How to check Logstash's pulse
Have you ever wondered if Logstash was sending data to your outputs? There's a brand new way to check if Logstash has a "pulse." Introducing the heartbeat input plugin! It’s bundled with Logstash 1.5 so you can start using it immediately!
Why?
Logstash currently has a single pipeline. All events generated by inputs travel through the filter block, and then out of Logstash through the output block.
Even if you have multiple outputs and are separating events using conditionals all events pass through this single pipeline. If any one of your outputs backs up, the entire pipeline stops flowing. The heartbeat plugin takes advantage of this to help you know when the flow of events slows, or stops altogether.
How?
The heartbeat plugin sends a message at a definable interval. Here are the options available for the message configuration parameter:
- Any string value: The message field will contain the specified string value. If unset, the message field will contain the string value ok
- epoch: Rather than a message field, this will result in a clock field which will contain the current epoch timestamp (UTC). If you are unfamiliar with this, it means the number of seconds elapsed since Jan 1, 1970.
- sequence: Rather than a message field, this will result in a clock field which will contain a number. At start time, the sequence starts at zero and will increment each time your specified interval time has elapsed. Note that this means that if you restart Logstash, the counter resets to zero again.
Examples
Be sure to assign a type to your heartbeat events. This will make it possible to conditionally act on these events later on.
"ok" Message
Perhaps you only want to know that Logstash is still sending messages. Your monitoring system can interpret an "ok" received within a time window as an indicator that everything is working. Your monitoring system would be responsible for tracking the time between "ok" messages.
I can send the default "ok" message every 10 seconds like this:
input {
heartbeat {
interval => 10
type => "heartbeat"
}
# ... other input blocks go here
}
The events would look like this:
{"message":"ok","host":"example.com","@version":"1","@timestamp":"2015-03-18T17:05:24.696Z","type":"heartbeat"}
{"message":"ok","host":"example.com","@version":"1","@timestamp":"2015-03-18T17:05:34.696Z","type":"heartbeat"}
{"message":"ok","host":"example.com","@version":"1","@timestamp":"2015-03Read More
Epoch timestamp
Perhaps your monitoring system uses unix timestamps to track event timing (like Zabbix, for example). If so, you can use the epoch timestamp in the clock field to calculate the difference between "now" and when Logstash generated the heartbeat event. You can calculate lag in this way. This may be especially useful if you inject the heartbeat before events go into a broker, or buffering system, like Redis, RabbitMQ, or Kafka. If the buffer begins to fill up, the time difference will become immediately apparent. You could use this to track the elapsed time--from event creation, to indexing--for your entire Logstash pipeline.
This example will send the epoch timestamp in the clock field:
input {
heartbeat {
message => "epoch"
interval => 10
type => "heartbeat"
}
# ... other input blocks go here
}
The events would look like this:
{"clock":1426698365,"host":"example.com","@version":"1","@timestamp":"2015-03-18T17:06:05.360Z","type":"heartbeat"}
{"clock":1426698375,"host":"example.com","@version":"1","@timestamp":"2015-03-18T17:06:15.364Z","type":"heartbeat"}
{"clock":1426698385,"host":"example.com","@version":"1","@timestamp":"2015Read More
Sequence of numbers
This example makes it easy to immediately check if new events are occurring because the clock will continuously increase.
input {
heartbeat {
message => "sequence"
interval => 10
type => "heartbeat"
}
# ... other input blocks go here
}
The events would look like this:
{"clock":1,"host":"example.com","@version":"1","@timestamp":"2015-03-18T17:08:13.024Z","type":"heartbeat"}
{"clock":2,"host":"example.com","@version":"1","@timestamp":"2015-03-18T17:08:23.027Z","type":"heartbeat"}
{"clock":3,"host":"example.com","@version":"1","@timestamp":"2015-03-18T17Read More
Output
Now let's add a conditional to send this to our monitoring system, and not to our other outputs:
output {
if [type] == "heartbeat" {
# Define the output block for your monitoring system here
} else {
# ... other output blocks go here
}
}
Of course, if you do want your heartbeat messages to be indexed alongside your log data, you are free to do so.
Conclusion
The new heartbeat plugin provides a simple, but effective way to monitor the availability of your Logstash instances right now. We have big plans for the future, though. Take a look at our road map!
In the future we plan to have a full API, complete with visibility into the pipeline, plugin performance, queue status, event throughput and so much more. We are super excited to bring these improvements to you!
Happy Logstashing!
input {
heartbeat {
tags => ["heartbeat"]
type => "heartbeat"
message => "epoch"
interval =>
}
}
output {
if "heartbeat" in [tags] {
file {
path => "/var/log/cloudchef/logstash/logstash-hearbeat.log"
}
}
}
How to check Logstash's pulse的更多相关文章
- DIY PIXHAWK APM等飞控用的PPM转接板
需要的硬件 一块arduino pro mini(推荐这个,比较小,当然如果你没有USB转转口的烧写工具买个ardunio nano板也是不错的,直接用USB线连接电脑就可以,用nano板要注意.它的 ...
- logstash服务启动脚本
logstash服务启动脚本 最近在弄ELK,发现logstash没有sysv类型的服务启动脚本,于是按照网上一个老外提供的模板自己进行修改 #添加用户 useradd logstash -M -s ...
- 日志分析 第五章 安装logstash
logstash是java应用,依赖JDK,首先需要安装JDK,在安装jdk过程中,logstash-2.3.4使用JDK-1.7版本有bug,使用JDK-1.8版本正常,因此我们安装JDK-1.8版 ...
- ELK——安装 logstash 2.2.0、elasticsearch 2.2.0 和 Kibana 3.0
本文内容 Elasticsearch logstash Kibana 参考资料 本文介绍安装 logstash 2.2.0 和 elasticsearch 2.2.0,操作系统环境版本是 CentOS ...
- logstash
logstash作为数据搜集器,主要分为三个部分:input->filter->output 作为pipeline的形式进行处理,支持复杂的操作,如发邮件等 input配置数据的输入和简 ...
- Centos7下使用ELK(Elasticsearch + Logstash + Kibana)搭建日志集中分析平台
日志监控和分析在保障业务稳定运行时,起到了很重要的作用,不过一般情况下日志都分散在各个生产服务器,且开发人员无法登陆生产服务器,这时候就需要一个集中式的日志收集装置,对日志中的关键字进行监控,触发异常 ...
- 使用Nginx和Logstash以及kafka来实现网站日志采集的详细步骤和过程
使用Nginx和Logstash以及kafka来实现网站日志采集的详细步骤和过程 先列出来总体启动流程: (1)启动zookeeper集群(hadoop01.hadoop02和hadoop03这3台机 ...
- Manage Spring Boot Logs with Elasticsearch, Logstash and Kibana
下载地址:https://www.elastic.co/downloads When time comes to deploy a new project, one often overlooked ...
- logstash 安装zabbix插件
<pre name="code" class="html">[root@xxyy yum.repos.d]# yum install ruby Lo ...
随机推荐
- java基础-day30
第07天 MySQL数据库 今日内容介绍 u 多表关系实战练习 u 多表查询 u SQL语句的练习 第1章 多表关系实战练习 1.1 多表关系--实战1--省和市 1.1.1 需求分析 在数据库 ...
- Q他中的乱码再理解
Qt版本有用4的版本的也有用5的版本,并且还有windows与linux跨平台的需求. 经常出现个问题是windows的解决了,源代码放到linux上编译不通过或者中文会乱码,本文主要是得出一个解决方 ...
- vc6中向vs2010迁移的几个问题
vc6版本支持的库编译:CJ60lib 1. 用vs2010打开CJ60库的源码的dsw,强制打开 (1)设置项目属性的语言 因为,如果代码字符的编码集不一样,则会出现函数冲定义,参数冲突等问题,这可 ...
- hdu 5051 找规律?+大trick
http://acm.hdu.edu.cn/showproblem.php?pid=5051 打表找规律 据说是http://zh.wikipedia.org/wiki/%E6%9C%AC%E7%A6 ...
- cpu信息查看
# 总核数 = 物理CPU个数 X 每颗物理CPU的核数 # 总逻辑CPU数 = 物理CPU个数 X 每颗物理CPU的核数 X 超线程数 # 查看物理CPU个数 cat /proc/cpuinfo| ...
- 机器学习实战-ch3-决策树
决策树是一种新算法: 优点:计算复杂度不高,输出结果易于理解,对中间值的缺失不敏感,可以处理不相关特征数据.缺点:可能会产生过度匹配问题. 决策树算法可用于数据类型:数值型和标称型. 决策树的核心在于 ...
- Windows编译Opencv
下载安装CMake 下载Opencv源码 打开CMake,设置源码路径和生成路径,点击Configure选择要生成的版本.(这里要多次Configure,直到所有红色消失!) 勾选BUILD_open ...
- 四种List实现类的对比总结
此文已由作者赵计刚授权网易云社区发布. 欢迎访问网易云社区,了解更多网易技术产品运营经验. 1.ArrayList 非线程安全 基于对象数组 get(int index)不需要遍历数组,速度快: it ...
- Python 爬虫(二十五) Cookie的处理--cookielib库的使用
Python中cookielib库(python3中为http.cookiejar)为存储和管理cookie提供客户端支持. 该模块主要功能是提供可存储cookie的对象.使用此模块捕获cookie并 ...
- Java几种单例模式的实现与利弊
饿汉式 提前new出来实例了,并不是在第一次调用get方法时才实例化,没有进行延迟加载 public class Singleton1 { private static Singleton1 inst ...