Resources

The Cloud Native movement and migration of applications to microservice architectures require general visibility and observability into software behavior. OpenTracing aims to offer a consistent, unified, and tracer-agnostic instrumentation API for a wide range of frameworks, platforms and programming languages. This guide walks you through OpenTracing basics, OpenTracing API, context propagation, and distributed tracers such as Zipkin and Jaeger.

Docker Enterprise Edition (EE) simplifies container orchestration and increases the flexibility and scalability of application deployments. However, the high level of automation create new challenges for monitoring and log management. Why? Because each container typically runs a single process, has its own environment, utilizes virtual networks, or has various methods of managing storage.

Elasticsearch is booming. Together with Logstash, a tool for collecting and processing logs, and Kibana, a tool for searching and visualizing data in Elasticsearch (collectively they comprise the “ELK stack”), adoption of Elasticsearch continues to grow by leaps and bounds. In this detailed booklet Sematext’s DevOps Evangelist, Stefan Thies, walks readers through Elasticsearch and ELK stack basics and supplies numerous graphs, diagrams and infographics to clearly explain the essential elements. There is also a “Top 10 Elasticsearch Metrics” list with corresponding explanations and screenshots. The booklet will be especially helpful to those readers new to Elasticsearch and ELK stack, and also to experienced users who want a quick start into performance monitoring.

This all-things-Logging booklet will especially appeal to readers who are looking to replace Splunk or a similar commercial application with Elasticsearch, Logstash, and Kibana (aka, “ELK stack”) or an alternative logging stack. Topics addressed by our logging experts with how-to instructions, screenshots, code, and more include: 5-Minute Logstash: Parsing and Sending a Log File, Encrypting Logs on Their Way to Elasticsearch, Recipe: rsyslog + Elasticsearch + Kibana, and Structured Logging with rsyslog and Elasticsearch. For more information about logging, see logging posts on Sematext Blog.

Similar to the previous edition of cookbook, we took the time to rebuild the book and all recipes were updated, half of the previous content has been thrown away and new content was added. The very important thing in our minds is that Solr Cookbook Third Edition covers Solr 4.x version (basing on the newest 4.10.3 version of Solr) and Solr 5.0 which should be released very soon.
The book is targeting beginners and intermediate users working with Apache Solr. You’ll find recipes that should make your life easier when you take the first steps with Solr and when you are encountering common problems that intermediate users tend to struggle with. However I don’t recommend the book for those of you who knows everything about Solr – you may find parts of the book interesting, but this book is not directed to you.

Elasticsearch makes it easy to add efficient and scalable searches to your enterprise applications. Busy administrators and developers love this open source real-time search and analytics engine because they can simply install it, make a few tweaks, and go on with their work. And once Elasticsearch is up and running, you’ll discover that it’s miles deep, so you can build nearly any custom search solution you can imagine. The book focuses on Elasticsearch’s REST API via HTTP. Code snippets are written mostly in bash using curl, which makes them easily translatable to other languages.

Apache Solr is a blazing fast, scalable, open source Enterprise search server built upon Apache Lucene. Solr is wildly popular because it supports complex search criteria, faceting, result highlighting, query-completion, query spell-checking, and relevancy tuning, amongst other numerous features. “Apache Solr 4 Cookbook” will show you how to get the most out of your search engine. Full of practical recipes and examples, this book will show you how to set up Apache Solr, tune and benchmark performance as well as index and analyze your data to provide better, more precise, and useful search data.

When Lucene first appeared, this superfast search engine was nothing short of amazing. Today, Lucene still delivers. Its high-performance, easy-to-use API, features like numeric fields, payloads, near-real-time search, and huge increases in indexing and searching speed make it the leading search tool. And with clear writing, reusable examples, and unmatched advice, Lucene in Action, Second Edition is still the definitive guide to effectively integrating search into your applications. It introduces you to searching, sorting, and filtering, and covers the numerous improvements to Lucene since the first edition. Source code is for Lucene 3.0.1.