Managed Service for OpenTelemetry
Managed Service for OpenTelemetry provides capabilities including end-to-end tracing analysis, application monitoring and alerting, trace topology, and log association analysis for applications that are developed in various programming languages, such as PHP, C++, Go, and Node.js. Based on the open source OpenTelemetry standards, Managed Service for OpenTelemetry allows you to report trace data by using OpenTelemetry, Jaeger, Zipkin, and SkyWalking. You can use the capabilities to quickly identify the performance bottleneck of the distributed application architecture. This helps you save the time required for root cause analysis on wrong or slow requests and improve the efficiency of developing and troubleshooting distributed applications.
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Category |
Feature |
Description |
References |
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Application integration |
Integration with Java applications |
You can report Java application data by using OpenTelemetry, SkyWalking, Jaeger, and Zipkin. |
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Integration with PHP applications |
You can report PHP application data by using OpenTelemetry. |
Use OpenTelemetry to report the trace data of PHP applications | |
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Integration with Go applications |
You can report Go application data by using OpenTelemetry, SkyWalking, Jaeger, and Zipkin. |
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Integration with Python applications |
You can report Python application data by using OpenTelemetry, SkyWalking, and Jaeger. |
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Integration with Node.js applications |
You can report Node.js application data by using OpenTelemetry and SkyWalking. |
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Integration with .NET applications |
You can report .NET application data by using OpenTelemetry, SkyWalking, Jaeger, and Zipkin. |
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Integration with C++ applications |
You can report C++ application data by using OpenTelemetry and Jaeger. |
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Integration with Ruby applications |
You can report Ruby application data by using OpenTelemetry. |
Use OpenTelemetry to report the trace data of Ruby applications | |
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Integration with Swift applications |
You can report Swift application data by using OpenTelemetry. |
Use OpenTelemetry to report Swift application data | |
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Integration with Android applications |
You can report Android application data by using OpenTelemetry. |
Use OpenTelemetry to report the trace data of Android applications | |
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Integration with Rust applications |
You can report Rust application data by using SkyWalking. |
Use SkyWalking to report Rust application data | |
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Integration with NGINX |
You can report the trace data of NGINX by using SkyWalking, Jaeger, and Zipkin. |
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Integration with NGINX Ingresses |
You can report the trace data of NGINX Ingresses to the Managed Service for OpenTelemetry console. |
Enable Tracing Analysis for NGINX Ingresses | |
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Application management |
Application list |
The Applications page displays the integrated applications and common metrics, such as the number of requests, number of errors, and duration. |
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Application overview |
The Overview page displays the information about applications, such as the number of requests, number of errors, duration, and number of instances. |
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Application topology |
The Application Topology page displays the topology of call relationships between the internal services of an application. |
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Provided services |
The Provided Services page displays the details of the services provided by an application, such as span calls, message queues, and scheduled tasks. |
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Used services |
The Used Services page displays the details of the services used by an application, such as external calls, database calls, and message queues. |
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Trace analysis |
This feature is based on full trace data in storage and allows you to specify filter conditions and aggregate dimensions for real-time analysis. This can meet your business requirements in different scenarios. |
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Database analysis |
This feature allows you to filter databases by database type, database name, and instance name. You can also query and analyze abnormal and slow SQL queries. |
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Exception analysis |
This feature allows you to filter exceptions by exception name, span name, and host. You can also optimize the abnormal code. |
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Event analysis |
This feature is based on the detailed data of generated alert events and allows you to specify multiple filter conditions for real-time analysis. This can meet your business requirements in different scenarios. |
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Trace Explorer |
Trace list |
You can quickly filter traces by status, duration, application name, span name, and host address. You can also specify multiple filter conditions for each query. The Trace Explorer page displays trace information based on the specified filter conditions. The displayed information includes the column chart of the numbers of spans and HTTP errors, the time series curve of duration percentile, and the span list. |
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Scatter plot |
On the Scatter plot tab, a time-consumption distribution chart is displayed, with time as the horizontal axis and duration metrics as the vertical axis. You can move the pointer over a point to view the basic information of the corresponding trace. You can click a point to view the call details of the corresponding trace. |
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Trace aggregation |
Trace Explorer allows you to analyze a queried span based on various dimensions. However, you may need to analyze traces that consist of a large number of spans. The trace aggregation feature allows you to query up to 5,000 distributed traces by using the specified conditions and query the corresponding spans based on the trace IDs. Then, you can aggregate the queried spans to obtain the results. During this process, the integrity of the aggregated traces is guaranteed. |
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Trace topology |
The Full Link Topology tab displays an application topology that is generated after traces are aggregated. You can view the topology of call relationships between applications. You can also view the number of requests, number of errors, and response time. |
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Trace details |
In the details panel of a trace, you can view all the spans, start time, errors, total duration of the trace, and the duration of each span. |
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Scenario-based analysis |
Exception analysis |
You can filter exceptions by application name, exception name, span name, and host. You can also optimize the abnormal code. |
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Slow request analysis |
You can select a time range to view the data of all slow requests such as slow spans and slow SQL queries within the specified time range. |
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Database analysis |
You can filter SQL statements by application name, database type, database name, and instance name. For example, you can search for abnormal SQL queries or slow SQL queries. |
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Advanced query |
Trace query |
You can query data based on the trace data stored in a Logstore in Simple Log Service. |
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Log query |
You can query logs based on the trace data stored in a Logstore in Simple Log Service. This feature is applicable to log association scenarios. |
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Alert management |
Alert rules |
You can create an alert rule for a specific application. If an alert is triggered, the system sends alert notifications to the specified contacts by using the specified notification methods. This way, the contacts can resolve issues at the earliest opportunity. Supported alert detection types are detection based on static thresholds and detection based on dynamic thresholds. |
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Alert notifications |
On the Alert Notification page, you can filter alerts and view the content of an alert that is assigned based on a notification policy. You can also manage the generated alerts. |
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Event analysis |
This feature is based on the detailed data of generated alert events and allows you to specify multiple filter conditions for real-time analysis. This can meet your business requirements in different scenarios. |
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Alert policies |
You can create alert policies, such as notification policies, escalation policies, and silence policies. |
Create and manage a notification policy | |
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Alert contacts |
You can set the alert contacts to which alert notifications are sent. The notification methods include phone calls, text messages, emails, DingTalk, WeCom, Lark, and webhook. |
Notification objects | |
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System configuration |
Cluster configuration |
You can enable or disable data capturing. You can also configure and display the data storage period. |
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Log association |
You can configure the association between an application and a Logstore in Simple Log Service to meet the requirements for log association analysis during trace query and analysis. |
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Usage statistics |
You can query the volume of written data by specifying the application name and data type. This helps you estimate costs. |
Resource usage and bills |