The Operating System Console is Alibaba Cloud's official intelligent platform for operating system management and diagnostics. It allows O&M and development teams to visually troubleshoot and manage operating systems, eliminating the need to log in to servers and use multiple command-line tools. You can manage the console through APIs, SDKs, CLIs, and MCP.
Use cases
Daily O&M:
Use System Health to quickly identify server performance bottlenecks.
Use System Diagnosis to automatically analyze complex issues, such as out-of-memory (OOM) process kills, I/O spikes, network jitter, and insufficient memory.
Use Crash Diagnosis to automatically interpret panic logs and receive repair suggestions.
AI/GPU scenarios:
AI Profiling non-intrusively collects full-stack call traces to determine if communication or operators are causing training bottlenecks.
If distributed training slows down due to specific nodes, use GPU Diagnosis to quickly identify the slow nodes.
If training hangs, GPU Diagnosis automatically determines whether the issue is a hardware failure or a communication problem.
Simplified troubleshooting: The OS Copilot allows you to use natural language to troubleshoot kernel-level issues and receive expert-level diagnostic advice.
Region restrictions
This feature is currently available only in the Chinese mainland and China (Hong Kong).
Prerequisites
If you are a RAM user, you must have the
AliyunECSReadOnlyAccess,AliyunSubManageFullAccess, andAliyunSysomFullAccesspolicies.When you log on to the Operating System Console for the first time, click Activate Service to enable console permissions.
Quick start
Log on to the Operating System Console.
In Resource Management > Component Management, install the SysOM component on the target ECS instance.
In Resource Management, confirm that the instance status is Managed.
Go to Overview or other feature modules to use the corresponding features.
Note: You can use some diagnostic features on Unmanaged instances without managing them first.
Features
The navigation pane on the left of the console contains the following feature modules:
Top-level menu | Second-level menu | Description |
Overview | — | Provides a global view of resources and quick-access entry points. |
System Health & Diagnosis | System Health | Monitors the health of clusters and nodes. |
System Diagnosis | Node Diagnosis, Pod Diagnosis, and Historical Diagnosis. | |
Process Hotspot Analysis | Tracks process-level performance hotspots and generates flame graphs. | |
Hotspot Comparison Analysis | Compares hotspots between different points in time or different instances. | |
GPU Performance & Diagnosis (Invitation-only Beta) | GPU Diagnosis | Diagnoses GPU anomalies in AI workloads. |
AI Profiling | Provides full-lifecycle performance observability for AI applications. | |
Continuous GPU Profiling | Continuously analyzes CPU and GPU performance hotspots. | |
Resource Management | Resource Management | Manages instances and clusters. |
Component Management | Installs, upgrades, and uninstalls extension components such as SysOM. | |
Abnormal Event Alarms | Abnormal Event List | Queries and filters abnormal events. |
Policy Management | Creates and manages alarm policies. | |
Subscription Management | — | Provides subscription services for operating system security updates. |
In the upper-right corner of the console, you can also access the OS Copilot intelligent assistant dialog box.
Overview
The Overview page provides a high-level view of your resources and overall system health.
Section | Description |
Resource Management Status | Displays the number of managed clusters and nodes. |
Abnormal Event Dashboard | Displays the current number of abnormal events across six dimensions: cluster, node, disk traffic, memory, scheduling, and network. |
Event Alarms | Summarizes recent abnormal event alarms. |
Subscription Services | Displays your current subscriptions, such as the Anolis 7 security update subscription. |
System health and diagnosis
System health
System health reflects the overall health of a cluster, node, or container, based on key monitoring metrics.
Key features:
Feature | Description |
Cluster health score | Allows you to select a managed cluster and view its health score and health metrics to assess its overall condition. |
Node count and resource monitoring | Displays node distribution and key resource metrics, such as CPU (utilization rate, allocation rate), memory (utilization rate, allocation rate), and disk (I/O utilization rate, allocation rate). |
Historical health trend | View health trends over the last 24 hours, week, or month. |
Abnormal event analysis | Displays the distribution and details of abnormal events, with support for multi-dimensional filtering. It integrates a large language model to provide context-aware root cause analysis and repair suggestions for alarms. |
System diagnosis
System Diagnosis provides multi-dimensional operating system diagnostic capabilities to help you quickly identify and analyze system issues. Use the drop-down list at the top to switch between three diagnosis modes:
Diagnosis modes:
Mode | Description |
Node Diagnosis | Performs system diagnosis on a single node. Multiple diagnosis items are supported. |
Pod Diagnosis | Diagnoses Pods managed by ACK and ACS clusters. This mode is suitable for containerized scenarios. |
Historical Diagnosis | Performs retrospective analysis of historical issues, such as OOM events, on ACS and ECI instances. |
Diagnosis items (Node Diagnosis mode):
Diagnosis type | Diagnosis item | Description | Architectures | Operating systems |
Memory Diagnosis | Panoramic memory analysis | Provides a panoramic view of system memory. It supports Glibc local memory allocation output, Java Native Memory analysis, and detection of tcp_mem and socket leaks. Java memory diagnosis supports large file uploads and generates on-heap and off-heap flame graphs. | x86, ARM64 |
|
OOM diagnosis | Diagnoses and analyzes OOM events with enhanced data collection. | |||
Storage Diagnosis | I/O traffic analysis | Analyzes the distribution and usage of system I/O traffic. | ||
One-click I/O diagnosis | Performs one-click rapid diagnosis for frequently occurring issues such as high I/O latency, I/O bursts, and high I/O wait times. | |||
Network Diagnosis | Packet loss diagnosis | Diagnoses the causes of network packet loss. | ||
Network jitter | Analyzes network jitter issues caused by slow packet reception, softirqs, and scheduler problems. | |||
Scheduling Diagnosis | Scheduling jitter diagnosis | Diagnoses system scheduling jitter issues. | ||
System load diagnosis | Analyzes the causes of an abnormal 1-minute average system load (load1 metric). | |||
Scenario Diagnosis | Crash diagnosis | Analyzes crash causes and provides repair suggestions. Supports hardlock and hung task analysis. | ||
One-Click Diagnosis | One-click diagnosis | Performs a one-click scan for common OS issues and generates a diagnostic report. |
Process hotspot analysis
Analyzes hotspots on a single node over a specific period, generating hotspot time-series charts, flame graphs, and call graphs. It supports hotspot tracking for Java processes (by collecting Java stack information) and querying historical hotspot records.
Item | Description |
Supported architectures | x86 |
Supported operating systems | Alibaba Cloud Linux 2/3/3 Pro, CentOS 7/8, Rocky Linux 8.8 and later, Ubuntu 22.04/24.04, and Anolis OS 7/8 |
Hotspot comparison analysis
Compares hotspots between different points in time or different instances to help identify the causes of performance changes.
Item | Description |
Supported architectures | x86 |
Supported operating systems | Alibaba Cloud Linux 2/3/3 Pro, CentOS 7/8, Rocky Linux 8.8 and later, Ubuntu 22.04/24.04, and Anolis OS 7/8 |
GPU performance and diagnosis (invitation-only beta)
The GPU Performance & Diagnosis module is designed for AI workloads and provides capabilities for GPU-level performance observation, diagnosis, and optimization. This is an advanced feature.
GPU diagnosis
Diagnoses system anomalies in AI workloads and generates diagnostic conclusions, GPU operational status, and AI job status.
Item | Description |
Fault diagnosis | Diagnoses inference service or training anomalies (task hangs, inference latency), GPU hardware anomalies (card drops, XID errors), and NCCL anomalies (network hangs, operator hangs), and locates slow nodes in large language model training. |
Slow node diagnosis | Provides slow node diagnosis for large language model training scenarios. The diagnostic report includes basic information, analysis conclusions, and raw data visualized with Perfetto. |
Supported architecture: x86
Supported operating systems: Alibaba Cloud Linux 2/3, Ubuntu 22.04/24.04
Other requirements: Available only for GPU instances. Requires specific NCCL versions (v2.21.5.1 to v2.28.9.1).
AI profiling
An advanced analysis tool for observing, diagnosing, and optimizing the performance of AI applications throughout their lifecycle. It provides end-to-end performance analysis by tracing cross-layer software stack calls during AI model training and inference. It is non-intrusive and requires no container modifications.
Item | Description |
Tracing scope | Python stack, Torch layer, GPU memory, CudaRuntime, and GPU kernel functions. |
Collection modes | Duration mode (collects data for a specified time, from 1,000 ms to 5,000 ms) and Iteration mode (collects data by iteration, with an option to skip the first n iterations). |
Analysis results | Provides analysis suggestions, CPU/GPU summaries, GPU kernel analysis (including Tensor Cores usage), iteration statistics with differential analysis, and CPU/GPU tracing visualization, which includes a built-in TimeLine view. Diagnostic reports can be exported for offline viewing. |
Supported architecture | x86 |
Supported operating systems | Alibaba Cloud Linux 2/3, Ubuntu 22.04/24.04 |
Other requirements | Python 3.9 to 3.12, torch 2.4 to 2.7, and CUDA 12.0 to 12.8 (excluding 12.7). Available only for GPU instances (A-series, L-series, and T-series cards). The target process must use the GPU and consume at least 0.5 GB of memory per second or per iteration. |
Continuous GPU profiling
Helps analyze performance hotspots of AI applications on both CPUs and GPUs. It visualizes function call stacks and time consumption distribution to locate performance bottlenecks and optimize AI task execution efficiency.
Item | Description |
Analysis views | CPU/GPU heatmap (each column represents 1 second and contains 50 cells, with each cell representing 20 ms), CPU flame graph (hotspot graph of process function call relationships), and GPU flame graph (displays GPU call stack information related to the Python process). |
Prerequisites | Install or upgrade the SysOM component to version 3.9.0 or later. Enabling this feature increases the memory limit of the SysOM Agent from the default of 300 MB to 2 GB. |
Supported architecture | x86 |
Supported operating systems | Alibaba Cloud Linux 2/3, Ubuntu 22.04/24.04 |
Resource management
Resource management
The Resource Management page lets you manage your instances and clusters. The page has three tabs:
Tab | Description |
Managed | Displays a list of managed instances, including resource management expiration time, instance ID/name, health score, image type, SysOM component version, and SysOM component configuration, and allows you to perform canary deployments. |
Unmanaged | Lists unmanaged instances that you can choose to manage. |
Clusters | Displays information about managed clusters, allows you to manage ACK clusters and configure auto scaling for their instances. |
Component management
Manages the entire lifecycle of OS extension components such as SysOM, including installation, upgrades, and uninstallation.
Feature | Description |
Install/upgrade/uninstall components | Manages extension components such as SysOM. Supports Rocky Linux 8.8 and later. |
Canary deployment | Supports canary deployment of components to ACK clusters based on the number of nodes, percentage of nodes, or ACK node labels. |
Configuration management | Supports enabling and configuring features, including the FastOOM feature (monitors node-level memory pressure and triggers a node-level FastOOM process-killing function with regex match details) and the zombie memcg reclamation feature. |
Abnormal event alarms
The Abnormal Event Alarms module provides capabilities for viewing and filtering abnormal events and managing alarm policies.
Abnormal event list
Displays abnormal events detected in the system. You can filter events by time range (last 24 hours, last 3 days, last week, last month, or a custom range) and various other conditions.
The list displays the following information: abnormal event type, description, severity level (Critical/Warning/Info), detection time, and associated cluster name or instance ID.
Supported abnormal event types include abnormal CPU utilization, tcp_mem anomaly, socket leak, abnormal I/O read/write latency, GPU anomaly, and crash event. Alarm information supports push notifications for GPU anomalies and can display Kubernetes label information.
Policy management
Creates and manages alarm policies for abnormal events.
Feature | Description |
Create policy | Creates a new alarm policy by configuring alarm conditions and notification methods. Notifications can be sent through multiple channels, such as email, SMS, and instant messaging tools. |
Policy list | Manages created policies. Displays information such as policy name, number of events, cluster name, and whether the policy is active. |
Subscription management
Subscription Management provides security update subscription services for operating systems that have reached their end-of-life (EOL).
Subscription service | Description |
CentOS 7 security update subscription | CentOS 7 reached its EOL on June 30, 2024. You can obtain security updates through this subscription service. |
Alibaba Cloud Linux 2 Extended Lifecycle Support (ELS) | Alibaba Cloud Linux 2 reached its EOL on March 31, 2024. You can continue to receive support through the ELS service. |
Anolis 7 security update subscription | Anolis OS 7 reached its EOL on June 30, 2024. You can obtain security updates through this subscription service. |
Note: You can unsubscribe from CentOS security update and Alibaba Cloud Linux 2 ELS subscriptions in the console.
OS Copilot
OS Copilot is Alibaba Cloud’s self-developed Linux operating system intelligent assistant. It is available in the dialog box in the upper-right corner of the console and supports natural language Q&A, assisted command execution, script/code generation, and system operations tuning.
Core capabilities:
Capability | Description |
Professional OS Q&A | Provides expert answers to OS-related questions and can include links to documentation in its responses. |
Assisted command execution | Helps generate and execute Linux commands based on natural language descriptions. |
Script/code generation | Automatically generates O&M scripts or code based on your requirements. |
Scenario-based tool integration | Integrates with scenario-based tools such as System Diagnosis to provide a one-stop O&M experience. |
Intelligent diagnosis agent | Includes a new high CPU load diagnosis feature that automatically identifies and analyzes sudden increases in CPU usage to quickly locate hotspot threads or methods. It also guides users through the diagnosis of anomalies such as OOM events by assisting with information collection and automatically running the panoramic memory analysis tool. |
Diagnosis MCP service | Supports the Diagnosis MCP service, allowing third-party intelligent agents to access the console's diagnostic capabilities through MCP. |
How to use:
Linux command line: Use it directly on a server from the command line.
Console dialog box: Start a conversation from the dialog box in the upper-right corner of the console.