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Application Real-Time Monitoring Service:Features

Last Updated:Jul 30, 2024

The Application Monitoring sub-service of Application Real-Time Monitoring Service (ARMS) is an application performance management (APM) service. By installing an ARMS agent for your application, you can comprehensively monitor the application without the need to modify your code. You can also keep track of the status of the application, quickly locate abnormal and slow interfaces, identify performance bottlenecks, and restore request parameters. This greatly improves the efficiency of error diagnostics. This topic describes the features of Application Monitoring.

Basic features

Feature

Description

Application overview

Displays the key metrics, upstream and downstream dependent components, and topology of an application.

Application details

Displays the topology, number of requests, response time, number of slow calls, and HTTP status codes of an application and corresponding instances.

Interface monitoring

Monitors the details about interface calls of an application, including SQL calls, NoSQL calls, exceptions, errors, upstream and downstream services, and traces.

Database call monitoring

Monitors the details about database calls of an application, including overview, SQL calls, exceptions, call sources, and traces.

NoSQL call monitoring

Monitors the details about NoSQL calls of an application, including overview, exceptions, and traces.

External call monitoring

Monitors external calls to locate slow or faulty external calls for your application.

Message queue monitoring

Displays the information about message publishing and topic subscription in ApsaraMQ for RocketMQ.

Scheduled task monitoring

Monitors details about a scheduled task, including overview, SQL calls, NoSQL calls, exceptions, errors, downstream services, and traces.

JVM monitoring

Monitors key Java virtual machine (JVM) metrics, such as metrics related to instantaneous garbage collections (GCs), heap memory, non-heap memory, metaspace, direct buffer, and JVM threads.

Thread pool and connection pool monitoring

Monitors thread pool metrics such as the number of core threads, number of existing threads, maximum number of allowed threads, number of active threads, and maximum number of tasks allowed in a task queue.

Host monitoring

Monitors host metrics such as CPU, memory, disk, load, network traffic, and network packets.

Container monitoring

Monitors details about the pods of an application, including CPU, physical memory, network traffic, and network packets.

Exception analysis

Displays details about the exceptions of an application.

Error analysis

Displays details about the errors of an application.

Trace query

Displays the information about each interface call, including duration, status, and the time when the call is made.

Event center

Centralizes, stores, analyzes, and displays event data generated by Alibaba Cloud services. If your application uses a supported service, the event center automatically analyzes and displays the corresponding events in a unified manner. This provides an easy way for you to view and analyze the events.

Trace query

Queries the details of a trace based on a specific trace ID. You can also configure multiple filter conditions to query traces.

Alert rule

Allows you to create custom alert rules that meet the monitoring requirements of your application. If an alert rule is triggered, alert notifications are sent to the contacts or DingTalk group chat based on the specified notification methods.

Custom configurations

Allows you to set the sampling rate of traces, agent switch, and the threshold of slow SQL queries.

Advanced features

Feature

Description

Continuous profiling

Diagnoses CPU utilization and memory usage details based on minimal performance overheads, and categorizes statistics data based on the method, class, and line number. This helps developers optimize programs, reduce latency, increase throughput, and save costs.

Trace Explorer

Allows you to combine filter conditions and aggregation dimensions for real-time analysis based on stored full trace data. This can meet the custom diagnosis requirements in various scenarios.

Memory snapshot

Creates and analyzes memory snapshots to troubleshoot memory issues such as memory leakage and memory waste.

Thread profiling

Displays the thread-specific statistics of CPU time consumption and the number of threads for each type to simulate the code execution process. If the CPU utilization is excessively high or a large number of methods are slow, you can use the thread profiling feature to locate the threads or methods that consumes much CPU.

Log analysis

Analyzes logs to accurately identify the exceptions of your application.

Arthas diagnostics

Utilizes bytecode enhancement to allow you to check the application status without restarting java processes.