Cloud Computing Intelligence Bureau Preview | Say goodbye to Kafka Streams, make lightweight stream processing easier

Author: not week
Keywords: Kafka ETL, high elasticity, free operation and maintenance, low cost

Alibaba Cloud Message Queue Kafka Edition provides a fully managed service compatible with the Apache Kafka ecosystem, and completely solves the long-term pain points of open source products. It is one of the indispensable products in the big data ecosystem. As Kafka becomes more and more popular, it started out as a simple message bus and gradually became a data integration system. Kafka's reliable delivery capability makes it a perfect data source for streaming systems. In the field of big data engineering, Kafka has played an important role in undertaking upstream and downstream and serial data stream pipelines, and Kafka's application of streaming framework to process messages has gradually become a trend.

When it comes to stream computing, Storm, Spark Streaming, Flink and Kafka Streams are commonly used. At present, these frameworks are relatively mature and have corresponding use cases, but these frameworks have a high threshold for use. First, you must learn the framework and various The use of technologies and specifications, and then migrate the business to these frameworks, and finally use and operate these stream computing frameworks online. Especially in the face of the needs of more than 70% of simple stream processing scenarios, the disadvantages of traditional solutions will continue to be magnified, customers still need to invest large labor costs and high resources, and the entire architecture is also relatively complex. To sum up, the main problems encountered include the following four aspects:

First, the operation and maintenance cost is high. The R&D team writes the code by itself, and requires continuous maintenance in the later stage, which will bring about a large operation and maintenance cost;
Second, the technical cost is high. For many lightweight or simple computing requirements, technical selection is required, and the introduction of a new component will bring high technical costs;
Third, the learning cost is unpredictable. After a component is selected, the R&D team needs to learn and maintain it continuously, which brings unpredictable learning costs;
Fourth, after developers choose open source components, reliability and availability cannot be well guaranteed.

In order to better solve the various problems encountered by traditional stream computing in the face of simple stream processing scenarios, Alibaba Cloud Message Queue Kafka version has also launched a corresponding solution: Kafka ETL.

So how does Alibaba Cloud Kafka ETL solve the above problems?

At 14:00 on February 18th, the live room of the Cloud Computing Intelligence Bureau will answer your questions.

Click here to immediately go to the live room of the Cloud Computing Intelligence Bureau!