Search Engines Training in Turin

The Elastic Stack (ELK) serves as a robust platform for the real-time searching, analysis, and visualization of log data collected from various sources.

This instructor-led training, available both online and onsite, is designed for intermediate-level IT professionals aiming to expand their ELK expertise. Participants will learn to manage distributed log data, automate alert systems, and develop sophisticated visualizations and dashboards.

Upon completing this course, participants will be equipped to:

• Set up complex ingestion and parsing workflows from diverse sources, including databases.
• Build tailored Kibana dashboards to meet the specific needs of different teams or use cases.
• Deploy email notifications and establish condition-based alerting mechanisms.
• Leverage regular expressions to enhance the accuracy of log searches.
• Administer user roles and access permissions to ensure secure log environments.
• Utilize the Elasticsearch REST API for automation and system integration.

Course Format

• Interactive lectures paired with discussions.
• Extensive exercises and practical practice sessions.
• Hands-on implementation within a live laboratory environment.

Customization Options

• For those interested in a tailored training experience for this course, please get in touch with us to arrange your requirements.

OpenSearch is a scalable, open-source search and analytics suite designed for high-volume data indexing, observability, and real-time analytics across distributed systems.

This instructor-led, live training (online or onsite) is aimed at advanced-level engineers and architects who wish to design, deploy, and manage OpenSearch clusters capable of handling large-scale data ingestion and analytics workloads, both on-premises and using AWS OpenSearch Service.

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

• Design and deploy highly scalable OpenSearch clusters across multiple environments.
• Optimize indexing, search, and storage for performance at scale.
• Integrate OpenSearch with AWS OpenSearch Service for hybrid and managed deployments.
• Implement observability, high availability, and automated recovery strategies.

Format of the Course

• Instructor-led theory sessions with guided discussions.
• Extensive hands-on exercises simulating real-world scaling challenges.
• Practical lab work on distributed deployment and performance tuning.

Course Customization Options

• This course can be adapted to emphasize your organization’s data size, performance goals, and deployment environment.

This instructor-led, live training in Turin (online or onsite) is designed for intermediate-level administrators and developers who wish to enhance their understanding of Elasticsearch administration. The curriculum includes advanced techniques for developing dashboards in Kibana, as well as system maintenance.

By the conclusion 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.

OpenSearch is an open-source search and analytics platform derived from Elasticsearch 7.10 and Kibana 7.10. It was originally developed by AWS to provide a fully open alternative following the licensing changes implemented by Elastic NV.

This instructor-led, live training (available online or onsite) is designed for intermediate-level engineers and architects who want to deploy, configure, and manage OpenSearch clusters to handle search, observability, and analytics workloads, while gaining a clear understanding of its relationship with the AWS OpenSearch Service.

Upon completion of this training, participants will be able to:

• Comprehend the architecture, components, and capabilities of OpenSearch and its dashboards.
• Deploy and configure OpenSearch clusters in both on-premises and cloud environments.
• Integrate OpenSearch with the AWS OpenSearch Service and other enterprise data systems.
• Optimize performance, security, and scalability for production-grade deployments.

Course Format

• Instructor-led explanations combined with live demonstrations.
• Hands-on labs and real-world configuration exercises.
• Collaborative discussions focused on troubleshooting and best practices.

Course Customization Options

• To tailor the content or focus of this OpenSearch training to your organization’s specific requirements, please contact us to arrange a customized session.

This instructor-led, live training in Turin 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 Turin (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.

This instructor-led, live training in Turin (onsite or remote) is designed for developers who want to learn 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 the monitoring of log files.
• Integrate index and query time plugins.
• Create optimized clusters that can handle thousands of queries per second.

This instructor-led, live training in Turin (online or onsite) is aimed at beginner-level IT professionals and developers who wish to use Elasticsearch to store, search, and analyze data in real time.

By the end of this training, participants will be able to: install and configure Elasticsearch, index and query data, optimize search performance, and integrate Elasticsearch into applications.

This instructor-led live training in Turin (online or onsite) is designed for advanced professionals who aim to effectively administer, monitor, and maintain Elasticsearch clusters for optimal performance and availability.

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

• Deploy and configure Elasticsearch clusters for high availability and performance.
• Monitor and optimize Elasticsearch operations.
• Integrate with Kibana and Logstash for advanced analytics and visualization.
• Extend Elasticsearch functionality with plugins.
• Scale Elasticsearch using clustering and sharding techniques.

This instructor-led, live training in Turin is designed for system administrators who want to configure an ELK stack (Elasticsearch, Logstash, Kibana). Please note that a minimum of 3 participants is required for the course to proceed.

The session begins with an overview of ELK architecture and functionality, progressing to practical lab implementation and application. Hands-on exercises are a key component, allowing participants to apply their knowledge in real-time while receiving constructive feedback on their performance.

The Elastic Stack (previously known as the ELK Stack) is a robust collection of open-source tools intended for searching, analyzing, and visualizing both structured and unstructured data. This training course is specifically designed to provide participants with an in-depth knowledge of the Elastic Stack's core components: Elasticsearch, Kibana, and Logstash. The curriculum addresses fundamental principles, installation procedures, configuration, cluster administration, advanced analytics, and industry best practices for production environments. The program is organized to deliver both theoretical knowledge and practical application, making it ideal for professionals aiming to deploy, manage, and optimize the Elastic Stack in real-world scenarios. Upon completion, participants will possess the necessary skills to design, implement, and sustain scalable and resilient Elastic Stack solutions.

This training introduces Kibana to users of Elasticsearch.

Kibana is an open-source analytics and visualization platform designed to integrate with Elasticsearch. You will use Kibana to search, view, and interact with data stored in Elasticsearch indices. It allows you to easily perform advanced data analysis and visualize your information through various charts, tables, and maps.

Kibana simplifies the understanding of large data volumes. Its intuitive, browser-based interface enables you to quickly create and share dynamic dashboards that display real-time changes to Elasticsearch queries.

The Hidden Cost of "Invisible" Code Migrating to or building with Nuxt 4 offers incredible performance, but its complex rendering modes (Hybrid, ISR, SWR) create a dangerous "Rendering Cliff." If your developers treat Nuxt 4 purely as a UI framework without understanding its hydration behavior, you risk deploying applications that are invisible to Google. A site that cannot be indexed yields 0% organic return on investment. Fixing these architectural issues post-launch costs 3x to 5x more than implementing them correctly during the build.

This instructor-led, live training in Turin (online or onsite) is designed for web developers who want to use regular expressions to build robust algorithms for defining search patterns.

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

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

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 provides an introduction to the Solr platform. By combining lectures, discussions, and practical labs, students will acquire hands-on experience in configuring efficient search and indexing capabilities.

The training starts with the fundamental installation and configuration of Solr, then progresses to teaching the search functionalities. Students will gain proficiency in key features such as faceting, indexing, and search relevance, which are central to the Solr platform. The course concludes with several advanced topics, including spell checking, suggestions, Multicore, and SolrCloud.

Duration: 3 days

Audience: Developers, business users, and administrators