Practical ELK Stack

<div>Chapter 1: &nbsp;Introduction to ELK Stack</div><div>Chapter Goal: This chapter emphasizes the importance of log analysis in today's big data crazy world. It would go on to analyze the challenges with log analysis. It presents ELK stack as a thorough solution for log analysis. Different components of ELK Stack - Elasticsearch, Logstash and Kibana are introduced with a description of their functions and installation.</div><div>No of pages: 25 </div><div>Sub -Topics</div><div>1. Log Analysis in Today's World</div><div>2. The ELK Stack</div><div>3. ELK Data Pipeline</div><div>4. ELK Stack Installation"</div><div><br></div><div>Chapter 2: &nbsp;Shipping, Filtering and Parsing Events with Logstash</div><div>Chapter Goal: The goal of this chapter is to get started with using Logstash for log generation, collection and filtering. It starts with introducing configuration settings of Logstash. It then goes on to illustrate how Logstash facilitates shipping of logs, filtering and transforming any type of data to a common format. This can further help in arriving at actionable insights.</div><div>No of pages: 40</div><div>Sub - Topics </div><div>1. Configuring Logstash</div><div>2. Shipping Events</div><div>3. Filtering Events with Logstash</div><div>4. Outputting Events from Logstash"</div><div><br>&lt;<div>Chapter 3: Extending Logstash</div><div>Chapter Goal: The goal of this chapter is to illustrate how Logstash is internally organized using Plugins. Logstash has a diverse collection of input, filter, codec and output plugins. An overview of the common plugins would be provided. It would then show how to create and use your own custom plugin.</div><div>No of pages: 20</div><div>Sub - Topics: &nbsp;</div><div>1. Plugin Management</div><div>2. Structure of a Plugin</div><div>3. Adding custom plugins"</div><div><br></div><div>Chapter 4: Creating, Indexing and Deleting Data</div><div>Chapter Goal: This chapter introduces data management using Elasticsearch. It covers features of Elasticsearch. Data is organized as documents. This chapter would show how to add data, index it, update it, and delete it. It also goes on to show how to work with distributed document stores.</div><div>No of pages: 40</div><div>Sub - Topics:&nbsp;</div><div>1. Anatomy of a Document</div><div>2. Creating Document</div><div>3. Indexing a Document</div><div>4. Updating a Document</div><div>5. Deleting a Document</div><div>6. Distributed Document Store</div><div><br></div><div>Chapter 5: Searching Data</div><div>Chapter Goal: The goal of this chapter is to explore the elaborate mechanism for searching data available in Elasticsearch. It covers both the search query variations - Search Lite and Full Body Search. Then it illustrates Query DSL and Filters.</div><div>No of pages: 25</div><div>Sub - Topics:&nbsp;</div><div>1. Basic Search</div><div>2. Search with Multi-Index, Multi-Type</div><div>3. Pagination in Search<div>4. Search Lite</div><div>5. Query DSL</div><div>6. Queries and Filters</div><div>7. Advanced Search Concepts"</div><div><br></div><div>Chapter 6: Mapping and Analysis</div><div>Chapter Goal: The goal of this chapter is to examine how Elasticsearch maps data. It then goes on to show how to map data for relevant analysis.</div><div>No of pages: 25</div><div>Sub - Topics:&nbsp;</div><div>1. Data Type</div><div>2. Analyzers</div><div>3. Mapping</div><div>4. Composite Field Types</div><div><br></div><div>Chapter 7: Data Exploration with Aggregates</div><div>Chapter Goal: This chapter explores the subject of Aggregates. It would help in giving a top level view of entire set of documents. This is unlike queries which just focus on a particular document. It is also shown how to group documents into buckets.</div><div>No of pages: 20</div><div>Sub - Topics:&nbsp;</div><div>1. Buckets and Metrics</div><div>2. Bar Charts</div><div>3. Scoping Aggregations</div><div>4. Aggregates with Filters</div><div>5. Approximate Aggregates</div><div><br></div><div>Chapter 8: Exploring Kibana</div><div>Chapter Goal: This chapter introduces Kibana. It explains basic concepts and key features.</div><div>No of pages: 25</div><div>Sub - Topics:&nbsp;</div><div>1. Kibana Key Concepts</div><div>2. Kibana Features</div><div><br></div><div>Chapter 9: Kibana - Discover, Visualize and Dashboard</div><div>Chapter Goal: This chapter will show how to work with Kibana by illustrating its interface to filter and visualize log messages gathered by Elasticsearch. It will cover the main interface components, and demonstrate how to create searches, visualizations, and dashboards.</div><div>No of pages: 40</div><div>Sub - Topics:&nbsp;</div><div>1. Exploring Discover Page</div><div>2. Exploring Visualize Page</div><div>3. Exploring Dashboard Page</div><div>4. Settings Page</div><div><br></div><div>Chapter 10: Insights with ELK Stack</div><div>Chapter Goal: This chapter really ties up all the components of ELK stack together to arrive at actionable insights. It first shows how to do proper data modelling so that useful logs are emitted by Logstash. Then these logs need to be organized into documents with proper indexing. Finally, appropriate dashboards need to be configured in Kibana to provide data analytics.</div><div>No of pages: 30</div><div>Sub - Topics:&nbsp;</div><div>1. Data Modelling</div><div>2. Configuring Logstash input</div><div>3. Analysis with Kibana</div><div><br></div><div>Chapter 11: Designing for Scale</div><div>Chapter Goal: Elasticsearch can be used to index and search petabytes of data. This chapter shows how Elasticsearch can be run in a cluster containing hundreds of nodes. This requires planning and design. It would cover replica shards and multiple indices.</div><div>No of pages: 25</div><div>Sub - Topics:&nbsp;</div><div>1. Elasticsearch Cluster</div><div>2. Logstash Second Indexer</div><div>3. Replica Shards</div><div>4. Multiple Indices</div><div><br></div><div>Chapter 12: ELK Stack at Work</div><div>Chapter Goal: This chapter would cover practical areas where ELK stack is being used. All the earlier chapters were laying the foundation for the practical aspects of ELK stack. It is being used in companies like Facebook, Netflix. It can be used for lot of diverse purpose like Social Media Analysis, Troubleshooting applications or Grid Monitoring at CERN.</div><div>No of pages: 40</div><div>Sub - Topics:&nbsp;</div><div>1. Social Media Analysis</div><div>2. Live Application Troubleshooting</div><div>3. ELK Stack at Github</div><div>4. ELK Stack at http://stackoverflow.com/</div><div>5. Real Time Analytics</div><div>6. Grid Monitoring at CERN</div><div>7. Searching New York Times Articles</div><div>8. Message Analytics at Netflix</div><div>9. Search at Facebook</div><div><br></div><div>13: Cover troubleshooting, performance improvement<br></div><div><br></div></div></div>