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Volcano Engine Function as a Service

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Consuming message queue for Kafka through Function as a Service

This topic introduces the advantages, use scenarios, business cases, and related document links for consuming Message Queue for Kafka through veFaaS.

Advantages

veFaaS is an event-driven, fully managed Serverless computing platform. Through the Kafka Trigger provided by veFaaS, the developers can easily integrate with the Kafka Topic to be consumed, without caring for the consumption message details of veFaaS, and focus on the business logic of handling messages to the maximum.

Low entry cost: There are no language restrictions and you do not need to learn the big data framework. You only need to focus on the message handling logic of businesses.

Low operation cost: no need to manage or maintain underlying infrastructure such as servers, and provides general governance of MQ consumption.

Automatic scaling: automatic scale-in/out for function instances based on business traffic to ensure reliable service operation.

Low resource cost: computing resources are billed based on request count and actual execution time, and there is no charge if no execution is performed, further reducing resource costs. It also supports multiple concurrent requests per instance to improve resource utilization.

Use scenarios

veFaaS is suitable for general large-scale, elastic consumption scenarios, mainly including:

Real-time ETL: use of triggers allows customized processing and storage of upstream data.

Offline consumption: applicable to scenarios with large amounts of data, multiple data sources, and significant traffic variations, considerably reducing costs.

Middleware scenario: maintains and manages numerous consumers without requiring resource or scaling management.

Business cases

TikTok red packet rain wallet transactions

The TikTok red packet rain wallet transaction businesses feature large traffic, low latency, and high stability, accompanied by sudden traffic spikes. By consuming messages from Kafka in real time through veFaaS and writing the red packet transaction messages into the database, tens of millions or even hundreds of millions of users can receive funds within a few minutes. The veFaaS features an instant elastic scaling capability, allowing scaling up consumption in real time based on business traffic and processing requests concurrently, guaranteeing the timeliness and stability of data processing. During business troughs, veFaaS automatically scales down to prevent resource waste.

MQ middle-end business

MQ middle-end business usually demands the processing of hundreds of thousands of message queues, featuring large traffic and multiple upstreams and downstreams. Therefore, it has a high requirement for resource isolation, dynamic scaling, and efficient development and maintenance. Through the Kafka Trigger feature provided by veFaaS, this business can quickly connect with and manage massive Kafka consumers, without needing to pay attention to consumer realization. Users only need to use the programming language that they are familiar with to complete message handling logic, and thus they can efficiently consume, process, and deliver messages. Further, based on the serverless automatic scaling capability provided by functions, users do not need to care about the function resource allocation, because function instances can automatically scale up and down according to business traffic, and users only need to make payments according to function execution duration. For scenarios with evident peaks and troughs, the resource cost is lower. Finally, using the OpenAPI provided by the veFaaS, users can quickly and conveniently build their own business platforms.

User Guide

For information about consuming Message Queue for Kafka through veFaaS, see Creating Kafka Triggers.

To quickly learn about the basic usage process of veFaaS, see Getting started.

Last updated: 2026.08.19 14:06:07