Monitoring Elasticsearch monitor your Elasticsearch cluster's health, and diagnose and solve it performance and reliability issues

Key Features* Understand common performance and reliability pitfalls in ElasticSearch * Use popular monitoring tools such as ElasticSearch-head, BigDesk, Marvel, Kibana, and more * This is a step-by-step guide with lots of case studies on solving real-world ElasticSearch cluster issues Book DescriptionElasticSearch is a distributed search server similar to Apache Solr with a focus on large datasets, a schema-less setup, and high availability. This schema-free architecture allows ElasticSearch to index and search unstructured content, making it perfectly suited for both small projects and large big data warehouses with petabytes of unstructured data. This book is your toolkit to teach you how to keep your cluster in good health, and show you how to diagnose and treat unexpected issues along the way. You will start by getting introduced to ElasticSearch, and look at some common performance issues that pop up when using the system. You will then see how to install and configure ElasticSearch and the ElasticSearch monitoring plugins. Then, you will proceed to install and use the Marvel dashboard to monitor ElasticSearch. You will find out how to troubleshoot some of the common performance and reliability issues that come up when using ElasticSearch. Finally, you will analyze your cluster’s historical performance, and get to know how to get to the bottom of and recover from system failures. This book will guide you through several monitoring tools, and utilizes real-world cases and dilemmas faced when using ElasticSearch, showing you how to solve them simply, quickly, and cleanly. What you will learn* Explore your cluster with ElasticSearch-head and BigDesk * Access the underlying data of the ElasticSearch monitoring plugins using the ElasticSearch API * Analyze your cluster’s performance with Marvel * Troubleshoot some of the common performance and reliability issues that come up when using ElasticSearch * Analyze a cluster’s historical performance, and get to the bottom of and recover from system failures * Use and install various other tools and plugins such as Kibana and Kopf, which is helpful to monitor ElasticSearch About the Author**Dan Noble** is a software engineer with a passion for writing secure, clean, and articulate code. He enjoys working with a variety of programming languages and software frameworks, particularly Python, Elasticsearch, and frontend technologies. Dan currently works on geospatial web applications and data processing systems. Dan has been a user and advocate of Elasticsearch since 2011. He has given talks about Elasticsearch at various meetup groups, and is the author of the Python Elasticsearch client rawes. Dan was also a technical reviewer for the Elasticsearch Cookbook, Second Edition, by Alberto Paro. Table of Contents1. Introduction to Monitoring Elasticsearch 2. Installation and the Requirements for Elasticsearch 3. Elasticsearch-head and Bigdesk 4. Marvel Dashboard 5. System Monitoring 6. Troubleshooting Performance and Reliability Issues 7. Node Failure and Post-Mortem Analysis 8. Looking Forward Cover 1 Copyright 3 Credits 4 About the Author 5 About the Reviewers 6 www.PacktPub.com 7 Table of Contents 8 Preface 12 Chapter 1: Introduction to Monitoring Elasticsearch 20 An overview of Elasticsearch 20 Learning more about Elasticsearch 20 Data distribution, redundancy, and fault tolerance 21 Full-text search 24 Similar technologies 26 Apache Lucene 26 Solr 27 Ferret 27 Monitoring Elasticsearch 27 Resourcefulness and problem solving 28 Summary 29 Chapter 2: Installation and the Requirements for Elasticsearch 30 Installing Elasticsearch 31 DEB/RPM installation 32 The yum and apt-get repositories 32 Ubuntu/Debian and apt-get 32 CentOS/RHEL and yum 33 Verification 33 Configuration files 35 Configuring an Elasticsearch cluster 35 Cluster name 35 Memory configuration 36 Open file limit 36 The maximum file limit 36 Updating max file descriptors on Ubuntu Linux 37 Enabling pluggable authentication modules 38 Verifying the open file limit 38 Disabling swapping 39 Understanding your cluster 40 Installing Elasticsearch-head 40 Installing Bigdesk 42 Marvel 43 Cluster requirements 45 Summary 46 Chapter 3: Elasticsearch-head and Bigdesk 48 Cluster setup 48 Cluster configuration 49 Sample data 50 Elasticsearch-head 52 The Overview tab 52 Cluster states 53 Node and index actions 56 The Indices tab 58 The Browser tab 59 The Structured Query tab 59 The Any Request tab 60 The official website 61 Bigdesk 61 The Elasticsearch cat API 65 Background 65 Count 66 Health 66 Indices 67 Shards 68 Summary 68 Chapter 4: Marvel Dashboard 70 Setting up Marvel 70 Upgrading Marvel 75 Configuring Marvel 76 Marvel agent configuration settings 77 Marvel index configuration 78 Understanding the Marvel dashboard 80 Overview dashboard 82 Indices dashboard 85 Nodes dashboard 88 Monitoring node failures 90 Summary 91 Chapter 5: System Monitoring 92 Working with Kopf 92 Installing Kopf 93 The cluster page 95 The nodes page 96 The rest page 97 The more dropdown 98 Working with Logstash and Kibana 99 ELK 99 Installation 99 Installing Logstash 100 Loading NGINX logs 100 Installing Kibana 103 Working with Nagios 111 Installing Nagios 111 Command line tools for system and process management 116 top 116 tail 117 grep 117 ps 118 kill 119 free 120 du and df 120 Summary 121 Chapter 6: Troubleshooting Performance and Reliability Issues 124 System configuration 124 The fielddata cache 125 Analyzing queries 127 Slow log 127 Improving query performance 129 High-cardinality fields 129 Querying smaller indices 129 Cold indices 130 The shard query cache 134 Script queries 136 Testing meticulously 136 System and data architecting 137 Hot-Warm architecture 137 Master nodes 137 Hot nodes 137 Warm nodes 137 Reducing disk size 138 Compression 138 Storing the _source and analyzed fields 139 Optimizing data ingestion 140 Bulk indexing operations 141 Drive configuration 143 Case studies 143 Node configuration 143 Query optimization 145 Web application performance 148 Summary 149 Chapter 7: Node Failure and Post-Mortem Analysis 150 Diagnosing problems 150 OutOfMemoryError exceptions 151 Shard failures 152 Slow queries 156 Resolving OutOfMemoryError exceptions 157 Elasticsearch process crashes 160 Disk space 161 Resolving the issue 162 Reviewing some case studies 162 The ES process quits unexpectedly 163 Query requests slow and timing out 164 Summary 165 Chapter 8: Looking Forward 166 Elasticsearch 5 overview 166 Performance and reliability 167 Data loss 168 Upgrading to Elasticsearch 5.0 168 When to upgrade 171 Monitoring Elasticsearch 5 172 Summary 173 Index 176

Monitor your Elasticsearch cluster's health, and diagnose and solve its performance and reliability issues

About This Book

• Understand common performance and reliability pitfalls in ElasticSearch
• Use popular monitoring tools such as ElasticSearch-head, BigDesk, Marvel, Kibana, and more
• This is a step-by-step guide with lots of case studies on solving real-world ElasticSearch cluster issues

Who This Book Is For

This book is for developers and system administrators who use ElasticSearch in a wide range of capacities. Prior knowledge of ElasticSearch and related technologies would be helpful, but is not necessary.

What You Will Learn

• Explore your cluster with ElasticSearch-head and BigDesk
• Access the underlying data of the ElasticSearch monitoring plugins using the ElasticSearch API
• Analyze your cluster's performance with Marvel
• Troubleshoot some of the common performance and reliability issues that come up when using ElasticSearch
• Analyze a cluster's historical performance, and get to the bottom of and recover from system failures
• Use and install various other tools and plugins such as Kibana and Kopf, which is helpful to monitor ElasticSearch

In Detail

ElasticSearch is a distributed search server similar to Apache Solr with a focus on large datasets, a schema-less setup, and high availability. This schema-free architecture allows ElasticSearch to index and search unstructured content, making it perfectly suited for both small projects and large big data warehouses with petabytes of unstructured data.

This book is your toolkit to teach you how to keep your cluster in good health, and show you how to diagnose and treat unexpected issues along the way. You will start by getting introduced to ElasticSearch, and look at some common performance issues that pop up when using the system. You will then see how to install and configure ElasticSearch and the ElasticSearch monitoring plugins. Then, you will proceed to install and use the Marvel dashboard to monitor ElasticSearch. You will find out how to troubleshoot some of the common performance and reliability issues that come up when using ElasticSearch. Finally, you will analyze your cluster's historical performance, and get to know how to get to the bottom of and recover from system failures.

This book will guide you through several monitoring tools, and utilizes real-world cases and dilemmas faced when using ElasticSearch, showing you how to solve them simply, quickly, and cleanly.

Style and approach

This is a step-by-step guide to monitoring your ElasticSearch cluster and correcting performance issues. It is filled with lots of in-depth, real-world use-cases on solving different ElasticSearch cluster issues.

Monitor your Elasticsearch cluster's health, and diagnose and solve its performance and reliability issuesAbout This Book Understand common performance and reliability pitfalls in ElasticSearch Use popular monitoring tools such as ElasticSearch-head, BigDesk, Marvel, Kibana, and more This is a step-by-step guide with lots of case studies on solving real-world ElasticSearch cluster issuesWho This Book Is For This book is for developers and system administrators who use ElasticSearch in a wide range of capacities. Prior knowledge of ElasticSearch and related technologies would be helpful, but is not necessary. What You Will Learn Explore your cluster with ElasticSearch-head and BigDesk Access the underlying data of the ElasticSearch monitoring plugins using the ElasticSearch API Analyze your cluster's performance with Marvel Troubleshoot some of the common performance and reliability issues that come up when using ElasticSearch Analyze a cluster's historical performance, and get to the bottom of and recover from system failures Use and install various other tools and plugins such as Kibana and Kopf, which is helpful to monitor ElasticSearchIn Detail ElasticSearch is a distributed search server similar to Apache Solr with a focus on large datasets, a schema-less setup, and high availability. This schema-free architecture allows ElasticSearch to index and search unstructured content, making it perfectly suited for both small projects and large big data warehouses with petabytes of unstructured data. This book is your toolkit to teach you how to keep your cluster in good health, and show you how to diagnose and treat unexpected issues along the way. You will start by getting introduced to ElasticSearch, and look at some common performance issues that pop up when using the system. You will then see how to install and configure ElasticSearch and the ElasticSearch monitoring plugins. Then, you will proceed to install and use the Marvel dashboard to monitor ElasticSearch. You will find out how to troubleshoot some of the common performance and reliability issues that come up when using ElasticSearch. Finally, you will analyze your cluster's historical performance, and get to know how to get to the bottom of and recover from system failures. This book will guide you through several monitoring tools, and utilizes real-world cases and dilemmas faced when using ElasticSearch, showing you how to solve them simply, quickly, and cleanly. Style and approach This is a step-by-step guide to monitoring your ElasticSearch cluster and correcting performance issues. It is filled with lots of in-depth, real-world use-cases on solving different ElasticSearch cluster issues Monitor your Elasticsearch cluster's health, and diagnose and solve its performance and reliability issues About This Book Understand common performance and reliability pitfalls in ElasticSearch Use popular monitoring tools such as ElasticSearch-head, BigDesk, Marvel, Kibana, and more This is a step-by-step guide with lots of case studies on solving real-world ElasticSearch cluster issues Who This Book Is For This book is for developers and system administrators who use ElasticSearch in a wide range of capacities. Prior knowledge of ElasticSearch and related technologies would be helpful, but is not necessary. What You Will Learn Explore your cluster with ElasticSearch-head and BigDesk Access the underlying data of the ElasticSearch monitoring plugins using the ElasticSearch API Analyze your cluster's performance with Marvel Troubleshoot some of the common performance and reliability issues that come up when using ElasticSearch Analyze a cluster's historical performance, and get to the bottom of and recover from system failures Use and install various other tools and plugins such as Kibana and Kopf, which is helpful to monitor ElasticSearch In Detail ElasticSearch is a distributed search server similar to Apache Solr with a focus on large datasets, a schema-less setup, and high availability. This schema-free architecture allows ElasticSearch to index and search unstructured content, making it perfectly suited for both small projects and large big data warehouses with petabytes of unstructured data. This book is your toolkit to teach you how to keep your cluster in good health, and show you how to diagnose and treat unexpected issues along the way. You will start by getting introduced to ElasticSearch, and look at some common performance issues that pop up when using the system. You will then see how to install and configure ElasticSearch and the ElasticSearch monitoring plugins. Then, you will proceed to install and use the Marvel dashboard to monitor ElasticSearch. You will find out how to troubleshoot some of the common performance and reliability issues that come up when using ElasticSearch. Finally, you will analyze your cluster's historical performance, and get to know how to get to the bottom of and recover from system failures. This book will guide you through several monitoring tools, and utilizes real-world cases and dilemmas faced when using ElasticSearch, showing you how to solve them simply, quickly, and cleanly. Style and approach.. About This BookUnderstand common performance and reliability pitfalls in ElasticSearchUse popular monitoring tools such as ElasticSearch-head, BigDesk, Marvel, Kibana, and moreThis is a step-by-step guide with lots of case studies on solving real-world ElasticSearch cluster issuesWho This Book Is ForThis book is for developers and system administrators who use Elasticsearch in a wide range of capacities. Prior knowledge of Elasticsearch and related technologies would be helpful, but is not necessary.What You Will LearnExplore your cluster with Elasticsearch-head and BigdeskAccess the underlying data of the Elasticsearch monitoring plugins using the Elasticsearch APIAnalyze your cluster's performance with MarvelTroubleshoot some of the common performance and reliability issues that come up when using ElasticsearchAnalyze a cluster's historical performance, and get to the bottom of and recover from system failuresUse and install tools such as Kibana and Kopf, which come in handy when monitoring ElasticsearchIn DetailElasticsearch is a distributed search server similar to Apache Solr with a focus on large datasets, a schema-less setup, and high availability. This book is your toolkit to teach you how to keep your cluster in good health, and show you how to diagnose and treat unexpected issues along the way. You will start by getting introduced to Elasticsearch, and look at some common performance issues that crop up when using the system. You will then see how to install and configure Elasticsearch and the Elasticsearch monitoring plugins. Then, you will proceed to install and use the Marvel dashboard to monitor Elasticsearch. You will find out how to troubleshoot some of the common performance and reliability issues that come up when using Elasticsearch. Finally, you will analyze your cluster's historical performance, and get to know how to get to the bottom of and recover from system failures. This book will guide you through several monitoring tools, and utilizes real-world cases and dilemmas faced when using Elasticsearch, showing you how to solve them simply, quickly, and cleanly.