Overview

After being reported from hosts and cloud services to LTS, logs will be retained in LTS for the retention period you specify. Once this period ends, LTS will delete them. For example, if you set the retention period to 30 days, logs will be kept for 30 days before being deleted. You can specify the retention period when creating a log group or stream. For details, see Managing Log Groups and Managing Log Streams. Retained logs are deleted once the period is over. For long-term storage or persistent logging, you can transfer logs to other cloud services.

Log transfer refers to when logs are replicated to other cloud services. LTS deletes retained logs once the retention period is over, but the logs that have been transferred to other services are not affected.

Currently, LTS allows you to transfer logs to the following services. Select services as required.

**Table 1** Transfer destination services
Service	Scenario
OBS	OBS provides mass, secure, and cost-effective data storage for you to store data of any type and size. It is suitable for various scenarios, such as enterprise-level backup/archiving, video on demand (VoD), and video monitoring. OBS offers the following storage classes: Standard, Infrequent Access, Archive, and Deep Archive (under restricted OBT), to meet different requirements for storage performance and cost.
DMS for Kafka	DMS for Kafka is a message queuing service using open-source Apache Kafka. It features highly reliable, asynchronous message delivery, and provides Kafka instances with isolated computing, storage, and bandwidth resources. It is widely used for transmitting data between different systems in many industries, including enterprise application, payment, telecommunications, e-commerce, social networking, instant messaging, video, Internet of Things (IoT), and Internet of Vehicle (IoV). Kafka can handle the transmission of massive logs. Applications asynchronously send log messages to message queues. Other components can read the log messages from message queues for further analysis, either in real time or offline. In addition, Kafka can collect key log information to monitor applications.
DIS	Data Ingestion Service (DIS) addresses the challenge of transmitting data from outside the cloud to inside the cloud. It builds data streams for custom applications capable of processing or analyzing streaming data. DIS continuously captures, transmits, and stores terabytes of data from hundreds of thousands of data sources every hour, such as IoT data collection, logs, location-tracking events, website clickstreams, and social media.