Billing Instructions for BYOC

Reference to the billing overview, this article provides a detailed explanation of each billing item involved in the AutoMQ Cloud product under the BYOC environment.

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The terms such as cloud providers and Public Cloud providers mentioned in this article refer to mainstream cloud service providers, such as AWS, Google Cloud, Azure, Alibaba Cloud, Tencent Cloud, Huawei Cloud, etc.

AutoMQ Subscription Fees (Payable to AutoMQ)

When using AutoMQ Cloud in a BYOC environment, subscription fees must be paid based on the actual cluster size. The metrics to measure subscription fees for AutoMQ include:

• Message Processing Specification AKU (AutoMQ Kafka Unit): Required, the AKU specification is used to measure the scale of computational resources allocated for message processing within a Kafka cluster. The AKU specification is directly correlated to the cluster's load pressure.

Message Processing Specification AKU Fees

Indicator Constraints

The Message Processing Specification AKU represents the computational processing resources allocated during message transmission within the cluster. The AKU considers resource consumption such as computational processing, storage IOPS, and network throughput.

Allocating appropriate AKU specifications for each AutoMQ instance ensures the required message transmission throughput capability. Based on benchmark performance test results, each additional AKU specification provides the following performance capabilities:

Capabilities Provided by Each 1 AKU		Description
Read/Write Throughput	Write 30 MiB/s or Read 60 MiB/s	Core business metrics and pressure of message read/write calls. If the specified limit is exceeded, it may cause slower service response times, increased RT, or throttling failures. Tip Example: An AutoMQ instance with a write throughput of 60 MiB/s and a read throughput of 240 MiB/s. The instance's write throughput consumption is 60/30 = 2 AKU, and read throughput consumption is 240/60 = 6 AKU, totaling 8 AKU.
Client Request Frequency	800 requests/second	The request frequency and pressure to the server accessed via Kafka Producer and Consumer SDK. If it exceeds the predetermined specifications, it may lead to throttling or increased response time (RT). Request types include: Produce FetchConsumer CommitOffset
Maximum number of partitions	1125	The number of partitions constrains the metadata size that an instance can handle simultaneously. If the specified limit is exceeded, the following issues may occur: Unable to create new topics or expand partitions. Tip AutoMQ's shared storage architecture based on S3 supports 10 times partition performance compared to Apache Kafka at the same cluster scale, without the risk of performance degradation caused by too many partitions. If the default number of partitions does not meet your requirements, please contact us via Obtaining Services▸ .

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In a production environment, it is recommended that applications strictly follow the above capacity specifications to evaluate resource consumption and perform timely scaling to avoid excessive pressure on the cluster, which could affect service stability.

Calculation Rules (example of Hourly Billing)

Each AutoMQ instance (cluster) can specify the required AKU specifications during creation or specification changes. During billing, the number of AKUs consumed in real-time by each instance will be accounted for.

• Scope of statistics: The number of AKUs consumed by each AutoMQ Kafka instance.

• Statistical method: Calculate the peak value within an hourly cycle.

• Aggregation method: Aggregate statistics based on instance granularity.

• Measurement unit: AKU·Hour, where actual consumption is measured on an hourly basis, with any period less than an hour counted as a full hour.

Billing Example (hourly Billing)

Based on the above calculation rules, here are some typical billing scenarios:

Example 1:

A user creates an instance at 10:00 with a capacity of 12 AKUs. At 11:00, the user scales up the instance to 24 AKUs.

From 10:00 to 12:00, the user's actual AKU consumption is:

12 * 1 hour + 24 * 1 hour = 36 AKU·hours.

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The above example uses real-time billing in the cloud market, with subscription fees calculated on an hourly basis. If opting for monthly billing or purchasing a subscription license in advance, you will also need to measure the number of AKUs consumed by each instance.

Cloud Resource Costs (cloud Resources on Which Deployed Instances Depend, Payable to Cloud Providers)

Deploying an AutoMQ instance incurs resource consumption in addition to subscription fees. For example, using Alibaba Cloud as a Cloud provider:

Cloud Product	Specifications and Usage	Dependency Description
VM (Virtual Machine)	Specification: May vary based on different regions. Usage: Scales with user cluster size.	AutoMQ Kafka virtual machine consumption scales with user cluster size. Even without creating instances, at least one machine is consumed for deploying the control panel.
Cloud Disk (Elastic Block Service)	Specifications: PL1 type Usage: Each Kafka data node consumes 40GB	AutoMQ Kafka uses cloud disks to store temporary message data.
Object Storage	Specifications: Standard disaster recovery storage Usage: 2 buckets per environment, storage space scales with the user's environment resource consumption	Core storage dependency of the message cluster. S3 charges based on actual storage space and number of calls.