huawei-cloud-mrs-host-alarm-diagnose

Huawei Cloud MRS Alarm Diagnosis Skill

Overview

This skill diagnoses Huawei Cloud MRS (MapReduce Service) cluster alarms. Given alarm information (alarm ID, alarm name, occurrence time, cluster ID, node, related service/role), it locates the root cause and outputs repair steps and a verification method.

Architecture: Caller (Agent) → check_api_mode.py (Python, scripts/) determines the API mode → either lakewatch_api_client.py → LakeWatch API → MRS cluster (node resource data, logs, MRS Manager proxy) or manager_api_client.py → MRS Manager REST API (28443). Per-alarm knowledge base (alarms/<alarm_id>.md in lakewatch mode, alarm_manager/<alarm_id>.md in manager mode) drives the diagnosis flow.

Note on language: This SKILL.md, the documents under references/, and the per-alarm knowledge base under alarms/ and alarm_manager/ are all written in English per the repository spec. Commands and code blocks are English throughout.

Applicable Scenarios:

An MRS cluster raises an alarm and the root cause must be located
An on-call engineer needs guided, per-alarm diagnostic steps
Alarm triage where an alarm ID is provided

Typical Use Cases:

"The MRS cluster received alarm 12089, please help diagnose it"
"PMS process abnormal alarm, alarm ID 12007, cluster ID xxx, help me identify the cause"
"Audit log dump failed alarm 12001, diagnose the root cause"
"Abnormal network connectivity between nodes, alarm ID 12089, occurrence time 2026/06/11 16:00:32 GMT+08:00"

Critical Constraints

Important constraints:

Read-only: This skill only runs information-gathering commands (view logs, query status). It MUST NOT run any start/stop, modify, or delete operations.

User confirmation for repair: The skill only provides executable repair steps; it MUST NOT directly execute any repair operation. All repair actions require user confirmation.

Strict execution: Diagnose strictly according to the per-alarm knowledge base content. Fabricating diagnostic commands outside the knowledge base is prohibited.

Prerequisites

1. Python Requirements

Python >= 3.7
Dependencies: pyyaml (YAML parsing), cryptography (Windows AES password encryption only)
Linux uses CryptoAPI for password encryption (no cryptography dependency)
Verify installation: python3 --version (Linux) / python --version (Windows)

This skill does NOT require KooCLI (hcloud). It calls the LakeWatch API through scripts/lakewatch_api_client.py (lakewatch mode) or the MRS Manager REST API through scripts/manager_api_client.py (manager mode). For the client setup, see CLI Installation Guide.

2. LakeWatch Credential Configuration

A valid LakeWatch service account (username + password)
The password MUST be encrypted with --encrypt-password and stored in scripts/lakewatch_api_config.yaml (auth.encrypted_password). Never store the plaintext password.
Security Rules:
- Never expose the LakeWatch password in conversation or command output
- Never ask the user to input the plaintext password in conversation; use the interactive --encrypt-password flow
- The token is cached locally with owner-only file permissions (Win: %TEMP%\lakewatch_token\, Linux: /tmp/lakewatch_token/)

3. MRS Manager Credential Configuration (Manager Mode)

Manager mode is enabled when scripts/manager_api_config.yaml exists and auth.encrypted_password is set.

A valid MRS Manager account (username + password)
Configure the Manager floating IP in server.host (port default 28443). To obtain it, run grep float_ip /opt/huawei/Bigdata/om-server/OMS/workspace/conf/oms.ini on the OMS node, or ask the cluster administrator.
The password MUST be encrypted with python3 scripts/manager_api_client.py --encrypt-password and stored in scripts/manager_api_config.yaml (auth.encrypted_password). Never store the plaintext password.
Security Rules:
- Never expose the Manager password in conversation or command output
- Never ask the user to input the plaintext password in conversation; use the interactive --encrypt-password flow
- Windows AES ciphertext requires the .aes_key file to be migrated together to decrypt on another machine; Linux SCC ciphertext is not portable across clusters
See MRS Manager API Client for the full client usage.

4. Access Permissions

Lakewatch mode: Reachability to the LakeWatch service endpoint (configured in scripts/lakewatch_api_config.yaml server.host/port); the LakeWatch account must have permission to call the MRS Manager proxy and collect node resource/log data on the target cluster
Manager mode: The script runtime environment must be able to reach the Manager port 28443; the Manager account needs read permissions on alarm, host, instance, and log APIs
See IAM Policies for the access model and required roles

Command Format Standard

This skill uses the LakeWatch API client instead of KooCLI. The unified command format is:

# Linux
python3 <skill_dir>/scripts/lakewatch_api_client.py -a <api_name> -p 'key1=value1' -p 'key2=value2'

# Windows
python <skill_dir>/scripts/lakewatch_api_client.py -a <api_name> -p 'key1=value1' -p 'key2=value2'

Element	Rule	Example
`python3` / `python`	Linux uses `python3`, Windows uses `python`	`python3 lakewatch_api_client.py`
`-a, --api`	API name to call (defined in `lakewatch_api_config.yaml`)	`-a collect_alarm_node_res_data`
`-p, --param`	API parameter in `key=value` form, repeatable	`-p 'cluster_id=xxx'`
Quoting	Every `-p` value MUST be wrapped in single quotes to prevent shell parsing of `[] {}	()`

Windows (PowerShell) quote rule: every " inside a value must be replaced with """ (including " inside [] and {}), otherwise the server returns {"message":"Unknown exception","success":false,"code":"500"}:

# Correct on Windows
-p 'keywords=["""ERROR"""]'
-p 'env={"""PID""":"""123"""}'

# Wrong on Windows (will fail)
-p 'keywords=["ERROR"]'

Linux (bash) quote rule: keep " as-is inside the value, wrap the whole value in single quotes:

# Correct on Linux
-p 'keywords=["ERROR","Exception"]'
-p 'env={"PID":"123"}'

For the full API catalog, parameters, and the token/encryption mechanism, see LakeWatch API Client.

MRS Manager API Client (Manager Mode)

When check_api_mode.py reports manager, use manager_api_client.py instead of the LakeWatch client. The unified command format is:

# Linux
python3 <skill_dir>/scripts/manager_api_client.py -a <api_name> -p 'key1=value1' -p 'key2=value2' --json

# Windows
python <skill_dir>/scripts/manager_api_client.py -a <api_name> -p 'key1=value1' -p 'key2=value2' --json

Element	Rule	Example
`python3` / `python`	Linux uses `python3`, Windows uses `python`	`python3 manager_api_client.py`
`-a, --api`	API name to call (defined in `manager_api_apis/`)	`-a get_instances`
`-p, --param`	API parameter in `key=value` form, repeatable	`-p 'service_name=DBService'`
`--json`	JSON formatted output	`--json`
`--auth`	Auth mode: `basic` (default) or `cookie`	`--auth cookie`
Quoting	Same quote rules as the LakeWatch client (`'` wrapping; Windows `"` → `"""`)	`-p 'keywords=["ERROR"]'`

For the full API catalog, authentication modes, metric names, and password encryption mechanism, see MRS Manager API Client.

Workflow

Step 1: Determine Alarm Information

Extract the following alarm information from the user input:

Field	Parameter	Required	Description	Example
Alarm ID	`alarm_id`	Optional	Alarm unique ID, e.g. 12089	`12007`
Alarm name	`alarm_name`	Required	Alarm Chinese name	`PMS进程异常`
Occurrence time	`alarm_time`	Required	Alarm occurrence time	`2026/06/11 16:00:32 GMT+08:00`
Cluster ID	`cluster_id`	Optional	MRS cluster ID	`fd04c789-39d4-4847-8fc9-4572fec9414f`
Host name	`node_name`	Optional	Host where the alarm occurred (from the alarm location info)	`8-5-225-6`
Service name	`server_name`	Optional	Service that raised the alarm (from the alarm location info)	`Manager`
Role name	`role_name`	Optional	Role that raised the alarm (from the alarm location info)	`pms`
Additional info	`additional_info`	Optional	Alarm additional information, usually contains key diagnostic clues

Notes:

A node value containing . is a node IP; otherwise it is a host name.
If the user does not provide the alarm ID or cluster ID, ask the user to provide the relevant information and stop execution.

Step 2: Determine the API Mode and Locate the Per-Alarm Knowledge Base

Step 2-1: Determine the API Mode

Run the mode check script to determine whether diagnosis is based on MRS Manager or LakeWatch:

Windows: python scripts/check_api_mode.py
Linux: python3 scripts/check_api_mode.py

The script checks whether scripts/manager_api_config.yaml exists and whether encrypted_password is filled in, and returns a JSON result:

{"mode": "manager", "reason": "..."}     // manager-based
{"mode": "lakewatch", "reason": "..."}   // lakewatch-based

Rules:

manager_api_config.yaml does not exist → default lakewatch
File exists but encrypted_password is empty → default lakewatch
File exists and encrypted_password is not empty → manager

Step 2-2: Locate the Per-Alarm Knowledge Base

Based on the Step 2-1 result:

lakewatch mode: read alarms/<alarm_id>.md under this skill directory to get the diagnosis flow. Also read LakeWatch API Client for the Python script usage.
manager mode: read alarm_manager/<alarm_id>.md under this skill directory to get the diagnosis flow. Also read MRS Manager API Client for the Python script usage.

If no matching alarm document exists, tell the user: 暂不支持此告警的分析。 (This alarm is not supported for analysis.)

Step 3: Execute Alarm Diagnosis

Follow the per-alarm knowledge base from Step 2 to execute the diagnosis.

Diagnosis execution notes:

Use only the specific commands provided in the per-alarm knowledge base; do not infer log paths yourself
Variable placeholders (e.g. <alarm_time>, <alarm_node>) MUST be substituted with actual values, never hardcoded
Command execution results MUST be summarized with a summarization tool
When running lakewatch_api_client.py or manager_api_client.py, use python on Windows and python3 on Linux
Use the client matching the Step 2-1 mode: lakewatch_api_client.py in lakewatch mode, manager_api_client.py in manager mode
All -p parameter values MUST be wrapped in single quotes; on Windows PowerShell, every " inside a value must be replaced with """
Important: After diagnosis, reflect on the diagnosis results to confirm whether the alarm diagnosis is complete

Command failure handling: When a command fails, skip the current check item and continue with the other checks.

Step 4: Output the Diagnosis Conclusion

Output following the template below:

## Diagnosis Result

| Item | Content |
|------|---------|
| Diagnosis time | [time] |
| Cluster ID | [cluster_id] |
| Alarm name | [alarm_name] |
| Alarm ID | [alarm_id] |
| Alarm node | [node info] |
| Alarm occurrence time | [occurrence time] |

### Root Cause

**Preliminary judgment**: [root cause type]

**Analysis basis**:

- [basis 1]
- [basis 2]

### Repair Suggestion

| Priority | Operation | Description | Needs user confirmation |
|----------|-----------|-------------|-------------------------|
| 1 | [operation 1] | [description] | Yes |
| 2 | [operation 2] | [description] | Yes |

Core Commands

Query Alarm Skill Content

# Query the alarm diagnosis skill content by alarm sequence ID
python3 lakewatch_api_client.py -a query_alarm_skill \
  -p 'cluster_id=<cluster_id>' \
  -p 'alarm_sequence_id=<alarm_serial_no>'

Collect Alarm Node Resource Data

# Collect node resource data for a given strategy (system-load, memory-usage, disk-space, etc.)
python3 lakewatch_api_client.py -a collect_alarm_node_res_data \
  -p 'cluster_id=<cluster_id>' \
  -p 'strategy_name=system-load' \
  -p 'node_name=<node_name>'

Supported strategy_name values include: system-load, memory-usage, disk-space, disk-io, network-io, file-handle, port-check (needs env={"PORT":"<port>"}), high-cpu-processes, high-memory-process, zombie-process, dns-check, network-connectivity-test (needs env={"TARGET_IP":"<ip>"}), process-basic-info (needs env={"process_name":"java"}), process-file-descriptor (needs env={"PID":"<pid>"}), jstack-thread-dump (needs env={"PID":"<pid>"}), disk-health-check, disk-smart-info (needs env={"DISK_DEVICE":"/dev/sda"}), disk-raid-status, ha-resource-status, and more. See LakeWatch API Client for the full list.

Collect Alarm Log Data

# Collect alarm-related log data around the alarm time
python3 lakewatch_api_client.py -a collect_alarm_log_data \
  -p 'cluster_id=<cluster_id>' \
  -p 'alarm_time=2026/06/11 16:00:32 GMT+08:00' \
  -p 'log_directory=/var/log/hadoop/hdfs' \
  -p 'log_file_name=hadoop-hdfs-datanode.log' \
  -p 'keywords=["ERROR","Exception"]' \
  -p 'log_type=local'

When the log time format is non-standard ISO (e.g. [2026-07-07 20:54:25,171]), pass time_pattern:

python3 lakewatch_api_client.py -a collect_alarm_log_data \
  -p 'cluster_id=<cluster_id>' \
  -p 'alarm_time=2026/07/07 20:54:00 GMT+08:00' \
  -p 'log_directory=/var/log/Bigdata/omm/oms/pms' \
  -p 'log_file_name=pms*.log' \
  -p 'keywords=["ERROR","Exception"]' \
  -p 'log_type=local' \
  -p 'time_pattern=^\[([0-9]{4})-([0-9]{2})-([0-9]{2}) ([0-9]{2}):([0-9]{2}):([0-9]{2})||ymdHMS'

Proxy MRS Manager GET API

# Query audit dump config via the LakeWatch manager-access proxy
python3 lakewatch_api_client.py -a access_manager_get \
  -p 'cluster_id=<cluster_id>' \
  -p 'target_url=api/v2/audits/config'

# Query audit logs (returns totalCount)
python3 lakewatch_api_client.py -a access_manager_get \
  -p 'cluster_id=<cluster_id>' \
  -p 'target_url=api/v2/audits?limit=1'

target_url MUST NOT start with /. The proxy requires Agent >= 1.0.5 and reported OMS node info. Only GET is supported currently.

MRS Manager API Commands (Manager Mode)

When in manager mode, use manager_api_client.py for the equivalent queries:

# Query current alarms (with status=1 for active alarms)
python3 manager_api_client.py -a get_alarms -p 'status=1' --json

# Query instance running status of a service
python3 manager_api_client.py -a get_instances \
  -p 'cluster_id=<cluster_id>' \
  -p 'service_name=DBService' \
  --json

# Query host process status
python3 manager_api_client.py -a get_host_process \
  -p 'hostname=<node_name>' \
  --json

# Query host monitor metrics (dev_ prefix)
python3 manager_api_client.py -a get_host_metrics \
  -p 'hostname=<node_name>' \
  -p 'metric_names=dev_cpu_surp_avg,dev_load_one_min' \
  --json

# Query host resource usage
python3 manager_api_client.py -a get_host_resource \
  -p 'hostname=<node_name>' \
  --json

# Search logs by keyword (returns task_id, then poll progress)
python3 manager_api_client.py -a start_log_search \
  -p 'cluster_id=<cluster_id>' \
  -p 'key_word=ERROR' \
  -p 'start_time=<alarm_time>' \
  -p 'end_time=<current_time>' \
  -p 'services=Manager:Manager:Agent' \
  -p 'min_log_level=ERROR' \
  --json

python3 manager_api_client.py -a get_log_search_progress \
  -p 'search_id=<task_id>' \
  --json

# Browse a log file directly (file_name must be a full path)
python3 manager_api_client.py -a browse_log \
  -p 'hostname=<node_name>' \
  -p 'file_name=/var/log/Bigdata/controller/acs/acs.log' \
  -p 'start_line=1' \
  -p 'end_line=200' \
  --json

start_log_search services format: component:service:role (e.g. HDFS:HDFS:NameNode), multiple separated by ;; start_time/end_time format: yyyy-MM-ddTHH:mm:ss. See MRS Manager API Client for metric names and full parameter rules.

Parameter Confirmation

Parameter	Required/Optional	Description	Default
`alarm_id`	Optional	Alarm unique ID, used to locate `alarms/<alarm_id>.md` (lakewatch mode) or `alarm_manager/<alarm_id>.md` (manager mode)	N/A
`alarm_name`	Required	Alarm Chinese name	N/A
`alarm_time`	Required	Alarm occurrence time, format `yyyy/MM/dd HH:mm:ss GMT+X:XX`	N/A
`cluster_id`	Optional	MRS cluster ID	N/A
`node_name`	Optional	Alarm node host name or IP	N/A
`server_name`	Optional	Service that raised the alarm	N/A
`role_name`	Optional	Role that raised the alarm	N/A
`additional_info`	Optional	Alarm additional information	N/A
`strategy_name`	Required by `collect_alarm_node_res_data`	Resource collection strategy (lakewatch mode)	N/A
`log_directory`	Required by `collect_alarm_log_data`	Log directory, must be under `/var/log/` (lakewatch mode)	N/A
`log_file_name`	Required by `collect_alarm_log_data`	Log file name, no path separators (lakewatch mode)	N/A
`keywords`	Required by `collect_alarm_log_data`	Log keyword filter, JSON array (lakewatch mode)	N/A
`log_type`	Required by `collect_alarm_log_data`	`local` or `hdfs` (lakewatch mode)	N/A
`time_pattern`	Optional	Non-standard log time regex, format `regex
`service_name`	Required by `get_instances`	Service name to query instances (manager mode)	N/A
`metric_names`	Required by `get_host_metrics`	Comma-separated monitor metric names with `dev_` prefix (manager mode)	N/A
`key_word`	Required by `start_log_search`	Log keyword to search (manager mode)	N/A
`current_time`	Required by `start_log_search`	Current time, format `yyyy-MM-ddTHH:mm:ss` (manager mode)	N/A

Output Format

The diagnosis report is output in Markdown, containing:

Diagnosis result table: diagnosis time, cluster ID, alarm name, alarm ID, alarm node, alarm occurrence time
Root cause: preliminary judgment + analysis basis (each basis cited from actual command output)
Repair suggestion table: priority, operation, description, needs-user-confirmation (all repair actions require user confirmation)

See the template in the Workflow → Step 4 section.

Verification Method

See Verification Method for the installation, configuration, and function verification steps.

Best Practices

Locate the knowledge base first: Always confirm the alarm ID and run check_api_mode.py, then read alarms/<alarm_id>.md (lakewatch mode) or alarm_manager/<alarm_id>.md (manager mode) before running any command; do not infer diagnostic steps yourself.
Substitute placeholders: Replace <cluster_id>, <alarm_time>, <node_name>, <target_ip>, <current_time>, etc. with actual user-provided values; never hardcode them.
Quote parameters: Always wrap -p values in single quotes; on Windows PowerShell, escape " as """ to avoid code:500 errors.
Time format: alarm_time must follow yyyy/MM/dd HH:mm:ss GMT+X:XX (lakewatch mode) or yyyy-MM-ddTHH:mm:ss (manager mode start_log_search); for non-standard log time formats in lakewatch mode, pass time_pattern.
Summarize results: Use a summarization tool to condense command output before analysis; large raw outputs should not be analyzed directly.
Reflect after diagnosis: After completing the checks, reflect on whether the root cause is confirmed; if not, re-check the per-alarm flow for missed steps.
Read-only: All commands are read-only; repair steps are suggestions only and require user confirmation before execution.

References

Document	Description
CLI Installation Guide	Python dependencies and LakeWatch client setup
IAM Policies	LakeWatch/MRS Manager access model and required roles
Verification Method	Installation, configuration, and function verification
Acceptance Criteria	Pass/fail criteria for skill testing
LakeWatch API Client	Full LakeWatch API catalog, parameters, token and encryption mechanism
MRS Manager API Client	Full MRS Manager API catalog, authentication modes, metric names and encryption mechanism
Related Commands	Common LakeWatch/Manager API commands quick reference
`alarms/<alarm_id>.md`	Per-alarm diagnosis knowledge base (lakewatch mode, mirrors the MRS product alarm catalog)
`alarm_manager/<alarm_id>.md`	Per-alarm diagnosis knowledge base (manager mode, mirrors the MRS product alarm catalog)

Notes

Security: This skill is read-only. It never exposes the LakeWatch or MRS Manager password; passwords are encrypted via --encrypt-password and stored in the corresponding config YAML. Repair steps are suggestions only.
No KooCLI: This skill does not use hcloud; it calls the LakeWatch API through lakewatch_api_client.py or the MRS Manager REST API through manager_api_client.py. Do not mix in hcloud commands.
Mode switching: Run check_api_mode.py to determine the mode. In manager mode use manager_api_client.py and the alarm_manager/ knowledge base; in lakewatch mode use lakewatch_api_client.py and the alarms/ knowledge base. Do not mix clients across modes.
Command failure: When a command fails, skip the current check item and continue with the other checks; do not abort the whole diagnosis.
Known limitations: The access_manager_get proxy only supports GET requests (PUT is not yet available on the Agent side); collect_alarm_log_data requires log_directory to be under /var/log/; some strategy_name values require extra env parameters; in manager mode browse_log requires the full log file path and start_log_search services must follow component:service:role.