Elasticsearch Advanced Administration, Monitoring and Maintenance Training Course

This instructor-led, live training in Taiwan (online or onsite) is aimed at intermediate-level administrators and developers who wish to deepen their understanding of Elasticsearch administration, including advanced techniques for dashboard development in Kibana, as well as maintenance of the system.

By the end of this training, participants will be able to:

• Set up and configure Elasticsearch and Kibana environments for advanced administration and dashboard development.
• Create and manage Elasticsearch indices, mappings, and data models.
• Develop advanced queries and filters to extract valuable insights from Elasticsearch data.
• Design and build interactive dashboards in Kibana using various visualization types and techniques.
• Implement best practices for Elasticsearch and Kibana administration, optimization, and troubleshooting.

Audience

Administrators or developers who want to know how to use Elasticsearch.

Audiance

Administrators or developers who want to know how to use Elasticsearch.

This instructor-led, live training in Taiwan is aimed at software developers who wish to build search and analytics solutions using Elasticsearch.

The training starts with a discussion of the Elasticsearch architecture, including its distributed model and search API. This is followed by an explanation of Elasticsearch's functionality and how to best integrate it into an existing application.

Hands-on exercises make up an important part of the training, and give participants a chance to put into practice their knowledge while receiving feedback on their implementation and progress.

This instructor-led, live training in Taiwan is aimed at system administrators who wish to set up an ELK stack (Elasticsearch, Logstash, Kibana). Note that a minimum of 3 delegates is needed for this course to run.

The training starts with a discussion of ELK architecture and functionality, then moves on to live lab implementation and practice. Hands-on exercises make up an important part of the training and give participants a chance to put into practice their knowledge while receiving feedback on their progress.

This training introduces Kibana to the users of Elasticsearch.

Kibana is an open source analytics and visualization platform designed to work with Elasticsearch. You use Kibana to search, view, and interact with data stored in Elasticsearch indices. You can easily perform advanced data analysis and visualize your data in a variety of charts, tables, and maps.

Kibana makes it easy to understand large volumes of data. Its simple, browser-based interface enables you to quickly create and share dynamic dashboards that display changes to Elasticsearch queries in real time.

This instructor-led, live training in Taiwan (online or onsite) is aimed at web developers who wish to use regular expressions to create robust algorithms for defining search patterns.

By the end of this training, participants will be able to:

• Write complex search patterns using character sets.
• Apply regular expression techniques to any regex engine like PHP, Python, etc.
• Script automation into a system process using extended regular expressions.

This instructor-led, live training in Taiwan (onsite or remote) is aimed at developers who wish to know how to use Solr for advanced development.

By the end of this training, participants will be able to:

• Tune and scale Solr and SolrCloud.
• Streamline monitor log files.
• Integrate index and query time plugins.
• Create optimized clusters that handle thousands of queries per second.

Drupal is a free and open-source framework for content management and digital experiences. Apache Solr is a fast, scalable and open-source Java search platform.

Apache SolrCloud is a distributed data processing engine that facilitates the searching and indexing of files on a distributed network.

In this instructor-led, live training, participants will learn how to set up a SolrCloud instance on Amazon AWS.

By the end of this training, participants will be able to:

• Understand SolCloud's features and how they compare to those of conventional master-slave clusters
• Configure a SolCloud centralized cluster
• Automate processes such as communicating with shards, adding documents to the shards, etc.
• Use Zookeeper in conjunction with SolrCloud to further automate processes
• Use the interface to manage error reporting
• Load balance a SolrCloud installation
• Configure SolrCloud for continuous processing and fail-over

Audience

• Solr Developers
• Project Managers
• System Administrators
• Search Analysts

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

This course introduces students to the Solr platform. Through a combination of lecture, discussion and labs students will gain hands on experience configuring effective search and indexing.

The class begins with basic Solr installation and configuration then teaches the attendees the search features of Solr. Students will gain experience with faceting, indexing and search relevance among other features central to the Solr platform. The course wraps up with a number of advanced topics including spell checking, suggestions, Multicore and SolrCloud.

Duration: 3 days

Audience: Developers, business users, administrators

The course is intended for IT specialist that want to implement a solution that allows for elastic and efficient searching of big data sources. This course uses the newest stable version of Solr, if you wish to use older or unstable version, please contact sales before booking.

This instructor-led, live training in Taiwan (online or onsite) is aimed at developers and administrators who wish to use OpenSearch to perform distributed search and data analytics in a unified and secure system.

By the end of this training, participants will be able to:

• Set up the necessary development environment to start building search and analytics solutions with OpenSearch and OpenSearch Dashboards.
• Understand the three approaches (snapshot, restart, and rolling) in upgrading from Elasticsearch OSS to OpenSearch.
• Learn how to index data, create data streams, run queries, and streamline cross-cluster operations in OpenSearch.
• Explore and use plugins, APIs, clients, and ingestion tools (Beats, Logstash, Grafana, etc.) to optimize search experience while keeping clusters secure.
• Use OpenSearch Dashboards to centralize data management, visualization, logging, monitoring, and maintenance.