Elastic Search
A distributed, open source search and analytics engine, designed for horizontal scalability, reliability, and easy management. It combines the speed of search with the power of analytics via a sophisticated, developer-friendly query language covering structured, unstructured, and time-series data
3 Days | Online/Classroom
Prerequisites
REST,HTTP any one programming language C#/Java etc., Knowledge on fiddler/curl/REST client
Training Outcomes
- The ElasticSearch training program covers real-world data sets and instructors work with the participants to ingest, search, and visualize them. This includes an Elasticsearch overview, Logstash configuration, creation of dashboards in Kibana, how to process logs, recommended architecture for designing a system to scale, choosing hardware, and managing the life cycle of your logs.
- By the end of the course, you should have an understanding of what Elasticsearch is capable of, how to implement basic and important functionality
LAB SPECIFICATIONS
Elastic search - Lab
- Installation/Basic Operation work (1.5 hr all hands on)
- System Requirement
- ElasticSearch Node setup
- Configuring Cluster/Node basics
- v Elastic config settings and associated risk and use
- v Creating cluster
- v Logging
- v Resiliency (Replica)
- Introduction to elastic consumer (30 Min)
- Tool to consume Elastic
- Talk about fiddler, UI tools to create restful calls and differences
- Technology for programming
- Setup Node (~3 hr 90% hands on)
- Create a new basic index with minimum fields
- Adding a Document
- Talk about filtering in a request (Reducing response data)
- Using Stack Trace option in case of error response
- Talk about Type
- Various API’s for accessing elastic
- Basic Search Query (1 hr 90% hands on)
- Flavors of full text search
- Bool Search
- Setup Sample bulk data in index (~2 hr 80% hands on)
- Talk about mapping
- Search results
- Analysis (1.5hr 70%l hands on)
- Architecture/Component of analysis
- Analyzer
- Tokenizer
- Inverted Index (30 min 50% hands on)
- Creating a Cluster (Similar to production environment) (1 hr, 70% hands on)
- Scalability
- Various performance parameter
- Aggregations Search (45 Min 90% hands on)
- Relationship Defined in elastic (30 Min 90% hands on)
- Geo-location Search (30 Min 90% hands on) Details Search API (2hr 60% hands on)
- Mappings in details
- Alias
- Synonyms
- Fuzzy Search (30 min 90% hands on)
- Fuzzy setup
- Synonyms search capability
- Various Plugins (30 min to 1 hr based on user requirement)
- Security
- Chinese Language support
- Integration with Spring/.NET application (30 Min)
- Create Spring/Spring-boot REST application
- Integrate with ElasticSearch
- Send/Receive data from ElasticSearch
- Introduction to Kibana and Elastic stack (3hr 80% Hands on)
- Point Kibana to a specific Index on node
- v Talk about .kibana index
- Creating a search query
- Creating Visualization
- Creating Dashboard
- Logstash (4 hr 80% hands on)
- Installation
- Filebeat/Packagebeat
- Data filters
- Parsing data
- Grok
- Mutant
- Production Environment setup consideration (30 min 40% hands on)
- Recap of the configuration setup defined in step 3.c.I
- Defining Data
- Example of book paragraph segregation with complete book saving
- Choosing the right amount of Memory
- Talk about Swapping
- BootStrap Checks / Failure detection
- CPU Consideration
- Replicas
- Shards Consideration
- Multiple indices