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For details about how to import logs to elasticsearch clusters Through flume, see flume log import to elasticsearch clusters.Kibana Introduction
Kibana Homepage
Kibana is a powerful elasticsearch data display client. logstash has built-in
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
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
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
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
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
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
Recently helped Lei elder brother transplant a set of open source log management software, replace Splunk. Splunk is a powerful log management tool that not only adds logs in a variety of ways, produces graphical reports, but, most of all, its search capabilities-known as "Google for it." Splunk has a free and premium version, the main difference is the size of the index per day (index is the basis of the search function), the free version of the maximum daily 500M. When using the free version,
http://nkcoder.github.io/blog/20141106/elkr-log-platform-deploy-ha/
1. Architecture for highly available scenarios
In the previous article using Elasticsearch+logstash+kibana+redis to build a log management service describes the overall framework of log services and the deployment of various components, this article mainly discusses the Log service framework of high-availability scenarios, mainly from the
a name so that you can monitor multiple indexes (typically data by talent index)Click Create can be. 2. Click the Menu "Discover", select the setting map you just created, you can find the following:@ then click Save in the upper right corner to enter a name. @ This is the data source to be used in the following illustration, but you can also search for your data here, and note that it is best to double quotation marks on both sides of the string. 3. Click "Visualize" to make various icons.You
Benefits of the unified collection of real-time logs:1. Quickly locate the problem machine in the cluster2, no need to download the entire log file (often relatively large, download time is much)3, the log can be countedA, to find the most frequently occurring anomalies, for tuning processingB, Statistics crawler IPC, Statistical user behavior, do cluster analysis, etc.Based on the above requirements, I adopted the ELK (Elasticsearch + Logstash +
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 docume
Kibana problem occurred, 5601 port is not connected, but the process exists, view log found the following error
"Elasticsearch is still initializing the Kibana index ... Trying again in 2.5 second. "
PS: View log can be used kibana-l Xxx.log
{' name ': ' Kibana ', ' hostn
The front-end time wrote an essay log4net. NOSQL +elasticsearch implements logging , because of project reasons need to integrate log root Java platform colleague integration using Logstash+kibana+elasticsearch+redis structure to achieve log statistics analysis, Therefore, a component that outputs Log4net logs to Redis is required. Did not find the ready-made, do
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