mirror of https://gitee.com/anolis/sysom.git
84 lines
3.8 KiB
Python
84 lines
3.8 KiB
Python
from typing import List
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from clogger import logger
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from .base import DiagnosisJobResult, DiagnosisPostProcessor, PostProcessResult
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import json
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class PostProcessor(DiagnosisPostProcessor):
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def parse_diagnosis_result(self, results: List[DiagnosisJobResult]) -> PostProcessResult:
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ret_str = results[0].stdout
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ret_code = 0
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ret_errmsg = ""
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ret = json.loads(ret_str)
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try:
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if ret["success"] != True:
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ret_code = 1
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ret_errmsg = ret["errmsg"]
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except:
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ret_code = 2
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ret_errmsg = "clustermem error!"
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pass
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postprocess_result = PostProcessResult(
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code=ret_code,
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err_msg=ret_errmsg,
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result={}
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)
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# 输出诊断结果
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md_msg = ""
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md_msg = "## 内存分析结果\n\n\n\n%s\n\n\n\n"%ret["root_cause"]
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md_msg = "%s## 修复/进一步排查建议\n\n\n\n%s\n\n\n\n"%(md_msg, ret["suggestion"])
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# markdown 输出诊断结果
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postprocess_result.result["ClustermemResult"] = {"data": md_msg}
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# 计算内存占比数据
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stat_data = []
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node_mem_data = ret["node_data"]["sysom_proc_meminfo"]
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node_mem_used = node_mem_data["MemTotal"] - node_mem_data["MemFree"]
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stat_data.append({"key": "节点内存使用(usage/total)",
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"value": round(node_mem_used * 100 / node_mem_data["MemTotal"], 1)})
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stat_data.append({"key": "节点应用内存(app/usage)",
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"value": round(node_mem_data["user_anon"] * 100 / node_mem_used, 1)})
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stat_data.append({"key": "节点文件缓存\n(cache/usage)",
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"value": round(node_mem_data["user_filecache"] * 100 / node_mem_used, 1)})
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stat_data.append({"key": "节点内核内存(kernel/total)",
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"value":round(node_mem_data["kernel_used"] * 100 / node_mem_data["MemTotal"], 1)})
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if len(ret["pod_name"]) > 0:
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pod_mem_data = ret["pod_data"]["sysom_cg_memUtil"]
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pod_anon_ratio = (pod_mem_data["usage"] - pod_mem_data["active_file"]
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- pod_mem_data["inactive_file"]) * 100 / pod_mem_data["usage"]
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# active_file + inactive_file可能大于usage
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pod_anon_ratio = pod_anon_ratio if pod_anon_ratio > 0 else 0.1
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stat_data.append({"key": "Pod内存使用(usage/limit)", "value": pod_mem_data["mem_util"]})
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stat_data.append({"key": "Pod应用内存(app/usage)", "value": round(pod_anon_ratio, 1)})
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stat_data.append({"key": "Pod文件缓存\n(cache/usage)", "value": pod_mem_data["cache_ratio"]})
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# stat输出内存占比
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postprocess_result.result["UsageResult"] = {"data": stat_data}
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# 显示podmem结果
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datas = []
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# pod page cache高，显示对应pod的podmem结果
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if ret["show_cache"] == "pod":
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pod_name = ret["pod_name"]
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pod_mem = ret["podmem_data"][pod_name]
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for file in pod_mem:
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datas.append({
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"Pod": pod_name,
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"文件名": file[0],
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"文件Cached大小": file[1]
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})
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# 节点page cache高，显示node上所有pod的podmem结果
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elif ret["show_cache"] == "node":
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podmem_data = ret["podmem_data"]
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for key, value in podmem_data.items():
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for file in value:
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datas.append({
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"Pod": key,
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"文件名": file[0],
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"文件Cached大小": file[1]
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})
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# table显示podmem结果
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postprocess_result.result["podmem"] = {"data": datas}
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return postprocess_result |