tencent cloud

Elastic MapReduce

Release Notes and Announcements
Release Notes
Announcements
Security Announcements
Product Introduction
Overview
Strengths
Architecture
Features
Use Cases
Constraints and Limits
Technical Support Scope
Product release
Purchase Guide
EMR on CVM Billing Instructions
EMR on TKE Billing Instructions
EMR Serverless HBase Billing Instructions
Getting Started
EMR on CVM Quick Start
EMR on TKE Quick Start
EMR on CVM Operation Guide
Planning Cluster
Administrative rights
Configuring Cluster
Managing Cluster
Managing Service
Monitoring and Alarms
TCInsight
EMR on TKE Operation Guide
Introduction to EMR on TKE
Configuring Cluster
Cluster Management
Service Management
Monitoring and Ops
Application Analysis
EMR Serverless HBase Operation Guide
EMR Serverless HBase Product Introduction
Quotas and Limits
Planning an Instance
Managing an Instance
Monitoring and Alarms
Development Guide
EMR Development Guide
Hadoop Development Guide
Spark Development Guide
Hbase Development Guide
Phoenix on Hbase Development Guide
Hive Development Guide
Presto Development Guide
Sqoop Development Guide
Hue Development Guide
Oozie Development Guide
Flume Development Guide
Kerberos Development Guide
Knox Development Guide
Alluxio Development Guide
Kylin Development Guide
Livy Development Guide
Kyuubi Development Guide
Zeppelin Development Guide
Hudi Development Guide
Superset Development Guide
Impala Development Guide
Druid Development Guide
TensorFlow Development Guide
Kudu Development Guide
Ranger Development Guide
Kafka Development Guide
Iceberg Development Guide
StarRocks Development Guide
Flink Development Guide
JupyterLab Development Guide
MLflow Development Guide
Practical Tutorial
Practice of EMR on CVM Ops
Data Migration
Practical Tutorial on Custom Scaling
API Documentation
History
Introduction
API Category
Cluster Resource Management APIs
Cluster Services APIs
User Management APIs
Data Inquiry APIs
Scaling APIs
Configuration APIs
Other APIs
Serverless HBase APIs
YARN Resource Scheduling APIs
Making API Requests
Data Types
Error Codes
FAQs
EMR on CVM
Service Level Agreement
Contact Us

Kafka Overview

PDF
フォーカスモード
フォントサイズ
最終更新日: 2025-01-03 15:02:25
Tencent Cloud EMR-Kafka offers the cloud hosting service of open-source Kafka, with convenient Kafka cluster deployment, configuration modification, monitoring and alarming, and other features, providing enterprises and users with safe, stable OLAP solutions. Kafka data pipelines have been the most commonly used data sources and data sinks in stream computing systems. You can import streaming data into a certain topic in Kafka, process it through Flink operators, and output it to another topic in the same or a different Kafka instance. Kafka supports reading/writing data from/to multiple partitions in the same topic, which increases throughput and reduces data skew and hotspots.

Architecture

Both single-node and multi-node architectures are available for your choice based on business needs.

OPS

The console provides out-of-the-box services such as monitoring, log search, and parameter adjustment.

Features

Sending-receiving decoupling: the relationship between producers and consumers is effectively decoupled. Under the premise that the same API constraint is ensured, the processing between producers and consumers can be independently expanded or modified.
Flexibility: Kafka clusters are able to withstand sudden increases in requests without breakdown, effectively improving the robustness of the system.
Orderly reading and writing: Kafka clusters can guarantee the order of messages in a partition. Just like most message queue services, they can also ensure that data is processed in order, greatly improving disk efficiency.
Asynchronous communication: in scenarios where the business does not need to process messages immediately, Kafka clusters provide the asynchronous message processing mechanism. When the traffic is heavy, messages are put into the queue only, and they will be processed after the traffic become lighter, which relieves the system pressure.

Strengths

100% compatibility with open-source Kafka and easy migration

Kafka clusters are compatible with open-source Kafka v1.1.1.
The business system of Kafka clusters is based on the existing code of the open-source Apache Kafka ecosystem. Without any changes to your existing project, you can migrate to the cloud and enjoy the high-performance Kafka services provided by Tencent Cloud.

High performance

Tencent Cloud has improved the service performance, eliminating the need for complicated parameter configuration.
You can upgrade or downgrade configurations on the UI and enjoy high-performance IaaS layer support.

High availability

Leveraging Tencent's years of experience in monitoring technologies, EMR offers comprehensive monitoring on clusters and has a professional OPS team in place that responds to alarms on a 24/7 basis to ensure the high availability of Kafka clusters.
Custom multi-AZ deployment in the same region is supported to improve disaster recovery ability.

High reliability

The disks are highly reliable, making it possible to keep services running even if 50% of the disks become faulty.
Two replicas are created by default, and up to three replicas can be used. The more replicas, the higher the reliability.

ヘルプとサポート

この記事はお役に立ちましたか?

フィードバック