OpenSearch
Build Secure, Scalable Search and Analytics Engines with OpenSearch – The Open-Source Alternative to ElasticsearchPreview OpenSearch course
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A custom search engine with relevance tuning and filters
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A log monitoring pipeline with dashboards and alerts
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A real-time observability solution using OpenSearch and Fluent Bit
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Set up OpenSearch clusters and secure them using RBAC and TLS
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Ingest data from logs, apps, or APIs using OpenSearch Ingest or Logstash
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Use OpenSearch Query DSL for flexible full-text and term-level search
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Perform aggregations, visualizations, and anomaly detection
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Monitor cluster health, performance, and query throughput
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DevOps and SREs building observability platforms
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Backend developers implementing search capabilities
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Data engineers handling log and event pipelines
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Analysts creating real-time visualizations and alerts
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Anyone transitioning from Elasticsearch to OpenSearch
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Learn the Fundamentals – Understand indices, documents, mappings, and analyzers
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Use the Dev Tools Console – Practice OpenSearch queries via OpenSearch Dashboards
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Follow Each Lab – Build projects like log monitoring and full-text search
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Configure Plugins and Extensions – Try security, anomaly detection, and alerting plugins
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Integrate with Fluent Bit / Filebeat – Ingest logs for real-world simulation
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Secure Early – Practice TLS setup, user roles, and authentication
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Explore the API and CLI Tools – Use RESTful endpoints and OpenSearch CLI
Course/Topic 1 - Coming Soon
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The videos for this course are being recorded freshly and should be available in a few days. Please contact info@uplatz.com to know the exact date of the release of this course.
By the end of this course, you will be able to:
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Deploy and configure OpenSearch clusters and nodes
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Create indices, define mappings, and manage documents
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Build custom queries with OpenSearch Query DSL
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Use Dashboards for data exploration and visualization
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Enable and manage security and access control
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Ingest data from external sources via connectors or APIs
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Implement anomaly detection and alerting rules
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Monitor system health and optimize performance
Course Syllabus
Module 1: Introduction to OpenSearch
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What is OpenSearch?
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Differences from Elasticsearch
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Key Use Cases and Features
Module 2: Setting Up OpenSearch
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Installing OpenSearch and OpenSearch Dashboards
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Running Locally, on Docker, or in the Cloud
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Cluster Configuration and Node Management
Module 3: Indexing and CRUD Operations
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Creating and Managing Indices
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Indexing and Updating Documents via REST API
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Using Bulk Operations
Module 4: Mappings and Analyzers
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Field Types and Mapping Strategies
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Full-Text vs Keyword Fields
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Custom Analyzers and Tokenizers
Module 5: Searching with OpenSearch Query DSL
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Match, Term, Range, and Bool Queries
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Filters and Scoring
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Highlighting, Boosting, and Sorting
Module 6: Aggregations and Analytics
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Buckets and Metrics
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Time-Series Analysis
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Nested and Pipeline Aggregations
Module 7: OpenSearch Dashboards
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Visualizing Indices and Queries
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Building Dashboards and Saved Searches
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Role-Based Access in Dashboards
Module 8: Ingesting Data
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Ingest Pipelines and Processors
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Fluent Bit and Filebeat Integration
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OpenSearch and Logstash Ingestion
Module 9: Observability and Security Plugins
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Enabling TLS and Auth
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User Management and RBAC
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Anomaly Detection and Alerting Plugins
Module 10: Performance and Monitoring
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Monitoring Cluster Health
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Index Lifecycle Management
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Query Optimization and Profiling
Module 11: Projects and Real-World Use Cases
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Custom E-commerce Search Engine
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Infrastructure Log Analytics with Dashboards
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Threat Detection and Alerting Platform
Module 12: OpenSearch Interview Questions & Answers
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Core Concepts and Design
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Query and Mapping Strategies
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Ingestion and Monitoring Best Practices
Upon completing this course, learners will receive a Certificate of Completion from Uplatz, validating their skills in search, analytics, and observability using OpenSearch. This certification is ideal for engineers and analysts working in DevOps, security monitoring, or data-driven application development.
With the rising popularity of OpenSearch as a secure, scalable, and open-source analytics platform, this course prepares you for roles such as:
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OpenSearch Engineer
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Search and Observability Developer
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Site Reliability Engineer (SRE)
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DevOps Platform Specialist
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Log and Security Analytics Architect
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What is OpenSearch and why was it created?
Answer: OpenSearch is an open-source fork of Elasticsearch and Kibana maintained by Amazon and the community. It was created after Elasticsearch’s licensing changed, providing a fully open alternative for search and analytics. -
How is OpenSearch different from Elasticsearch?
Answer: While OpenSearch started as a fork of Elasticsearch 7.10, it has diverged with unique features such as community plugins, native security, anomaly detection, and improved dashboarding. OpenSearch remains fully open-source under the Apache 2.0 license. -
What is OpenSearch Dashboards?
Answer: OpenSearch Dashboards is the visualization layer for OpenSearch, similar to Kibana. It provides visual tools, query editors, and dashboards to analyze and explore data indexed in OpenSearch. -
What is the OpenSearch Query DSL?
Answer: Query DSL is a JSON-based query language used to search, filter, and analyze data in OpenSearch. It supports full-text, term-level, boolean, range, and nested queries with fine-grained control. -
How do you secure an OpenSearch cluster?
Answer: OpenSearch provides built-in security features including TLS encryption, role-based access control (RBAC), authentication (basic, LDAP, SAML), audit logging, and per-index permissions. -
What are ingest pipelines in OpenSearch?
Answer: Ingest pipelines are processing flows that allow data to be transformed during indexing. Processors can modify fields, remove tags, or enrich documents before they are stored. -
How do you monitor cluster health in OpenSearch?
Answer: Use APIs like_cluster/health
,_cat/nodes
, and the performance dashboards within OpenSearch Dashboards. You can also integrate with Prometheus and Grafana. -
What plugins are available in OpenSearch?
Answer: Key plugins include Security, Anomaly Detection, Index Management, Alerting, SQL, and Notifications. These enhance OpenSearch with enterprise features. -
Can OpenSearch integrate with Fluent Bit and Logstash?
Answer: Yes. Fluent Bit and Logstash are commonly used to collect and parse logs before sending them to OpenSearch via the OpenSearch output plugin or REST API. -
What are common use cases for OpenSearch?
Answer:-
Application and infrastructure log analytics
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Full-text search systems
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Security monitoring and SIEM
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Observability and anomaly detection
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Real-time data dashboards
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