注册观测云账号
先注册一个账号， 注册地址
注册流程很简单，按照提示点点点就完事了
安装采集器Datakit
登录观测云页面，选择「集成」 - 「DataKit」，选择适合自己环境的安装指令，复制。 我这里是linux环境，其他小伙伴可以按照提示选择对应的安装脚本。
1 复制安装指令
2 在服务器上安装 DataKit
DK_DATAWAY="https://openway.guance.com?token=**************" bash -c "$(curl -L https://static.guance.com/datakit/install.sh)"
安装完成，服务会自动启动，程序默认安装在/usr/local/datakit/
3 查询 DataKit 状态
执行命令 systemctl status datakit
4 查看数据
Datakit 安装好后，默认会采集一些数据，可在 「观测云」 - 「基础设施」 - 「主机」查看相关数据
LOG
django配置日志
setting.py中设置日志格式
import ddtrace
# 设置datakit接收链路数据ip地址与端口
ddtrace.tracer.configure(
hostname='127.0.0.1',
port='9529'
)
os.environ['DD_SERVICE'] = 'DJANGO_TEST' # 设置服务名
os.environ['DD_TAGS'] = 'project:django_test,env:test,version:v1' # 设置环境名 设置版本号
os.environ['DD_LOGS_INJECTION'] = 'true' # 开启log注入
LOGGING = {
'version': 1,
'disable_existing_loggers': False,
'formatters': {
'simple': {
'format': '%(asctime)s - %(name)s - %(levelname)s - %(dd.service)s - %(dd.trace_id)s - %(dd.span_id)s - %(message)s'
},
'verbose': {
# '()': DDTraceLoggingFormatter,
# 'format': '{levelname} {asctime} {module} {process:d} {thread:d} {message}',
# 'style': '{',
'format': '%(asctime)s - %(name)s - %(levelname)s - TraceID:%(trace_id)s - SpanID:%(span_id)s - Service:%(service)s - %(message)s'
},
},
'handlers': {
'console': {
'class': 'logging.StreamHandler',
'formatter': 'simple', # 使用自定义的日志格式化程序
},
'file': {
'level': 'DEBUG', # 设置日志级别
'class': 'logging.FileHandler', # 使用 FileHandler 处理器
'filename': 'myapp.log', # 日志文件名
'formatter': 'simple', # 使用自定义的日志格式化程序
},
},
'loggers': {
'django': {
'handlers': ['console','file'],
'level': 'INFO', # 设置日志级别，可以根据需求调整
'propagate': False,
},
},
}
view.py中配置
from django.shortcuts import render,HttpResponse
from django.http import JsonResponse
# Create your views here.
from app01.utils.logger import log
def Test(request):
log.info('hello world')
return render(request,'index.html')
def Getuser(request):
data = {"message": "zhangsan"}
log.info('get user')
return JsonResponse(data)
url.py中配置
from django.contrib import admin
from django.urls import path
from app01 import views
urlpatterns = [
path('admin/', admin.site.urls),
path('test/', views.Test),
path('get_user/', views.Getuser),
]
通过如下命令开启 Python 应用：
ddtrace-run python manage.py runserver 0.0.0.0:8082
访问后，查看日志数据
...
2023-08-30 05:52:39,765 - django.server - WARNING - DJANGO_TEST - 0 - 0 - "GET /otel_test/ HTTP/1.1" 404 2331
2023-08-30 05:52:45,120 - django - INFO - DJANGO_TEST - 8114496497421676062 - 9327308312721880308 - hello world
2023-08-30 05:52:45,124 - django.server - INFO - DJANGO_TEST - 0 - 0 - "GET /test/ HTTP/1.1" 200 1721
2023-08-30 05:52:47,397 - django - INFO - DJANGO_TEST - 8633758971550947871 - 17177623937713897994 - get user
2023-08-30 05:52:47,398 - django.server - INFO - DJANGO_TEST - 0 - 0 - "GET /get_user/ HTTP/1.1" 200 37
2023-08-30 05:52:55,202 - django - INFO - DJANGO_TEST - 6964601362188057752 - 4924727743778452383 - hello world
2023-08-30 05:52:55,204 - django.server - INFO - DJANGO_TEST - 0 - 0 - "GET /test/ HTTP/1.1" 200 1721
...
通过上面的日志可以看到，链路的traceid和spanid被记录到日志中了
日志收集
设置/usr/local/datakit/conf.d/log/logging.conf
# {"version": "1.9.2", "desc": "do NOT edit this line"}
[[inputs.logging]]
## Required
## File names or a pattern to tail.
logfiles = [
"/usr/local/my_python/ddtrace_test/myapp.log",
]
# Only two protocols are supported:TCP and UDP.
# sockets = [
# "tcp://0.0.0.0:9530",
# "udp://0.0.0.0:9531",
# ]
## glob filteer
ignore = [""]
## Your logging source, if it's empty, use 'default'.
source = "django_test"
## Add service tag, if it's empty, use $source.
service = "django_test"
## Grok pipeline script name.
pipeline = ""
## optional status:
## "emerg","alert","critical","error","warning","info","debug","OK"
ignore_status = []
## optional encodings:
## "utf-8", "utf-16le", "utf-16le", "gbk", "gb18030" or ""
character_encoding = ""
## The pattern should be a regexp. Note the use of '''this regexp'''.
## regexp link: https://golang.org/pkg/regexp/syntax/#hdr-Syntax
multiline_match = '''[0-9]{4}-[0-9]{2}-[0-9]{2}'''
auto_multiline_detection = true
auto_multiline_extra_patterns = []
## Removes ANSI escape codes from text strings.
remove_ansi_escape_codes = false
## If the data sent failure, will retry forevery.
blocking_mode = true
## If file is inactive, it is ignored.
## time units are "ms", "s", "m", "h"
ignore_dead_log = "1h"
## Read file from beginning.
from_beginning = false
[inputs.logging.tags]
# some_tag = "some_value"
# more_tag = "some_other_value"
设置日志pipeline 选择「日志」 - 「Pipeline」，这里可以设置样本，直接调试，非常人性化
做完日志切割以后，我们看一下切割后的日志
详细日志记录可以通过显示列添加字段，也可以点击某条日志查看字段
当日志收集上来以后，可以做一些大盘展示，还有监控告警，可玩性很高，可以自己尝试一下。
