kibana database

1. Elasticsearch Common terms Document documents DataThe index index (a concept that can be understood as a database in MySQL, where all document is stored in a specific index.) ）Type of data in the index (can be easily understood as a table in MySQL)Field fields, document properties (such as user's document, age, name attribute)Query syntax for querying DSL 2. Elasticsearch CRUD Operations Create documentRead reading a documentUpdate Updates Docum

Install the latest version, install the 6.* versionFirst prompt an important thing, Kibana new version does not need to install sense, the official is the old version of Kibana only need, we now use DevtoolHttp://localhost:5601/app/kibana#/dev_tools/console?_g= ()Because the official documents a bit long, caused me to install the system when the time to go a lot

PartyCase BackJingTypically, the logs are stored on different devices that are scattered. If you manage hundreds of dozens of of servers, you are also using the traditional method of logging in to each machine in turn. This is not feeling very cumbersome and inefficient. Open Source Real-time log analyticsELKthe platform can perfectly solve the problem of log collection and log retrieval and analysis,elk means Elasticsearch .,Logstashand theKiabanaThree of open source tools. Because elk can be d

Log into the Elasticsearch cluster via flume see here: Flume log import ElasticsearchKibana IntroductionKibana HomeKibana is a powerful elasticsearch data display Client,logstash has built-in Kibana. You can also deploy Kibana alone, the latest version of Kibana3 is pure html+jsclient. can be very convenient to deploy to Apache, Nginx and other httpserver.Address of Kibana3: https://github.com/elasticsearch

After installation Kibana directly can access, this is not conducive to security, next we use Apache Password Authentication for security configurationThe Apache configuration file is as follows:authuserfile/data/kibana/.htpasswdThis is the file we want to store the password in.Next generate the password#htpasswd-C/data/kibana/.htpasswd user#new password: #Re-typ

In the Kibana display page, we click on the left column of table and find that the data in Elasticsearch is the correct data in the display, such as: Agent Www.baidu.com/test, the interface will be displayed correctly as Www.baidu.com /test, but if we show this field in term, will be divided into www.baidu.com and test two groups, by looking at Curl did not find any problems, and finally found the reason for elasticsearch to separate the results of

"]}#对ua进行解析useragent {Source = "UA"# type = "Linux-syslog"Add_tag = ["useragent"]}}output{#入eselasticsearch{hosts = ["10.130.2.53:9200", "10.130.2.46:9200", "10.130.2.54:9200"]flush_size=>50000Workers = 5Index=> "Logstash-tracklog"}} Need to note:1. The logsdate is replaced because: for example, the 2016-01-01 form of the field, into the ES, will be considered a time format, auto-completion is: 2016-01-01 08:00:00, resulting in kibana need to

This is my entire process of log analysis for haproxy in the unit.We have been in the maintenance ES cluster configuration, and did not put a set of processes including the collection end of the code, all their own once, and the online collection of logs when we generally use the logstash, but the industry many people say logstash whether it is performance and stability is not very good, The advantage of Logstash is the simple configuration, this time I chose the RsyslogToday this haproxy log, I

ObjectiveJMeter is an open source tool for performance testing, stress testing, and is being tested by a large number of testers to test product performance, load, and more. JMeter In addition to the powerful presets of various plugins, various visual charting tools, there are some inherent flaws, such as: We often can only analyze the performance of the same deployment in the report, it is inconvenient to make a vertical comparison, for example, each build will run a one-time test, but

First, open the Kibana discover interface, and we'll find that the default entry in the search box at the top of the page is "*", which also means that the default query is all information.Now, suppose our import kibana information is divided into two categories: trace and statistic, and the two types of information are differentiated in info-type.Then, when we enter Info-type:trace in the search box above

-http_ssl_module -- With-OpenSSL =/opt/openssl-1.0.1i -- With-PCRE =/opt/pcre-8.33 -- With-zlib =/opt/zlib-1.2.8 Nginx command Start:/usr/local/nginx/sbin/nginx Restart:/usr/local/nginx/sbin/nginx-s reload Stop:/usr/local/nginx/sbin/nginx-s stop View the main process: netstat-ntlp Check whether the startup is successful: netstat-ano | grep 80 Required to install Ruby to run kibana Sudo apt-Get update Wget http://cache.ruby-lang.org/pub/ruby/2.1/ruby

Elk Architecture: Elasticsearch+kibana+filebeatVersion information:Elasticsearch 5.2.1Kibana 5.2.1Filebeat 6.0.0 (preview)Today in the Elk Test, the Kibana above the discover regardless of the index, found that will be error:[Request] Data too large, data for [And in the Elasticsearch log you can see:Org.elasticsearch.common.breaker.CircuitBreakingException: [Request] data too large, data for [According to

Elasticsearch+logstash+kibana ConfigurationThere are a lot of articles about the installation of Elasticsearch+logstash+kibana, which is not repeated here, only some of the more detailed content. Considerations for installing in AWS EC2 9200,9300,5601 Port to remember to open Elasticsearch address do not write external IP, otherwise it will be a waste of data, write internal IP"ip-10-1

In the use of the Kibana plug-in Discover feature, there are two shortcuts for "filter in" (finding data that matches this value) and "filter out" (excluding data that matches this value), and when working with date data, you are prompted with the following error: Discover:failed to parse Date field [975542400000] with format [Year_month_day] failed to parse date field [975542400 with format [Year_month_day] As a hint, it should be an error that th

Raspberry Pi on the Cloud (1): Environment preparationRaspberry Pi on the Cloud (2): Uploading sensor data to AWS IoT and leveraging Kibana for presentation1. Sensor installation and configuration 1.1 DHT22 installationThe DHT22 is a temperature and humidity sensor with 3 pins, the first pin on the left (#1) is the 3-5v power supply, the second pin (#2) is connected to the data input pin, and the rightmost pin (#4) is grounded.The Raspberry Pi 3B has

little too hard.Open source real-time log analysis Elk platform can perfectly solve our problems above, elk by Elasticsearch, Logstash and Kiabana three open source tools. Official website: https://www.elastic.coElasticsearch is an open source distributed search engine, it features: distributed, 0 configuration, automatic discovery, Index auto-shard, index copy mechanism, RESTful style interface, multi-data source, automatic search load, etc.Logstash is a fully open source tool that collects, a

This article is written to record the Logstash+elasticsearch+kibana+redis building process. All programs are running under the Windows platform.1. Download1.1 Logstash, Elasticsearch, Kinana download from official site: https://www.elastic.co/1.2 Redis official without the Windows platform. You can download Windows platform version from GitHub: https://github.com/MSOpenTech/redis/releases2. Start each part of the component2.1 Redis Boot: Still relativ

This article is a reference to the practice of logstash official documentation. The environment and required components are as follows: RedHat 5.7 64bit/centos 5.x JDK 1.6.0 _ 45 Logstash 1.3.2 (with kibana) Elasticsearch 0.90.10 Redis 2.8.4 The process of building a centralized log analysis platform is as follows: Elasticsearch 1. Download elasticsearch. wget https://download.elasticsearch.org/elasticsearch/elasticsearch/elasticsearch-0.90.10.

Elasticsearch + Logstash + Kibana ConfigurationElasticsearch + Logstash + Kibana Configuration There are many articles about the installation of Elasticsearch + Logstash + Kibana. I will not repeat them here, but I will only record some details here. Precautions for installing AWS EC2Remember to open the elasticsearch address on ports 9200,9300 and 5601. Do not w

Kubernetes Release:stac Kdriver Logging for use with Google Cloud Platform, and Elasticsearch. You can find more information and instructions in the dedicated documents. Both use FLUENTD with custom configuration as a agent on the node.Okay, here's our pits guide.1. Preparatory work The Kubernetes code in GitHub is planted down to master local. git clone https://github.com/kubernetes/kubernetes Configure ServiceAccount, this is because after the download of FLUENTD images