Billing Modes of DMS for Kafka
DMS for Kafka has two billing modes: yearly/monthly and pay-per-use. Learn more about Distributed Message Service for Kafka Pricing Details.
- Yearly/Monthly is a prepaid mode. You need to pay first, and will be billed for your subscription period. The longer the subscription, the bigger the discount. This mode is recommended for mature services that feature long-term stable requirements.
- Pay-per-use is a postpaid mode. You can pay after using the service, and will be billed for your usage duration. The fees are calculated in seconds and settled by hour. This mode allows you to adjust resource usage easily. You do not need to prepare resources in advance, and will not have excessive or insufficient preset resources. This mode is recommended for scenarios such as e-commerce flash sales which feature sudden traffic bursts.
Table 1 compares the two billing modes.
Billing Mode |
Yearly/Monthly |
Pay-per-use |
---|---|---|
Payment |
Prepaid Billed by the required duration specified in your order |
Postpaid Based on the usage duration of your Kafka instance. |
Billing period |
Billed by the required duration specified in your order |
Calculated in seconds, settled by hour. |
Billing items |
Instance and storage space |
Instance and storage space |
Billing mode change |
Can be changed to pay-per-use. The change takes effect only after the yearly/monthly subscription expires. |
Can be changed to yearly/monthly. |
Specification change |
Supported |
Supported |
Whether instances in Recycle Bin are billed |
Yearly/Monthly instances with recycling policies enabled will be moved to Recycle Bin upon unsubscription. After that, they will not generate fees, but their storage will. Yearly/Monthly instances will be changed to pay-per-use ones upon successful recovery. |
Pay-per-use instances with recycling policies enabled will be moved to Recycle Bin upon deletion. After that, they will not generate fees, but their storage will. |
Scenario |
Recommended for long-term use. Suitable and price-friendly for scenarios where the resource usage duration can be estimated. |
Recommended if you want more flexibility. Suitable for scenarios where resource demands fluctuate. |
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