Search Engines Training in Tashkent

The Elastic Stack (ELK) is a powerful platform designed for real-time searching, analysis, and visualization of log data from multiple sources.

This instructor-led, live training (available online or on-site) is tailored for intermediate-level IT professionals seeking to deepen their ELK expertise in managing distributed log data, automating alerts, and developing advanced visualizations and dashboards.

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

• Configure advanced ingestion and parsing workflows from diverse sources, including databases.
• Develop custom Kibana dashboards tailored to specific teams or use cases.
• Implement email notifications and condition-based alerting mechanisms.
• Leverage regular expressions to enhance search precision within log data.
• Manage user roles and access rights to ensure secure log environments.
• Interact with the Elasticsearch REST API for automation and integration purposes.

Course Format

• Interactive lectures and group discussions.
• Extensive hands-on exercises and practical sessions.
• Live implementation in a dedicated lab environment.

Course Customization Options

• To request a customized version of this training, please contact us to arrange a tailored session.

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 Tashkent (available online or on-site) is designed for intermediate-level administrators and developers who want to deepen their knowledge of Elasticsearch administration. Key areas include advanced dashboard development in Kibana and effective system maintenance.

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.

OpenSearch is an open-source search and analytics suite derived from Elasticsearch 7.10 and Kibana 7.10, originally developed by AWS to maintain a fully open alternative after licensing changes by Elastic NV.

This instructor-led, live training (online or onsite) is aimed at intermediate-level engineers and architects who wish to deploy, configure, and manage OpenSearch clusters for search, observability, and analytics workloads, while understanding its relationship with AWS OpenSearch Service.

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

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

Course Format

• Instructor 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 needs, please reach out to arrange a customized session.

This instructor-led, live training in Tashkent 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 Tashkent (online or onsite) is designed for developers and administrators who want to use OpenSearch to conduct 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 Tashkent (online or in-person) is designed for entry-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 Tashkent (online or onsite) is aimed at advanced-level professionals who wish to administer, monitor, and maintain Elasticsearch clusters effectively for high 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 Tashkent is designed for system administrators who want to set up an ELK stack (Elasticsearch, Logstash, Kibana). Please note that a minimum of 3 participants is required for the course to proceed.

The session starts with an overview of ELK architecture and functionality, then transitions to live lab implementation and practice. Hands-on exercises are a vital part of the training, enabling participants to apply their knowledge while getting feedback on their progress.

The Elastic Stack, previously known as the ELK Stack, is a complete suite of open-source tools created for searching, analyzing, and visualizing both structured and unstructured data. This training program is designed to give participants a thorough understanding of the Elastic Stack's core components: Elasticsearch, Kibana, and Logstash. The curriculum explores foundational concepts, installation and configuration procedures, cluster management, advanced analytics techniques, and best practices for production environments.

The course is organized to offer both theoretical knowledge and practical experience, 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 maintain scalable and resilient Elastic Stack solutions.

The Hidden Cost of "Invisible" Code: Migrating to or building with Nuxt 4 delivers exceptional performance, yet its complex rendering modes (Hybrid, ISR, SWR) create a perilous "Rendering Cliff." If your developers treat Nuxt 4 solely as a UI framework without grasping its hydration behaviour, you risk deploying applications that remain invisible to Google. A site that cannot be indexed yields a 0% organic return on investment. Rectifying these architectural issues after launch costs three to five times more than implementing them correctly during the build phase.

OpenSearch is an open-source search and analytics engine, originally forked from Elasticsearch. It provides distributed search, log analytics, and observability without license risks or managed-service lock-in.

This instructor-led, live training (online or onsite) is aimed at intermediate DevOps and search engineers who wish to use OpenSearch to replace Amazon OpenSearch, Elastic Cloud, or Splunk.

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

• Deploy and secure a multi-node OpenSearch cluster.
• Ingest logs, traces, and metrics via Beats, Fluent Bit, and OpenTelemetry.
• Build dashboards in OpenSearch Dashboards.
• Apply role-based access control and index lifecycle policies.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Apache SolrCloud is a distributed data processing engine designed to facilitate the searching and indexing of files across a distributed network.

In this instructor-led, live training session, 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 SolrCloud's key features and how they compare to those of traditional master-slave clusters
• Configure a centralized SolrCloud cluster
• Automate processes such as communicating with shards, adding documents to shards, and more
• Leverage ZooKeeper alongside SolrCloud to further automate operational workflows
• Utilize the interface for effective error reporting and management
• Implement load balancing for a SolrCloud deployment
• Configure SolrCloud to support continuous processing and fail-over capabilities

Audience

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

Course Format

• A blend of lectures, discussions, practical exercises, and extensive hands-on practice