# kibana

Kibana is an open-source interface for querying, analyzing, visualizing, and managing data stored in Elasticsearch.

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## How we improved reporting and monitoring of test automation results

DevFeed: [How we improved reporting and monitoring of test automation results](<https://devfeed.tech/articles/how-we-improved-reporting-and-monitoring-of-test-automation-results-28033.md>)

Original publisher: [Read original article](<https://tech.trivago.com/post/2023-02-15-how-we-improved-reporting-and-monitoring-of-test-automation-results/>)

Author: Giuseppe Donati Web Test Automation Engineer Not a stereotypical Italian guy; Except

Published: 2023-02-15T00:00:00Z

Content type: article

Language: en

Sources: [Trivago](<https://devfeed.tech/sources/trivago.md>)

Topics: [Testing](<https://devfeed.tech/topics/testing.md>), [Test automation](<https://devfeed.tech/topics/test-automation.md>), [GitHub Actions](<https://devfeed.tech/topics/github-actions.md>), [Selenium](<https://devfeed.tech/topics/selenium.md>), [CI/CD](<https://devfeed.tech/topics/cicd.md>), [Cloud](<https://devfeed.tech/topics/cloud.md>), [Kafka](<https://devfeed.tech/topics/kafka.md>), [elasticsearch](<https://devfeed.tech/topics/elasticsearch.md>), [kibana](<https://devfeed.tech/topics/kibana.md>), [logstash](<https://devfeed.tech/topics/logstash.md>), [Grafana](<https://devfeed.tech/topics/grafana.md>), [Cucumber](<https://devfeed.tech/topics/cucumber.md>)

Tags: [article](<https://devfeed.tech/tags/article.md>), [elasticsearch](<https://devfeed.tech/tags/elasticsearch.md>), [frontend](<https://devfeed.tech/tags/frontend.md>), [gcp](<https://devfeed.tech/tags/gcp.md>), [github-actions](<https://devfeed.tech/tags/github-actions.md>), [grafana](<https://devfeed.tech/tags/grafana.md>), [kafka](<https://devfeed.tech/tags/kafka.md>), [kibana](<https://devfeed.tech/tags/kibana.md>), [logstash](<https://devfeed.tech/tags/logstash.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [quality-assurance](<https://devfeed.tech/tags/quality-assurance.md>), [selenium](<https://devfeed.tech/tags/selenium.md>), [test-automation](<https://devfeed.tech/tags/test-automation.md>)

### AI overview

The article describes trivago's updated system for executing, reporting, and monitoring Selenium-based end-to-end tests. It covers GitHub Actions workflows, custom runners on Google Cloud, cloud report storage, Kafka and Logstash processing, Elasticsearch and Kibana visualization, and Grafana and Slack alerting.

### Source excerpt

Over the last few years, we completely refactored what was described in our previous article about how we use the ELK sta...

## How to manage nested objects in Elasticsearch documents

DevFeed: [How to manage nested objects in Elasticsearch documents](<https://devfeed.tech/articles/how-to-manage-nested-objects-in-elasticsearch-documents-37446.md>)

Original publisher: [Read original article](<https://iridakos.com/programming/2019/05/02/add-update-delete-elasticsearch-nested-objects>)

Author: Lazarus Lazaridis

Published: 2019-05-02T12:30:00Z

Content type: tutorial

Language: en

Sources: [Lazarus Lazaridis](<https://devfeed.tech/sources/lazarus-lazaridis.md>)

Topics: [elasticsearch](<https://devfeed.tech/topics/elasticsearch.md>), [kibana](<https://devfeed.tech/topics/kibana.md>), [API](<https://devfeed.tech/topics/api.md>)

Tags: [elasticsearch](<https://devfeed.tech/tags/elasticsearch.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [kibana](<https://devfeed.tech/tags/kibana.md>), [nested-objects](<https://devfeed.tech/tags/nested-objects.md>), [opensource](<https://devfeed.tech/tags/opensource.md>), [programming](<https://devfeed.tech/tags/programming.md>), [script](<https://devfeed.tech/tags/script.md>), [scripts](<https://devfeed.tech/tags/scripts.md>), [update](<https://devfeed.tech/tags/update.md>)

### AI overview

This tutorial explains how to manage nested objects in Elasticsearch documents using Kibana. It covers defining a nested mapping, indexing a document containing cats, and adding, removing, and updating nested objects through the Update API and scripts.

### Source excerpt

In this post we are going to manage nested objects of a document indexed with Elasticsearch. The nested type is a specialised version of the object datatype that allows arrays of objects to be indexed in a way that they can be queried independently of each other. - Nested datatype - Official Elasticsearch reference Prerequisites To follow this post you need: an up and running Elasticsearch instance I use 6.7 here an up and running Kibana instance to interact with Elasticsearch Preparation The document of our index will represent a human and its nested objects will be cats (no surprises). Create the index Open your Kibana dev console and type the following to create the index. # Create the index PUT iridakos_nested_objects { "mappings": { "human": { "properties": { "name": { "type": "text" }, "cats": { "type": "nested", "properties": { "colors": { "type": "integer" }, "name": { "type": "text" }, "breed": { "type": "text" } } } } } } } Human has: a name property of type text a cats property of type nested Each cat has: a colors property of type integer a name property of type text a breed property of type text Add a human In the Kibana console, execute the following to add a human with three cats. # Index a human POST iridakos_nested_objects/human/1 { "name": "iridakos", "cats": [ { "colors": 1, "name": "Irida", "breed": "European Shorthair" }, { "colors": 2, "name": "Phoebe", "breed": "European" }, { "colors": 3, "name": "Nino", "breed": "Aegean" } ] } Confirm the insertion with: GET iridakos_nested_objects/human/1 You should see something like this: { "_index": "iridakos_nested_objects", "_type": "human", "_id": "1", "_version": 1, "found": true, "_source": { "name": "iridakos", "cats": [ { "colors": 1, "name": "Irida", "breed": "European Shorthair" }, { "colors": 2, "name": "Phoebe", "breed": "European" }, { "colors": 3, "name": "Nino", "breed": "Aegean" } ] } } Done, moving on. Managing nested objects Add a new nested object Suppose that iridakos got a new Persian

## ElasticSearch 最佳实践

DevFeed: [ElasticSearch 最佳实践](<https://devfeed.tech/articles/elasticsearch-40980.md>)

Original publisher: [Read original article](<https://blog.joway.io/posts/elasticsearch-bp/>)

Author: Joway

Published: 2017-05-28T00:00:00Z

Content type: tutorial

Language: zh

Sources: [Random Thoughts](<https://devfeed.tech/sources/random-thoughts.md>)

Topics: [elasticsearch](<https://devfeed.tech/topics/elasticsearch.md>), [Amazon Web Services](<https://devfeed.tech/topics/aws.md>), [kibana](<https://devfeed.tech/topics/kibana.md>), [Ansible](<https://devfeed.tech/topics/ansible.md>), [Kafka](<https://devfeed.tech/topics/kafka.md>)

Tags: [ansible](<https://devfeed.tech/tags/ansible.md>), [aws](<https://devfeed.tech/tags/aws.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [elasticsearch](<https://devfeed.tech/tags/elasticsearch.md>), [kafka](<https://devfeed.tech/tags/kafka.md>), [kibana](<https://devfeed.tech/tags/kibana.md>), [ssd](<https://devfeed.tech/tags/ssd.md>), [tech](<https://devfeed.tech/tags/tech.md>)

### AI overview

A practical guide to tuning and operating Elasticsearch clusters, covering hardware and JVM memory settings, CPU behavior during queries and force merges, swap, node and cluster configuration, shard recovery, rolling restarts, and logging pipelines. It also discusses using Kafka as a buffer and Ansible for consistent cluster management.

### Source excerpt

Elasticsearch 是一个需要不停调参数的庞然大物 , 从其自身的设置到JVM层面, 有着无数的参数需要根据业务的变化进行调整。最近采用3台 AWS r3.2xlarge , 32GB, 4核, 构建了一套日均日志量过亿的 EFK 套件。经过不停地查阅文档进行调整优化 , 目前日常CPU占用只在30% , 大部分 Kibana 内的查询都能在 5s ~ 15s 内完成。

## Go and structured logging with ElasticSearch

DevFeed: [Go and structured logging with ElasticSearch](<https://devfeed.tech/articles/go-and-structured-logging-with-elasticsearch-29659.md>)

Original publisher: [Read original article](<https://goteleport.com/blog/golang-elastic-search/>)

Author: sasha@goteleport.com (Sasha Klizhentas)

Published: 2016-01-01T00:00:00Z

Content type: tutorial

Language: en

Sources: [Teleport](<https://devfeed.tech/sources/teleport.md>)

Topics: [Logging](<https://devfeed.tech/topics/logging.md>), [log management](<https://devfeed.tech/topics/log-management.md>), [Go Language](<https://devfeed.tech/topics/go-language.md>), [elasticsearch](<https://devfeed.tech/topics/elasticsearch.md>), [kibana](<https://devfeed.tech/topics/kibana.md>), [Docker](<https://devfeed.tech/topics/docker.md>)

Tags: [beats](<https://devfeed.tech/tags/beats.md>), [docker](<https://devfeed.tech/tags/docker.md>), [elasticsearch](<https://devfeed.tech/tags/elasticsearch.md>), [format](<https://devfeed.tech/tags/format.md>), [framework](<https://devfeed.tech/tags/framework.md>), [go](<https://devfeed.tech/tags/go.md>), [kibana](<https://devfeed.tech/tags/kibana.md>), [logging](<https://devfeed.tech/tags/logging.md>), [udp](<https://devfeed.tech/tags/udp.md>)

### AI overview

This tutorial describes an experiment that uses Go, logrus, and Elastic Beats to emit structured logs over UDP and ship them to Elasticsearch. It also covers running Elasticsearch and Kibana with Docker and configuring the document schema and mappings.

### Source excerpt

We are playing with Elastic Beats, doing structured logging with Golang and Elastic Search

## Elasticsearch and Kibana for Selenium Automation

DevFeed: [Elasticsearch and Kibana for Selenium Automation](<https://devfeed.tech/articles/elasticsearch-and-kibana-for-selenium-automation-27935.md>)

Original publisher: [Read original article](<https://tech.trivago.com/post/2015-12-02-selenium_with_kibana/>)

Author: Teodor Rupi Follow

Published: 2015-12-02T00:00:00Z

Content type: tutorial

Language: en

Sources: [Trivago](<https://devfeed.tech/sources/trivago.md>)

Topics: [kibana](<https://devfeed.tech/topics/kibana.md>), [Selenium](<https://devfeed.tech/topics/selenium.md>), [Testing](<https://devfeed.tech/topics/testing.md>), [Automation](<https://devfeed.tech/topics/automation.md>), [Data visualization](<https://devfeed.tech/topics/data-visualization.md>), [elasticsearch](<https://devfeed.tech/topics/elasticsearch.md>), [Jenkins](<https://devfeed.tech/topics/jenkins.md>), [Kafka](<https://devfeed.tech/topics/kafka.md>), [logstash](<https://devfeed.tech/topics/logstash.md>), [ci](<https://devfeed.tech/topics/ci.md>), [Maven](<https://devfeed.tech/topics/maven.md>)

Tags: [apache](<https://devfeed.tech/tags/apache.md>), [automation](<https://devfeed.tech/tags/automation.md>), [backend](<https://devfeed.tech/tags/backend.md>), [chrome](<https://devfeed.tech/tags/chrome.md>), [ci](<https://devfeed.tech/tags/ci.md>), [data-visualization](<https://devfeed.tech/tags/data-visualization.md>), [devops](<https://devfeed.tech/tags/devops.md>), [elasticsearch](<https://devfeed.tech/tags/elasticsearch.md>), [firefox](<https://devfeed.tech/tags/firefox.md>), [java](<https://devfeed.tech/tags/java.md>), [jenkins](<https://devfeed.tech/tags/jenkins.md>), [kafka](<https://devfeed.tech/tags/kafka.md>), [kibana](<https://devfeed.tech/tags/kibana.md>), [linux](<https://devfeed.tech/tags/linux.md>), [logging](<https://devfeed.tech/tags/logging.md>), [logstash](<https://devfeed.tech/tags/logstash.md>), [mac](<https://devfeed.tech/tags/mac.md>), [mac-os](<https://devfeed.tech/tags/mac-os.md>), [maven](<https://devfeed.tech/tags/maven.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [selenium](<https://devfeed.tech/tags/selenium.md>), [testing](<https://devfeed.tech/tags/testing.md>)

### AI overview

This article describes trivago's Selenium-based automated testing infrastructure and its use of Kibana for real-time reporting, filtering, and analysis of test results. It outlines a setup that uses Jenkins, Kafka, Logstash, Elasticsearch, and Kibana, with testing across multiple platforms and browsers.

### Source excerpt

The advances and growth of our Selenium based automated testing infrastructure generated an unexpected number of test results to evaluate. We had to rethink our reporting systems. Combining the power of Selenium with Kibana's graphing and filtering features totally changed our way of working.

## Writing a Fuzzy Receipt Parser in Python

DevFeed: [Writing a Fuzzy Receipt Parser in Python](<https://devfeed.tech/articles/writing-a-fuzzy-receipt-parser-in-python-27933.md>)

Original publisher: [Read original article](<https://tech.trivago.com/post/2015-10-06-python_receipt_parser/>)

Author: Matthias Endler

Published: 2015-10-06T00:00:00Z

Content type: tutorial

Language: en

Sources: [Trivago](<https://devfeed.tech/sources/trivago.md>)

Topics: [Python](<https://devfeed.tech/topics/python.md>), [Parser](<https://devfeed.tech/topics/parser.md>), [Hackathon](<https://devfeed.tech/topics/hackathon.md>), [CSV](<https://devfeed.tech/topics/csv.md>), [elasticsearch](<https://devfeed.tech/topics/elasticsearch.md>), [kibana](<https://devfeed.tech/topics/kibana.md>)

Tags: [csv](<https://devfeed.tech/tags/csv.md>), [elasticsearch](<https://devfeed.tech/tags/elasticsearch.md>), [engineering-culture](<https://devfeed.tech/tags/engineering-culture.md>), [hackathon](<https://devfeed.tech/tags/hackathon.md>), [kibana](<https://devfeed.tech/tags/kibana.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [python](<https://devfeed.tech/tags/python.md>), [scanner](<https://devfeed.tech/tags/scanner.md>), [usb](<https://devfeed.tech/tags/usb.md>)

### AI overview

A Python hackathon project explores building a fuzzy receipt parser for household expense tracking. The tool is intended to scan receipts, identify the shop, date, and total with more than 90% precision, and export the results to CSV for later analysis.

### Source excerpt

Last weekend, the Python Hackathon Düsseldorf took place at trivago's office. Although we were only five people we had a lot of fun. I took the chance to brush up my Python skills a little bit. Also I wanted to scratch an itch that was bugging me for a long time: our housekeeping book.

## 10x: Logging at Clay.io

DevFeed: [10x: Logging at Clay.io](<https://devfeed.tech/articles/10x-logging-at-clay-io-35612.md>)

Original publisher: [Read original article](<https://zolmeister.com/2014/10/10x-logging-at-clay-io.html>)

Author: Zoli Kahan

Published: 2014-10-25T05:00:00Z

Content type: article

Language: en

Sources: [Zolmeister](<https://devfeed.tech/sources/zolmeister.md>)

Topics: [Logging](<https://devfeed.tech/topics/logging.md>), [log management](<https://devfeed.tech/topics/log-management.md>), [logstash](<https://devfeed.tech/topics/logstash.md>), [elasticsearch](<https://devfeed.tech/topics/elasticsearch.md>), [kibana](<https://devfeed.tech/topics/kibana.md>), [Amazon VPC](<https://devfeed.tech/topics/amazon-vpc.md>), [Server](<https://devfeed.tech/topics/server.md>), [Linux](<https://devfeed.tech/topics/linux.md>), [Docker](<https://devfeed.tech/topics/docker.md>)

Tags: [aggregate](<https://devfeed.tech/tags/aggregate.md>), [amazon](<https://devfeed.tech/tags/amazon.md>), [amazon-vpc](<https://devfeed.tech/tags/amazon-vpc.md>), [analyze](<https://devfeed.tech/tags/analyze.md>), [apply](<https://devfeed.tech/tags/apply.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [complex](<https://devfeed.tech/tags/complex.md>), [docker](<https://devfeed.tech/tags/docker.md>), [elasticsearch](<https://devfeed.tech/tags/elasticsearch.md>), [kibana](<https://devfeed.tech/tags/kibana.md>), [linux](<https://devfeed.tech/tags/linux.md>), [logging](<https://devfeed.tech/tags/logging.md>), [logs](<https://devfeed.tech/tags/logs.md>), [logstash](<https://devfeed.tech/tags/logstash.md>), [network](<https://devfeed.tech/tags/network.md>), [series](<https://devfeed.tech/tags/series.md>), [server](<https://devfeed.tech/tags/server.md>), [servers](<https://devfeed.tech/tags/servers.md>), [ssh](<https://devfeed.tech/tags/ssh.md>)

### AI overview

This article describes how Clay.io used Logstash to aggregate logs from more than 20 servers, with Elasticsearch and Kibana for analysis. It also discusses log rotation, securing Elasticsearch through Amazon VPC, and open-sourced Docker containers for deploying a distributed logging system.

### Source excerpt

10x: Logging at Clay.io Managing 20+ servers as a small team is no easy task, and when things go wrong (they always do) figuring out what happened quickly is essential. Of course we can't ssh into each machine, that would take ages, so instead we use Logstash to aggregate our logs. This is the second post in my series, and if you missed last episode: Architecture at Clay.io. Logstash overview Logstash deployments have two parts. The aggregate server (or cluster), and the client servers.