticsearch Service destination?

Kinesis Data Firehose can rotate your Amazon Elasticsearch Service index based on a time duration. You can configure this time duration while creating your delivery stream. For more information, see Index Rotation for the Amazon Elasticsearch Destination in the Amazon Kinesis Data Firehose developer guide.

Q: Why do I need to provide an Amazon S3 bucket when choosing Amazon Elasticsearch Service as destination?

When loading data into Amazon Elasticsearch Service, Kinesis Data Firehose can back up all of the data or only the data that failed to deliver. To take advantage of this feature and prevent any data loss, you need to provide a backup Amazon S3 bucket.

Q: Can I change the configurations of my delivery stream after it’s created?

You can change the configuration of your delivery stream at any time after it’s created. You can do so by using the Firehose Console or the UpdateDestination operation. Your delivery stream remains in ACTIVE state while your configurations are updated and you can continue to send data to your delivery stream. The updated configurations normally take effect within a few minutes.

When delivering to a VPC destination, you can change the destination endpoint URL, as long as new destination is accessible within the same VPC, subnets and security groups. For changes of VPC, subnets and security groups, you need to re-create the Firehose delivery stream.

Q: Can I use a Kinesis Data Firehose delivery stream in one account to deliver my data into an Amazon Elasticsearch Service domain VPC destination in a different account?

No, your Kinesis Data Firehose delivery stream and destination Amazon Elasticsearch Service domain need to be in the same account.

Q: Can I use a Kinesis Data Firehose delivery stream in one region to deliver my data into an Amazon Elasticsearch Service domain VPC destination in a different region?

No, your Kinesis Data Firehose delivery stream and destination Amazon Elasticsearch Service domain need to be in the same region.

Q: How often does Kinesis Data Firehose deliver data to my Amazon Elasticsearch domain?

The frequency of data delivery to Amazon Elasticsearch Service is determined by the Elasticsearch buffer size and buffer interval values that you configured for your delivery stream. Firehose buffers incoming data before delivering it to Amazon Elasticsearch Service. You can configure the values for Elasticsearch buffer size (1 MB to 100 MB) or buffer interval (60 to 900 seconds), and the condition satisfied first triggers data delivery to Amazon Elasticsearch Service. Note that in circumstances where data delivery to the destination is falling behind data ingestion into the delivery stream, Amazon Kinesis Data Firehose raises the buffer size automatically to catch up and make sure that all data is delivered to the destination.

Q: What is the manifests folder in my Amazon S3 bucket?
For Amazon Redshift destination, Amazon Kinesis Data Firehose generates manifest files to load Amazon S3 objects to Redshift cluster in batch. The manifests folder stores the manifest files generated by Firehose.

Q: How do backed up Elasticsearch documents look like in my Amazon S3 bucket?
If “all documents” mode is used, Amazon Kinesis Data Firehose concatenates multiple incoming records based on buffering configuration of your delivery stream, and then delivers them to your S3 bucket as an S3 object. Regardless of which backup mode is configured, the failed documents are delivered to your S3 bucket using a certain JSON format that provides additional information such as error code and time of delivery attempt. For more information, see Amazon S3 Backup for the Amazon ES Destination in the Amazon Kinesis Data Firehose developer guide.

Q: Can a single delivery stream deliver data to multiple Amazon S3 buckets?

A single delivery stream can only deliver data to one Amazon S3 bucket currently. If you want to have data delivered to multiple S3 buckets, you can create multiple delivery streams.

Q: Can a single delivery stream deliver data to multiple Amazon Redshift clusters or tables?

A single delivery stream can only deliver data to one Amazon Redshift cluster and one table currently. If you want to have data delivered to multiple Redshift clusters or tables, you can create multiple delivery streams.

Q: Can a single delivery stream deliver data to multiple Amazon Elasticsearch Service domains or indexes?

A single delivery stream can only deliver data to one Amazon Elasticsearch Service domain and one index currently. If you want to have data delivered to multiple Amazon Elasticsearch domains or indexes, you can create multiple delivery streams.

Q: How does Amazon Kinesis Data Firehose deliver data to my Amazon Elasticsearch Service domain into a VPC?

When you enable Kinesis Data Firehose to deliver data to an Amazon Elasticsearch Service destination in a VPC, Amazon Kinesis Data Firehose creates one or more cross account elastic network interfaces (ENI) in your VPC for each subnet(s) that you choose. Amazon Kinesis Data Firehose uses these ENIs to deliver the data into your VPC. The number of ENIs scales automatically to meet the service requirements.

Troubleshooting and managing delivery streams

Q: Why do I get throttled when sending data to my Amazon Kinesis Data Firehose delivery stream?

By default, each delivery stream can intake up to 2,000 transactions/second, 5,000 records/second, and 5 MB/second. You can have this limit increased easily by submitting a service limit increase form.

Q: Why do I see duplicated records in my Amazon S3 bucket, Amazon Redshift table, Amazon Elasticsearch index, or Splunk clusters?

Amazon Kinesis Data Firehose uses at least once semantics for data delivery. In rare circumstances such as request timeout upon data delivery attempt, delivery retry by Firehose could introduce duplicates if the previous request eventually goes through.

Q: What happens if data delivery to my Amazon S3 bucket fails?

If your data source is Direct put and the data delivery to your Amazon S3 bucket fails, then Amazon Kinesis Data Firehose will retry to deliver data every 5 seconds for up to a maximum period of 24 hours. If the issue continues beyond the 24-hour maximum retention period, then Amazon Kinesis Data Firehose discards the data.

If your data source is Kinesis Data Streams and the data delivery to your Amazon S3 bucket fails, then Amazon Kinesis Data Firehose will retry to deliver data every 5 seconds for up to a maximum period of what is configured on Kinesis Data Streams.

Q: What happens if data delivery to my Amazon Redshift cluster fails?

If data delivery to your Amazon Redshift cluster fails, Amazon Kinesis Data Firehose retries data delivery every 5 minutes for up to a maximum period of 120 minutes. After 120 minutes, Amazon Kinesis Data Firehose skips the current batch of S3 objects that are ready for COPY and moves on to the next batch. The information about the skipped objects is delivered to your S3 bucket as a manifest file in the errors folder, which you can use for manual backfill. For information about how to COPY data manually with manifest files, see Using a Manifest to Specify Data Files.

Q: What happens if data delivery to my Amazon Elasticsearch domain fails?

For Amazon Elasticsearch Service destination, you can specify a retry duration between 0 and 7200 seconds when creating the delivery stream. If data delivery to your Amazon ES domain fails, Amazon Kinesis Data Firehose retries data delivery for the specified time duration. After the retrial period, Amazon Kinesis Data Firehose skips the current batch of data and moves on to the next batch. Details on skipped documents are delivered to your S3 bucket in the elasticsearch_failed folder, which you can use for manual backfill.

Q: What happens if there is a data transformation failure?

There are two types of failure scenarios when Firehose attempts to invoke your Lambda function for data transformation:

  • The first type is when the function invocation fails for reasons such as reaching network timeout, and hitting Lambda invocation limits. Under these failure scenarios, Firehose retries the invocation for three times by default and then skips that particular batch of records. The skipped records are treated as unsuccessfully processed records. You can configure the number of invocation re-trials between 0 and 300 using the CreateDeliveryStream and UpdateDeliveryStream APIs. For this type of failure, you can also use Firehose’s error logging feature to emit invocation errors to CloudWatch Logs. For more information, see Monitoring with Amazon CloudWatch Logs.
  • The second type of failure scenario occurs when a record’s transformation result is set to “ProcessingFailed” when it is returned from your Lambda function. Firehose treats these records as unsuccessfully processed records. For this type of failure, you can use Lambda’s logging feature to emit error logs to CloudWatch Logs. For more information, see Accessing Amazon CloudWatch Logs for AWS Lambda.

For both types of failure scenarios, the unsuccessfully processed records are delivered to your S3 bucket in the processing_failed folder.

Q: Why is the size of delivered S3 objects larger than the buffer size I specified in my delivery stream configuration?

The size of delivered S3 objects should reflect the specified buffer size most of the time if buffer size condition is satisfied before buffer interval condition. However, when data delivery to destination is falling behind data writing to delivery stream, Firehose raises buffer size dynamically to catch up and make sure that all data is delivered to the destination. In these circumstances, the size of delivered S3 objects might be larger than the specified buffer size.

Q: What is the errors folder in my Amazon S3 bucket?

The errors folder stores manifest files that contain information of S3 objects that failed to load to your Amazon Redshift cluster. You can reload these objects manually through Redshift COPY command. For information about how to COPY data manually with manifest files, see Using a Manifest to Specify Data Files.

Q: What is the elasticsearch_failed folder in my Amazon S3 bucket?

The elasticsearch_failed folder stores the documents that failed to load to your Amazon Elasticsearch domain. You can re-index these documents manually for backfill.

Q: What is the processing_failed folder in my Amazon S3 bucket?

The processing_failed folder stores the records that failed to transform in your AWS Lambda function. You can re-process these records manually.

Q: How do I monitor the operations and performance of my Amazon Kinesis Data Firehose delivery stream?

Firehose Console displays key operational and performance metrics such as incoming data volume and delivered data volume. Amazon Kinesis Data Firehose also integrates with Amazon CloudWatch Metrics so that you can collect, view, and analyze metrics for your delivery streams. For more information about Amazon Kinesis Data Firehose metrics, see Monitoring with Amazon CloudWatch Metrics in the Amazon Kinesis Data Firehose developer guide.

Q: How do I monitor data transformation and delivery failures of my Amazon Kinesis Data Firehose delivery stream?

Amazon Kinesis Data Firehose integrates with Amazon CloudWatch Logs so that you can view the specific error logs if data transformation or delivery fails. You can enable error logging when creating your delivery stream. For more information, see Monitoring with Amazon CloudWatch Logs in the Amazon Kinesis Data Firehose developer guide.

Q: How do I manage and control access to my Amazon Kinesis Data Firehose delivery stream?

Amazon Kinesis Data Firehose integrates with AWS Identity and Access Management, a service that enables you to securely control access to your AWS services and resources for your users. For example, you can create a policy that only allows a specific user or group to add data to your Firehose delivery stream. For more information about access management and control of your stream, see Controlling Access with Amazon Kinesis Data Firehose.

Q: How do I log API calls made to my Amazon Kinesis Data Firehose delivery stream for security analysis and operational troubleshooting?

Amazon Kinesis Data Firehose integrates with AWS CloudTrail, a service that records AWS API calls for your account and delivers log files to you. For more information about API call logging and a list of supported Amazon Kinesis Data Firehose API operations, see Logging Amazon Kinesis Data Firehose API calls Using AWS CloudTrail.

Pricing and billing

Q: Is Kinesis Data Firehose available in the AWS Free Tier?

No. Kinesis Data Firehose is not currently available in AWS Free Tier. AWS Free Tier is a program that offers free trial for a group of AWS services. For more details see AWS Free Tier.

Q: How much does Kinesis Data Firehose cost?

Kinesis Data Firehose uses simple pay as you go pricing. There is neither upfront cost nor minimum fees and you only pay for the resources you use. Amazon Kinesis Data Firehose pricing is based on the data volume (GB) ingested by Firehose, with each record rounded up to the nearest 5KB. For more information about Amazon Kinesis Data Firehose cost, see Amazon Kinesis Data Firehose Pricing.

Q: When I use PutRecordBatch operation to send data to Amazon Kinesis Data Firehose, how is the 5KB roundup calculated?

The 5KB roundup is calculated at the record level rather than the API operation level. For example, if your PutRecordBatch call contains two 1KB records, the data volume from that call is metered as 10KB. (5KB per record)

Q: Does Kinesis Data Firehose cost include Amazon S3, Amazon Redshift, Amazon Elasticsearch Service, and AWS Lambda costs?

No, you will be billed separately for charges associated with Amazon S3, Amazon Redshift, Amazon Elasticsearch Service, and AWS Lambda usage, including storage and request costs. For more information, see Amazon S3 Pricing, Amazon Redshift Pricing, Amazon Elasticsearch Service Pricing, and AWS Lambda Pricing.

Service Level Agreement

Q: What does the Amazon Kinesis Data Firehose SLA guarantee?

Our Amazon Kinesis Data Firehose SLA guarantees a Monthly Uptime Percentage of at least 99.9% for Amazon Kinesis Data Firehose.

Q: How do I know if I qualify for a SLA Service Credit?

You are eligible for a SLA credit for Amazon Kinesis Data Firehose under the Amazon Kinesis Data Firehose SLA if more than one Availability Zone in which you are running a task, within the same region has a Monthly Uptime Percentage of less than 99.9% during any monthly billing cycle.

For full details on all of the terms and conditions of the SLA, as well as details on how to submit a claim, please see the Amazon Kinesis Data Firehose SLA details page.

Learn more about Amazon Kinesis Data Firehose pricing

Visit the pricing page
Ready to get started?
Sign up
Have more questions?
Contact us