Unlock real-time data insights! Explore the roadmap to hiring the best Elasticsearch developers creating lightning-fast search and analytics solutions.
Elasticsearch has become perhaps the most popular search analytics engine. Thousands of companies including Netflix, Shopify, Slack, Uber, Instacart, Udemy, Stack Overflow, and Wikipedia use the tool.
First released in 2010, Elasticsearch is an open-source tool known for being a multi-faceted, multi-purpose search engine with countless applications – indexing, security intelligence, business analytics, and big data, to name a few. It also offers several wide-ranging benefits, from scalability to high performance.
In just over a decade, Elasticsearch has grown from a search engine to a complete ecosystem, alongside components and tools within the so-called “Elastic Stack”. Its popularity has led many companies to try to incorporate the platform into their own stacks.
Are you looking to bring the power of Elasticsearch to your organization? Find out what to look for in a developer specializing in the subject and how to find the best option.
What is Elasticsearch?
Built on Apache Lucene, Elasticsearch is an open-source search and analytics engine that accesses, manages, and stores many different types of data:
- Geospatial
- Numeric
- Structured
- Textual
- Unstructured
A NoSQL database, Elasticsearch is famous for its foundation of RESTful APIs. It offers many distinct benefits, such as:
- Speed/high performance
- Scalability
- Reliability
- Easy deployment
- Distribubility
Elasticsearch has several purposes, including document indexing, data analysis and summarization, and information storage. Its ability to speed up real-time searches and present analysis immediately is the main reason it has become so widely used.
Today, Elasticsearch is the central tool of the so-called “Elastic Stack”, an ecosystem of tools for finding, manipulating and managing data. Logstash and Kibana accompany Elasticsearch to provide companies with the ability to process and visualize data in a variety of ways.
What to look for in an Elasticsearch developer
Elasticsearch and the Elastic Stack are extremely popular, so it's not too difficult to find a talented developer with strong skills in these technologies. That said, you want to look for a professional who can present previous work with a clear specialization in this area. There are certifications in Elasticsearch and other tools on the ELK Stack that demonstrate superior skills in these technologies.
Of course, the candidate must have excellent programming and development skills, with experience using languages such as Java and SQL. Extensive knowledge of database architecture and design and management is also essential, as is experience with databases and data solutions.
Elasticsearch specializations
There are several specialties in Elasticsearch and the ELK Stack, so it's important to determine which ones are right for your business. Engineers, developers and consultants are some of these specialties.
As noted, there are Elasticsearch certifications available, which serve to demonstrate high knowledge and experience in the ELK stack across different types of roles.
An Elastic Certified Engineer, for example, focuses on expertise in the technology of the same name, while a Kibana certification helps data analysts improve their data visualization and analysis skills. Observability engineers can hone their data observability skills, allowing them to work with dashboards, machine learning, and more.
Interview Questions
What are the main features of Elasticsearch?
Elasticsearch has several key features. They include:
- RESTful APIs
- Indexing
- Multilingual support
- Strong security
- Geolocation support
- Near real-time search
- Grouping
- Full text search
- Automatic node recovery and data rebalancing
- Alert
- Rollups and data flows
- Schema creation
- Filtering
Additionally, some of the benefits are:
- Scalability, both horizontally and vertically
- Reliability and resilience
- Wide integration availability
How can you search on Elasticsearch?
Elasticsearch supports 3 types of searches. In a multi-index, multi-type search, you can search APIs across indexes thanks to the multi-index system. In a URI lookup, the search request is initiated via a URI with the search providing the parameters for the request. Finally, in a request body lookup, the request must be executed with a lookup DSL, including the query DSL in the body.
Explain the nodes
When you launch an Elasticsearch instance, you launch a node. There are several types of nodes:
- Master nodes play a primary role, controlling the cluster and allowing management and configuration of additions and deletions of other roles.
- Data nodes store and manipulate data.
- Client nodes serve as balancers, sending cluster requests to master and data nodes.
- Ingestion nodes transform and process documents before indexing.
What is a cluster in Elasticsearch?
A cluster is a group of one or more nodes that stores the entire dataset. The cluster enables federated indexing and searching across all nodes. A node must be given an individual name and assigned to join a cluster.
Explain indexes
Clusters can include various types of indexes. Each index is essentially a database of documents, each containing fields with values.
Job description
An innovation-driven company is looking for a software engineer with experience in Elasticsearch and a passion for developing new technologies. The successful candidate will have extensive experience working with Elasticsearch and integrating the platform with other tools and technologies.
Responsibilities
- Work with engineering, UI/UX, and data science teams to develop products that incorporate Elasticsearch
- Design new systems to measure and implement quality control procedures
- Identify opportunities for new software and improvements to existing technologies
- Communicate with stakeholders
- Research and gather requirements
- Debugging Software
Skills and qualifications
- At least 4 years of experience in Elasticsearch development and Elastic Cloud migration
- At least 7 years of total application development experience
- Experience working with other tools in the ELK stack
- Knowledge of Java, Apache, Terraform, C#, .NET, SQL, REST, HTML/CSS, Angular, Spring, Spring Boot, Spark, C/C++, Python and other tools, languages and technologies
- Knowledge of database design and architecture
- Strong written and verbal communication, problem solving, strategic thinking and collaboration skills
- Bachelor's degree in computer science or related field
