All Products
Document Center

Log Service:Usage notes

Last Updated:Aug 25, 2023

Simple Log Service provides the Trace application based on the native OpenTelemetry protocol to implement distributed tracing. You can use the application to import, store, analyze, and visualize trace data. You can also use the application to configure alerts for trace data and manage trace data based on AIOps. This topic describes the background information, features, assets, and billing of the Trace application.

Background information

In modern IT systems, such as cloud-native systems and microservice systems, an external request often requires multiple internal services, middleware, and machines to call each other. During the call process, various issues may occur and cause external service failures or an increased latency. This affects user experience. To identify and analyze issues, you can use the distributed tracing method.

Distributed tracing can provide information about call relationships, latencies, and results of an entire service call link. Distributed tracing is suitable for systems that require interaction between multiple services, such as cloud-native, distributed, and microservices systems.

OpenTelemetry is a globally accepted standard of distributed tracing, and is compatible with OpenTracing and OpenCensus clients. OpenTelemetry provides a collection of APIs, SDKs, and tools. You can use OpenTelemetry to instrument, generate, collect, and export various observable data, including traces, logs, and metrics.


OpenTelemetry defines data formats, and generates, collects, and sends data. OpenTelemetry does not analyze or visualize data and does not support alerting. The Trace application is implemented based on the OpenTelemetry protocol. You can use the application to collect trace data from OpenTelemetry and other platforms, such as Jaeger, Zipkin, and SkyWalking. You can also store, analyze, and visualize trace data, and configure alerts for trace data.

Architecture of the Trace application
  • Multiple import methods

    • You can import trace data over multiple protocols such as OpenTelemetry, Jaeger, and Zipkin.

    • You can import trace data in more than 10 programming languages.

    • You can import trace data from multiple trace platforms.

    • You can import trace data over the Internet, an Alibaba Cloud internal network, and a Global Accelerator (GA) network. An Alibaba Cloud internal network can be the classic network or a virtual private cloud (VPC).

  • Compliance with OpenTelemetry Trace 1.0

    The trace data format of Simple Log Service complies with OpenTelemetry Trace 1.0 and meets the format requirements of cloud-native systems and microservice systems for trace data.

  • High performance

    You can import petabytes of data per day, extract and analyze metrics, precompute data, and sample 100% of trace data in large-scale scenarios.

  • Scalability

    You can configure custom data retention periods. Simple Log Service can dynamically scale the capacity of Logstores to meet your business requirements.

  • Various trace-related features

    You can view trace and service details, query and analyze trace data, analyze dependencies, and perform custom SQL analysis.

  • High compatibility with downstream applications

    Trace data and calculated metrics in Simple Log Service are compatible with various stream processing platforms and batch computing engines. The Trace application also supports the custom processing of subscription data.

  • Multiple built-in AIOps algorithms

    The Trace application can automatically analyze the impact of trace data on performance and error rates. This helps developers identify the root causes of various issues in complex scenarios.


All assets that are created by the Trace application are stored in a specified project. The project contains the following assets:

  • Logstore


    Do not update or delete indexes in the following Logstores. Otherwise, the Trace application becomes unavailable.

    • {instance}-traces: stores the raw trace data that is uploaded.

    • {instance}-traces-metrics: stores the intermediate results of aggregated metrics after trace data is calculated.

    • {instance}-traces-deps: stores the data of dimension call relationships after trace data is calculated.

    • {instance}-logs: stores the raw log data that is uploaded.

  • Metricstore

    {instance}-metrics: stores the uploaded metrics.

  • Scheduled SQL

    • {instance}-metric_info: queries the metrics that are used to aggregate trace data.

    • {instance}-service: queries the dependencies that are used to aggregate trace data at the service granularity.

    • {instance}-service_name_host: queries the dependencies that are used to aggregate trace data at the service, name, and host granularities.

    • {instance}-service_name_host_resource: queries the dependencies that are used to aggregate trace data at the service, name, host, and resource granularities.

  • Dashboard

    • Import overview: displays the basic information about imported trace data, such as the number of traces, number of spans, and import status of each service.

    • Statistics: displays the statistics of imported trace data, such as the latency, queries per second (QPS), and error rate.


  • If your Logstore uses the pay-by-ingested-data billing mode, you are not charged for the Trace application. For more information, see Pay-by-ingested-data.

  • If your Logstore uses the pay-by-feature billing mode, you are charged for the Trace application based on billable items such as index traffic, data storage, read and write traffic, and read traffic over the Internet. For more information about the billable items, see Billable items of pay-by-feature.