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.

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.

Software Service Fees (Paid to AutoMQ)

When using AutoMQ Cloud in a BYOC environment, users need to pay software service fees based on the actual size of their cluster. AutoMQ measures the scale of software service fees based on the following indicators:

• Message Processing Specification AKU (AutoMQ for Kafka Unit): Required. The AKU measures the scale of computational processing resources allocated during the sending and receiving of messages in a Kafka cluster. The AKU specification is positively correlated with the cluster's scale 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
Message Write Throughput	20 MB/s	Core business metrics and pressure for message read/write calls. Exceeding the predetermined specifications may cause slower service response, increased RT, or throttling failures.
Message Read Throughput	20 MB/s
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 the instance can handle simultaneously. If it exceeds the predetermined specifications, it may cause the following issues: Unable to create new Topics or expand partitions.

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.

The above calculation is based on real-time settlement in the cloud marketplace, where software service fees are calculated on an hourly basis. If monthly settlement or pre-purchased subscription licenses are used, the AKU consumption of each instance must also be considered.

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

When deploying AutoMQ instances, in addition to software service fees, users will incur dependent resource consumption. Taking Alibaba Cloud as an example:

Cloud Product	Specifications and Usage	Dependency Description
ECS (Elastic Compute Service)	Specifications: May vary by region. Usage: Scales with the size of the user's cluster	The AutoMQ Kafka virtual host consumption varies with the size of the user's cluster. At least one host is consumed for deploying the control interface even if no instance is created.
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.