ELK Stack enables companies to handle their unstructured data and provide visualizations from multiple feeds to enable real-time analytics.
ELK stack is a highly scalable suite of open-source, enterprise-ready tools. ELK is an analytics engine that allows users to store, search, and analyze a massive amount of data quickly and in near real-time. It is used as a technology that powers applications that have complex search requirements.
Elastic search is based on Lucene library; developed in JAVA. ELK stacks is a solution of all complex structure and unstructured data. All growing enterprise has set of data collected over a period of time. For climbing next big achievement goal this data is required to be studied. To know and serve customers better, data has to be first extracted from different data sources, logged into single data repository and then can be analysed.
Data lakes are formed after extracting data from various sources and then transformed into structured format. This can also be made continuous process of data logging. Data logging is immutable in nature so are highly trustable records. Once Data Lake is ready, this can be used for analysis and can give various results.
Elasticsearch is aid to many complex data problems. Various use cases of ELK stack
When database becomes huge and search is the essence of the system, it’s wise to move to Elastic search solution. Traditional method cannot deliver quality and speed results on huge database. This is also one of the core features of Elastic search. Along with search it provides inbuilt auto complete feature commonly known is smart search.
ELK stack has become a powerful tool to make any kind of custom monitoring and data logging. It can capture any kind of data irrespective of its source. Kibana then can convert it into meaningful dashboards.
Server Logs can also be plugged into Logstash and Kibana can be used to keep a check on security and its analysis. Automations can be designed based on the outputs. Elastic APM can also be plugged in to improve performance and Optimise the system.
This is a very important and key aspect of data sharding so there is no data failure or loss. Elastic search can manage automatically data sharding and replication. It has primarily 5 shard and 1 replica, which will make 2 nodes in 1 cluster.
In microservice structure, its highly recommended to have Logging feature to understand and identify any issues in the system and solve it later.
Search in unstructured notes and records of patients.
Making smart searches using Machine learning
Monitor real time anomalies using ML
Giving user privatisation on large available content
Elasticsearch can help you to develop a sound search feature. It is capable to search in structured and unstructured data. In no time with related results. Search everything! Search anything!
Kibana can give face to the data. It can visually represent the data and makes it in human readable form.
Its a tool which can create data processing pipelines to ingest the data from various sources. It can transform and log the data.
There are various other products Elastic.co provides as solution, however ELK stack is the major products which can help to solve every aspect of data problem.
Nexuscode works with clients around the globe to provide development and implementation services for the ELK stack. We provide inexpensive custom development to support your Elastic Stack efforts. We apply our deep insights into logistics, distribution, manufacturing, and retail to enrich your Elastic Stack initiative.
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