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This article mainly explains "the related configuration and use of skywalking6.2". The content of the explanation in the article is simple and clear, and it is easy to learn and understand. Please follow the editor's train of thought to study and learn "the relevant configuration and use of skywalking6.2".

1. Log and project name configuration: logs can be configured inside or outside the probe agent.config

The configuration method on the outside is:

-javaagent:/data/path/skywalking-agent.jar=logging.file_name=agent_passport.log,logging.dir=/data/applogs/skyagent/-Dskywalking.agent.service_name=passport

Since the project is run by docker so as not to overwrite the configuration, you can modify the override directly by catalina.sh script.

Version 6.2 removes the login authentication on the web side.

3. Alarm configuration

Concept:

SLA: service availability (mainly calculated by the number of successful and failed requests)

CPM: number of calls per minute

Avg Response Time: average response time

Service_resp_time_rule: alarm rule name * * _ rule (rule name can be customized but must end with'_ rule')

Indicator-name: metric data name: definition see point here

Op: operator: >, <, = [of course you can extend and develop other operators yourself]

Threshold: target value: the target data of metric data, such as 1000 in sample, is the service response time, and the operator is the service response greater than 1000ms.

Period: alarm check cycle: how often do you check whether the current metric data conforms to the alarm rules?

Counts: the number of times the alarm threshold has been reached

Silence-period: ignore the period of the same alarm information

Message: alarm information

Webhooks: address of service alarm notification service

Alarm parameters: click here

Alarm explanation: click here

The default alarm contains

1. The response time of the service serviceapi has exceeded 1000 milliseconds in 3 minutes of the past 10 minutes.

2. The success rate of service serviceapi is less than 80% in the past 10 minutes.

3. 90% response time of the service serviceapi exceeded 1000 milliseconds in 3 minutes of the past 10 minutes.

4. The response time of the service instance serviceapi has exceeded 1000 milliseconds in the past 10 minutes.

5. The response time of the endpoint serviceapi exceeds 1000 milliseconds in 2 minutes of the last 10 minutes.

The error alarm in the project did not find a way to configure the alarm.

Aggregate functions: features provided

LongAvg. The average of all inputs for each scope entity. The input field must be of type long.

Instance_jvm_memory_max = from (ServiceInstanceJVMMemory.max). LongAvg ()

In this case, the input is a request per service instance jvmmemmory scope, and the average is based on the maximum value of the field.

DoubleAvg. The average of all inputs for each scope entity. The input field must be double.

Instance_jvm_cpu = from (ServiceInstanceJVMCPU.usePercent). DoubleAvg ()

In this case, the input is a request for each ServiceInstance JVM CPU scope, and the avg is based on the field usePercent.

Percentile. The number or ratio is expressed as a score of 100, for conditional matching input.

Endpoint_percent = from (Endpoint.*) .cake (status = = true)

In this case, all inputs are requests from each endpoint, provided that endpoint.status = = true.

Sum. The sum call for each scope entity.

Service_Calls_Sum = from (Service.*). Sum ()

In this case, each service invocation.

P99, p95, p90, p75, p50. Read P99 refer to wiki: click here

All_p99 = from (All.latency) .p99 (10)

In this case, the p99 value of all incoming requests. Thermodynamic.

All_heatmap = from (All.latency) .roomdynamic (100,20)

In this case, the thermodynamic heat map of all incoming requests.

Thank you for your reading, the above is the content of "the relevant configuration and use of skywalking6.2", after the study of this article, I believe you have a deeper understanding of the relevant configuration and use of skywalking6.2, and the specific use needs to be verified in practice. Here is, the editor will push for you more related knowledge points of the article, welcome to follow!

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