Hire Deeply Vetted ELK stack (Elasticsearch, Logstash, Kibana) Developer

Upstaff is the best deep-vetting talent platform to match you with top ELK stack (Elasticsearch, Logstash, Kibana) developers remotely. Scale your engineering team with the push of a button

Hire Deeply Vetted <span>ELK stack (Elasticsearch, Logstash, Kibana) Developer</span>
Trusted by Businesses

Chuck N., Senior Python Engineer

Last Updated: 4 Jul 2023

- 12 years with Python (Django, Flask, and other Python frameworks), PostgreSQL 10 years - 22 years of experience in tech - Strong experience in data structures, software development with object-oriented design, cloud platforms - Data scraping from SourceForge & Yahoo Finance, ETL pipelines - ELK (Elasticsearch, Logstash, Kibana) stack, various Data / API Integrations, IoT (Internet of Things) - Advanced English - Available ASAP

Learn more
ELK stack (Elasticsearch, Logstash, Kibana)

ELK stack (Elasticsearch, Logstash, Kibana)


Python   12 yr.

View Chuck

Vladyslav K, Senior AWS DevOps Engineer

Vinnitsa, Ukraine
Last Updated: 4 Jul 2023

- 4 years in IT field as a DevOps Engineer. Strong scripting skills (Python, Bash, Groovy). - Good understanding of Software Development processes. Practical experience and professional competence in CI/CD (Jenkins, Azure DevOps), infrastructure as code (Terraform, CloudFormation), monitoring (ELK, Zabbix, Grafana), cluster management (Kubernetes, Kubespray, Helm), configuration management (Ansible) and computer network. Proficiency in Amazon Web Services. Extensive background in UNIX-like Operating Systems administration and maintenance. - Upper-Intermediate English

Learn more
ELK stack (Elasticsearch, Logstash, Kibana)

ELK stack (Elasticsearch, Logstash, Kibana)

Amazon Web Services (AWS)

Amazon Web Services (AWS)

View Vladyslav

Oleksandr T., Full-Stack Software Engineer (Java/Angular)

Zaporizhzhya, Ukraine
Last Updated: 5 Dec 2023

- Full-Stack Developer with experience in various projects, including military weapon maintenance, truck analytics, app store launch, social benefits management, ISP monitoring, and router web interface. - Over 6 years of experience and a solid background in object-oriented analysis and design, comprehensive knowledge of system development life cycle, physical and logical data modeling, performance tuning, and enterprise-level system development. - Led a team responsible for data migration to the cloud, enabling server-to-cloud data synchronization and strengthening software security. - Upper-Intermediate English

Learn more
ELK stack (Elasticsearch, Logstash, Kibana)

ELK stack (Elasticsearch, Logstash, Kibana)



View Oleksandr

Mykyta G., Java Developer

Last Updated: 16 Aug 2023

- 4+ years of experience in developing applications using Java and related technologies. - Good knowledge in programming JDBC, Hibernate. - Experience in using Design patterns. - Good logical thinking, self-learning, high level of responsibility. - Hard-working, result-oriented, creative and communicative, team player. - Upper-Intermediate English. - Availability starting from 18.09.2023

Learn more
ELK stack (Elasticsearch, Logstash, Kibana)

ELK stack (Elasticsearch, Logstash, Kibana)



View Mykyta

Mykhaylo R., DevOps/SRE/Lead System Administrator

Last Updated: 19 Mar 2024
Identity Verified
Language Verified
Programming Skills Verified
CV Verified

- Over 20 years in IT with a master's degree in Cybernetics - Proficient in Ansible: Extensive experience in deploying and managing Ansible-driven infrastructure, particularly highlighted in roles as SRE/Architect (Aug 2018 – Present) and Senior DevOps Engineer/Lead Sysadmin (Aug 2020 – May 2021), where Ansible was pivotal in scaling a learning platform from 1,000 to over 100,000 students and in key migration projects. - Expertise in Windows Environments: Demonstrated strong skills in managing Windows environments, especially as an SRE/Architect (Aug 2018 – Present) and CTO (2013 – Mar 2022), involving Windows AD+MSSQL backoffice management and ITIL Service Management framework implementation on Windows platforms. - Versatile IT Roles with Ansible and Windows: Across various roles including IT Service Manager, Senior DevOps Engineer, and CTO, consistently applied Ansible and Windows technologies in large-scale infrastructure projects and day-to-day operations, showing versatility and depth in these areas. - Managing the growth of the learning platform from 1,000+ to 100k+ active students - ITIL v3 Foundations Certificate - More than 5 years of experience in leading ITIL Service Management capability and implementing end-to-end ITIL Service Management framework - Strong experience in using ServiceNow and Jira Service Desk for ITSM - Experienced IT/Telecom Specialist - UNIX and UNIX-Like OS (FreeBSD, Linux, SunOS, MacOS X) background - Over 20 years of Windows/windows server family. From NT4.0 /win3.1 up to Server2019. As well as upgrading Up to 15 years with server HW, and 13 years with storage solutions - Infrastructure problem-solver with a strong view on reliability, performance, and disaster recovery - Fluent English

Learn more
ELK stack (Elasticsearch, Logstash, Kibana)

ELK stack (Elasticsearch, Logstash, Kibana)


Bash   10 yr.

Shell Scripts

Shell Scripts   10 yr.


MySQL   10 yr.



Ansible Playbook

Ansible Playbook

View Mykhaylo

Talk to Our Talent Expert

Our journey starts with a 30-min discovery call to explore your project challenges, technical needs and team diversity.
Maria Lapko
Global Partnership Manager

Only 3 Steps to Hire ELK stack (Elasticsearch, Logstash, Kibana) Engineers

Talk to Our Talent Expert
Our journey starts with a 30-min discovery call to explore your project challenges, technical needs and team diversity.
Meet Carefully Matched Talents
Within 1-3 days, we’ll share profiles and connect you with the right talents for your project. Schedule a call to meet engineers in person.
Validate Your Choice
Bring new talent on board with a trial period to confirm you hire the right one. There are no termination fees or hidden costs.

Welcome to Upstaff

Yaroslav Kuntsevych
Upstaff.com was launched in 2019, addressing software service companies, startups and ISVs, increasingly varying and evolving needs for qualified software engineers

Yaroslav Kuntsevych

Trusted by People
Henry Akwerigbe
Henry Akwerigbe
This is a super team to work with. Through Upstaff, I have had multiple projects to work on. Work culture has been awesome, teammates have been super nice and collaborative, with a very professional management. There's always a project for you if you're into tech such Front-end, Back-end, Mobile Development, Fullstack, Data Analytics, QA, Machine Learning / AI, Web3, Gaming and lots more. It gets even better because many projects even allow full remote from anywhere! Nice job to the Upstaff Team 🙌🏽.
Vitalii Stalynskyi
Vitalii Stalynskyi
I have been working with Upstaff for over a year on a project related to landscape design and management of contractors in land design projects. During the project, we have done a lot of work on migrating the project to a multitenant architecture and are currently working on new features from the backlog. When we started this project, the hiring processes were organized well. Everything went smoothly, and we were able to start working quickly. Payments always come on time, and there is always support from managers. All issues are resolved quickly. Overall, I am very happy with my experience working with Upstaff, and I recommend them to anyone looking for a new project. They are a reliable company that provides great projects and conditions. I highly recommend them to anyone looking for a partner for their next project.
Владислав «Sheepbar» Баранов
Владислав «Sheepbar» Баранов
We've been with Upstaff for over 2 years, finding great long-term PHP and Android projects for our available developers. The support is constant, and payments are always on time. Upstaff's efficient processes have made our experience satisfying and their reliable assistance has been invaluable.
Roman Masniuk
Roman Masniuk
I worked with Upstaff engineers for over 2 years, and my experience with them was great. We deployed several individual contributors to clients' implementations and put up two teams of upstaff engineers. Managers' understanding of tech and engineering is head and shoulders above other agencies. They have a solid selection of engineers, each time presented strong candidates. They were able to address our needs and resolve things very fast. Managers and devs were responsive and proactive. Great experience!
Yanina Antipova
Yanina Antipova
Хочу виразити велику подяку за таку швидку роботу по підбору двох розробників. Та ще й у такий короткий термін-2 дні. Це мене здивувало, адже ми шукали вже цілий місяць. І знайдені кандидати нам не підходили Це щось неймовірне. Доречі, ці кандидати працюють у нас і зараз. Та надать приклад іншим працівникам. Гарного дня!)
Наталья Кравцова
Наталья Кравцова
I discovered an exciting and well-paying project on Upstaff, and I couldn't be happier with my experience. Upstaff's platform is a gem for freelancers like me. It not only connects you with intriguing projects but also ensures fair compensation and a seamless work environment. If you're a programmer seeking quality opportunities, I highly recommend Upstaff.
Leaving a review to express how delighted I am to have found such a great side gig here. The project is intriguing, and I'm really enjoying the team dynamics. I'm also quite satisfied with the compensation aspect. It's crucial to feel valued for the work you put in. Overall, I'm grateful for the opportunity to contribute to this project and share my expertise. I'm thrilled to give a shoutout and recommendation to anyone seeking an engaging and rewarding work opportunity.

Hire ELK stack (Elasticsearch, Logstash, Kibana) Developer as Effortless as Calling a Taxi

Hire ELK stack (Elasticsearch, Logstash, Kibana) engineer

FAQs about ELK stack (Elasticsearch, Logstash, Kibana) Development

How do I hire a ELK stack (Elasticsearch, Logstash, Kibana) developer? Arrow

If you urgently need a verified and qualified ELK stack (Elasticsearch, Logstash, Kibana) developer, and resources for finding the right candidate are lacking, UPSTAFF is exactly the service you need. We approach the selection of ELK stack (Elasticsearch, Logstash, Kibana) developers professionally, tailored precisely to your needs. From placing the call to the completion of your task by a qualified developer, only a few days will pass.

Where is the best place to find ELK stack (Elasticsearch, Logstash, Kibana) developers? Arrow

Undoubtedly, there are dozens, if not hundreds, of specialized services and platforms on the network for finding the right ELK stack (Elasticsearch, Logstash, Kibana) engineer. However, only UPSTAFF offers you the service of selecting real qualified professionals almost in real time. With Upstaff, software development is easier than calling a taxi.

How are Upstaff ELK stack (Elasticsearch, Logstash, Kibana) developers different? Arrow

AI tools and expert human reviewers in the vetting process are combined with a track record and historically collected feedback from clients and teammates. On average, we save over 50 hours for client teams in interviewing ELK stack (Elasticsearch, Logstash, Kibana) candidates for each job position. We are fueled by a passion for technical expertise, drawn from our deep understanding of the industry.

How quickly can I hire ELK stack (Elasticsearch, Logstash, Kibana) developers through Upstaff? Arrow

Our journey starts with a 30-minute discovery call to explore your project challenges, technical needs, and team diversity. Meet Carefully Matched ELK stack (Elasticsearch, Logstash, Kibana) Talents. Within 1-3 days, we’ll share profiles and connect you with the right talents for your project. Schedule a call to meet engineers in person. Validate Your Choice. Bring a new ELK stack (Elasticsearch, Logstash, Kibana) developer on board with a trial period to confirm that you’ve hired the right one. There are no termination fees or hidden costs.

How does Upstaff vet remote ELK stack (Elasticsearch, Logstash, Kibana) engineers? Arrow

Upstaff Managers conduct an introductory round with potential candidates to assess their soft skills. Additionally, the talent’s hard skills are evaluated through testing or verification by a qualified developer during a technical interview. The Upstaff Staffing Platform stores data on past and present ELK stack (Elasticsearch, Logstash, Kibana) candidates. Upstaff managers also assess talent and facilitate rapid work and scalability, offering clients valuable insights into their talent pipeline. Additionally, we have a matching system within the platform that operates in real-time, facilitating efficient pairing of candidates with suitable positions.

Discover Our Talent Experience & Skills

Browse by Experience
Browse by Skills
Browse by Experience
Browse by Experience
Browse by Skills
Rust Frameworks and Libraries Arrow
Adobe Experience Manager (AEM) Arrow
_Business Intelligence (BI) Arrow
Codecs & Media Containers Arrow
Hosting, Control Panels Arrow

Hiring ELK stack (Elasticsearch, Logstash, Kibana) developers? Then you should know!

Share this article
Table of Contents

TOP 13 Facts about ELK stack (Elasticsearch, Logstash, Kibana)

  • ELK stack is a combination of three powerful open-source tools: Elasticsearch, Logstash, and Kibana.
  • Elasticsearch is a distributed, RESTful search and analytics engine designed for horizontal scalability and real-time search.
  • Logstash is a flexible data ingestion and processing pipeline that allows you to collect, parse, and enrich data from various sources.
  • Kibana is a data visualization and exploration tool that provides a user-friendly interface to interact with data stored in Elasticsearch.
  • ELK stack is widely used for log analysis, real-time monitoring, and operational intelligence.
  • Elasticsearch, the core component of ELK stack, offers advanced search capabilities, including full-text search, filtering, and aggregations.
  • Logstash supports a wide range of data inputs and outputs, making it easy to collect logs and data from diverse sources such as files, databases, and message queues.
  • With Logstash’s powerful filtering capabilities, you can easily transform and enrich your data before storing it in Elasticsearch.
  • Kibana provides a variety of visualization options, including charts, graphs, and maps, allowing you to gain insights from your data.
  • ELK stack can handle large volumes of data and is designed to scale horizontally by adding more nodes to the cluster.
  • The open-source nature of ELK stack allows for community-driven development and a vibrant ecosystem of plugins and integrations.
  • ELK stack is used by many organizations and industries, including e-commerce, finance, healthcare, and cybersecurity, to analyze and monitor their data.
  • ELK stack supports various security features, such as encryption, role-based access control (RBAC), and audit logging, ensuring the confidentiality and integrity of your data.
  • ELK stack is constantly evolving, with regular updates and new features being added to improve performance, scalability, and usability.

Cases when ELK stack (Elasticsearch, Logstash, Kibana) does not work

  1. Insufficient hardware resources: The ELK stack requires a significant amount of computational power, memory, and storage to handle large volumes of data efficiently. If the hardware resources allocated to the ELK stack are insufficient, it may lead to performance issues, slow processing, and even system crashes.
  2. Improper configuration: The ELK stack consists of multiple components that need to be properly configured and interconnected. If any of the configurations are incorrect or misaligned, it can lead to data ingestion failures, indexing issues, or inability to visualize data effectively in Kibana.
  3. Network connectivity problems: As the ELK stack operates in a distributed manner, it relies heavily on network connectivity between its components. If there are issues with network connectivity, such as packet loss, high latency, or network congestion, it can impact the overall functionality and performance of the ELK stack.
  4. Insufficient storage capacity: Elasticsearch requires ample storage capacity to store the indexed data. If the storage capacity allocated to Elasticsearch is insufficient, it may result in data loss, incomplete indexing, or the inability to retain historical data for analysis.
  5. Data ingestion challenges: Logstash, the data ingestion component of the ELK stack, may face challenges in parsing and processing certain types of log data. If the log data is in a format that Logstash does not support or if there are issues with the log data itself (e.g., corrupt files, incompatible encodings), it can cause data ingestion failures.
  6. Security and access control issues: Elasticsearch, as a distributed search and analytics engine, needs to be properly secured to prevent unauthorized access and data breaches. If security measures such as user authentication, role-based access control, or SSL/TLS encryption are not properly implemented, it can expose sensitive data and compromise the integrity of the ELK stack.
  7. Data scalability limitations: While Elasticsearch is designed to handle large volumes of data, there are scalability limits depending on the hardware resources and cluster configuration. If the data volume exceeds the scalability limits of the ELK stack, it may result in performance degradation, increased response times, or the need for additional hardware resources.

Soft skills of a ELK stack (Elasticsearch, Logstash, Kibana) Developer

Soft skills are as important as technical skills for an ELK stack (Elasticsearch, Logstash, Kibana) Developer, as they contribute to the overall success of a project. Here are the essential soft skills for developers at different levels:


  • Effective Communication: Ability to clearly convey ideas and information to team members and stakeholders.
  • Adaptability: Willingness to learn and quickly adapt to new technologies and tools.
  • Attention to Detail: Paying close attention to small details to ensure accurate and reliable data analysis.
  • Collaboration: Working well in a team environment, sharing knowledge and ideas with colleagues.
  • Problem-Solving: Being resourceful and finding creative solutions to technical challenges.


  • Leadership: Taking ownership of tasks and guiding junior developers in the team.
  • Time Management: Prioritizing tasks and delivering work within deadlines.
  • Mentoring: Assisting junior developers in their professional growth by sharing knowledge and providing guidance.
  • Critical Thinking: Analyzing complex problems and making informed decisions.
  • Customer Focus: Understanding user requirements and delivering solutions that meet their needs.
  • Teamwork: Collaborating effectively with cross-functional teams to ensure smooth project execution.
  • Conflict Resolution: Resolving conflicts and promoting a positive work environment.


  • Project Management: Overseeing multiple projects and ensuring their successful completion.
  • Strategic Thinking: Aligning technical solutions with business goals and objectives.
  • Decision-Making: Making informed decisions based on data analysis and industry best practices.
  • Presentation Skills: Communicating complex technical concepts to non-technical stakeholders.
  • Innovation: Identifying opportunities for process improvements and introducing new technologies.
  • Quality Assurance: Ensuring the delivery of high-quality and reliable ELK solutions.
  • Client Management: Building and maintaining strong relationships with clients.
  • Continuous Learning: Staying up-to-date with the latest trends and advancements in ELK stack development.

Expert/Team Lead

  • Strategic Planning: Developing long-term plans and roadmaps for ELK stack projects.
  • Team Management: Leading and mentoring a team of developers to achieve project objectives.
  • Negotiation Skills: Negotiating contracts, timelines, and resources with clients and stakeholders.
  • Business Acumen: Understanding the business implications and impact of ELK stack solutions.
  • Risk Management: Identifying and mitigating risks associated with project delivery.
  • Vendor Management: Collaborating with external vendors to leverage their expertise and resources.
  • Technical Expertise: Deep understanding of ELK stack components and their integration.
  • Strategic Partnerships: Establishing partnerships with technology vendors and industry experts.
  • Change Management: Managing organizational change during the implementation of ELK stack projects.
  • Continuous Improvement: Driving continuous improvement initiatives to enhance development processes.
  • Empathy: Understanding and empathizing with the needs and concerns of team members.

How and where is ELK stack (Elasticsearch, Logstash, Kibana) used?

Case NameCase Description
Log Analysis and TroubleshootingELK stack is widely used for log analysis and troubleshooting in various industries. By integrating Elasticsearch, Logstash, and Kibana, organizations can collect, parse, and visualize log data from different sources in real-time. This allows developers and system administrators to easily identify errors, anomalies, and performance bottlenecks, enabling them to troubleshoot and resolve issues more efficiently.
Security Monitoring and Threat DetectionELK stack is a powerful tool for security monitoring and threat detection. By aggregating and analyzing security logs, network traffic, and system events, organizations can identify potential security breaches, detect malicious activities, and respond to threats in a timely manner. Elasticsearch’s indexing and searching capabilities, combined with Kibana’s visualizations and dashboards, provide security teams with valuable insights into their infrastructure’s security posture.
Application Performance MonitoringELK stack can be utilized for application performance monitoring, allowing organizations to gain visibility into the performance metrics of their applications. By collecting and analyzing application logs, system metrics, and user interactions, developers can identify performance issues, optimize application performance, and enhance the user experience. With Kibana’s powerful visualizations and Elasticsearch’s fast search capabilities, organizations can monitor and analyze application performance in real-time.
Business Intelligence and AnalyticsELK stack can be leveraged for business intelligence and analytics purposes. By integrating Elasticsearch with various data sources, organizations can index and analyze large volumes of data in real-time. Kibana’s rich set of visualizations and dashboards allow users to explore and analyze data, uncover insights, and make data-driven decisions. This makes ELK stack a valuable tool for data analysis and decision-making across different industries.
DevOps and Continuous DeliveryELK stack plays a crucial role in DevOps and continuous delivery processes. By collecting and analyzing logs, metrics, and events from different stages of the software development lifecycle, organizations can gain valuable insights into the performance and stability of their applications. This helps in identifying areas for improvement, optimizing resource allocation, and ensuring smooth and efficient deployment processes.
Real-time Monitoring of IoT DevicesELK stack can be utilized for real-time monitoring of IoT devices and sensors. By collecting and analyzing data streams from IoT devices, organizations can gain insights into device performance, detect anomalies, and trigger alerts or actions based on predefined thresholds. Elasticsearch’s fast indexing and querying capabilities make it ideal for handling large volumes of streaming data, while Kibana enables visualizing and analyzing the IoT data in real-time.
Log Data Centralization and StandardizationELK stack provides a centralized platform for log data storage, centralization, and standardization. By collecting logs from various systems, applications, and devices into a single repository, organizations can simplify log management, perform cross-system log analysis, and maintain a standardized log format. Elasticsearch’s scalability and flexibility, combined with Logstash’s log processing capabilities, make it an ideal choice for log data centralization and standardization.
Compliance and Audit TrailELK stack can assist organizations in meeting compliance requirements and maintaining audit trails. By collecting, indexing, and analyzing logs and events from various systems and applications, organizations can demonstrate compliance, track user activities, and investigate security incidents. Elasticsearch’s powerful search capabilities enable efficient searching and retrieval of relevant log data, while Kibana’s visualizations and dashboards facilitate auditing and reporting processes.

What are top ELK stack (Elasticsearch, Logstash, Kibana) instruments and tools?

  • Elasticsearch: Elasticsearch is a distributed, open-source search and analytics engine built on Apache Lucene. It was first released in 2010 and is known for its scalability, speed, and ease of use. Elasticsearch is widely used for full-text search, log analysis, and real-time analytics. It is a core component of the ELK stack and is used by companies like Netflix, LinkedIn, and Uber.
  • Logstash: Logstash is an open-source data processing pipeline that ingests, transforms, and sends data from various sources to a centralized repository. It was created by Jordan Sissel in 2009 and is written in Ruby. Logstash supports a wide range of input sources, including log files, databases, and message queues. It also provides a variety of output options, such as Elasticsearch, Kafka, and Amazon S3. Logstash is highly extensible and can be customized to fit specific data processing needs.
  • Kibana: Kibana is an open-source data visualization and exploration tool that works with Elasticsearch. It allows users to interactively explore and analyze data through visualizations, dashboards, and search capabilities. Kibana was first released in 2014 and is written in JavaScript. It provides a user-friendly interface for creating and sharing visualizations, making it easier for non-technical users to derive insights from data. Kibana is widely used for monitoring, log analysis, and business intelligence purposes.
  • Beats: Beats are lightweight data shippers that send data from various sources to Elasticsearch or Logstash. They are designed to be easy to deploy and have a minimal impact on system resources. Beats can collect data from sources such as logs, metrics, and network packets. There are different types of beats available, including Filebeat for log files, Metricbeat for system and application metrics, and Packetbeat for network data. Beats are widely used for collecting and forwarding data in real-time.
  • X-Pack: X-Pack is a commercial extension for the ELK stack developed by Elastic. It provides additional features and functionality on top of the open-source components. X-Pack includes security features like role-based access control and encryption, monitoring and alerting capabilities, machine learning capabilities for anomaly detection, and graph exploration for relationship analysis. X-Pack is used by organizations that require advanced security, monitoring, and machine learning capabilities.
  • LogTrail: LogTrail is a plugin for Kibana that enhances log analysis and troubleshooting capabilities. It provides a centralized view of logs in real-time, allowing users to search, filter, and analyze logs more efficiently. LogTrail also supports custom log parsing and highlighting, making it easier to identify important information within log messages. It is a popular tool among developers and system administrators for troubleshooting and debugging applications.
  • ElastAlert: ElastAlert is an open-source tool that enables real-time alerting based on data in Elasticsearch. It allows users to define rules and conditions to trigger alerts when specific events occur. ElastAlert supports various alerting mechanisms, including email, Slack, and JIRA. It can be used to monitor system metrics, log files, security events, and other types of data stored in Elasticsearch. ElastAlert is highly flexible and customizable, making it suitable for different alerting use cases.

TOP 10 ELK stack (Elasticsearch, Logstash, Kibana) Related Technologies

  • Python

    Python is a widely-used programming language known for its simplicity and readability. It is a popular choice for ELK stack development due to its extensive libraries and frameworks that facilitate integration with Elasticsearch, Logstash, and Kibana.

  • Java

    Java is a robust and platform-independent language widely used in enterprise software development. Its strong object-oriented programming features make it suitable for building scalable and high-performance applications that leverage ELK stack capabilities.

  • JavaScript

    JavaScript is a versatile programming language primarily used for web development. It is often utilized in ELK stack projects to create interactive visualizations and dashboards with Kibana, as well as to enhance user experience across the entire stack.

  • Node.js

    Node.js is a runtime environment that allows server-side execution of JavaScript. It is commonly used in ELK stack development to create lightweight and scalable applications, especially for handling real-time data streaming and processing with Logstash.

  • React

    React is a popular JavaScript library for building user interfaces. It is frequently employed in ELK stack projects to develop responsive and dynamic visualizations within Kibana, enabling users to interact with data in a more intuitive and engaging manner.

  • Spring Boot

    Spring Boot is a Java-based framework that simplifies the development of stand-alone, production-grade applications. It is often used in ELK stack development to create robust and scalable backend services that integrate seamlessly with Elasticsearch and Logstash.

  • Go

    Go, also known as Golang, is a statically-typed language known for its efficiency and simplicity. It is gaining popularity in ELK stack development due to its concurrency features, which make it suitable for handling large volumes of data and building performant applications.

Let’s consider Difference between Junior, Middle, Senior, Expert/Team Lead developer roles.

Seniority NameYears of ExperienceResponsibilities and ActivitiesAverage Salary (USD/year)
Junior0-2 yearsAssist in developing and maintaining software applications under the guidance of senior developers. Participate in code reviews and testing activities. Contribute to the documentation and troubleshooting of software issues.$50,000 – $75,000
Middle2-5 yearsDevelop and maintain software applications independently. Collaborate with team members on larger projects. Contribute to architectural discussions and provide technical guidance to junior developers. Participate in code reviews and testing activities.$75,000 – $100,000
Senior5-10 yearsLead the development of complex software applications. Mentor junior and middle developers. Provide technical expertise and guidance to the team. Collaborate with stakeholders to gather requirements and propose technical solutions. Review and optimize code for performance and scalability.$100,000 – $150,000
Expert/Team Lead10+ yearsLead a team of developers in designing and implementing software solutions. Define and enforce coding standards and best practices. Participate in project planning and resource allocation. Drive technical innovation and keep up-to-date with industry trends. Act as a subject matter expert and provide guidance to the entire development team.$150,000 – $200,000+

TOP 13 Tech facts and history of creation and versions about ELK stack (Elasticsearch, Logstash, Kibana) Development

  • Elasticsearch, the core component of the ELK stack, was developed by Shay Banon in 2010 as an open-source search and analytics engine.
  • Logstash, another component of the ELK stack, was created by Jordan Sissel in 2010. It is a powerful tool for collecting, parsing, and storing logs for analysis.
  • Kibana, the third component, was initially released by Rashid Khan in 2013. It provides a flexible and intuitive interface for visualizing and exploring data stored in Elasticsearch.
  • The ELK stack is based on the “Elastic Stack” concept, which emphasizes the ability to easily search, analyze, and visualize data in real-time.
  • ELK is widely used for log analysis, monitoring, and data visualization in various industries, including IT, finance, healthcare, and more.
  • Elasticsearch’s distributed architecture allows it to handle large amounts of data and provide near real-time search and analytics capabilities.
  • Logstash supports over 200 plugins, allowing users to easily integrate with various data sources and customize their data pipelines.
  • Kibana offers a wide range of interactive visualizations, including charts, maps, and graphs, enabling users to explore data in a meaningful way.
  • The ELK stack has gained popularity due to its scalability, flexibility, and ease of use, making it a popular choice for organizations of all sizes.
  • In 2015, Elastic, the company behind the ELK stack, introduced Beats, lightweight data shippers that can send data from various sources directly to Elasticsearch.
  • With the release of Elasticsearch 7.0 in 2019, the ELK stack introduced a new feature called “Elasticsearch SQL,” allowing users to query data using SQL syntax.
  • Elasticsearch has an active and vibrant community, constantly contributing to its development and providing support through forums, meetups, and online resources.
  • The ELK stack has evolved over the years, with regular updates and new versions being released to introduce improvements, bug fixes, and new features.

Hard skills of a ELK stack (Elasticsearch, Logstash, Kibana) Developer

Hard skills of an ELK stack (Elasticsearch, Logstash, Kibana) Developer:


  • Experience with Elasticsearch, Logstash, and Kibana
  • Basic knowledge of data ingestion and processing using Logstash
  • Understanding of Elasticsearch querying and indexing
  • Ability to create basic visualizations and dashboards in Kibana
  • Familiarity with Elasticsearch data modeling and mapping


  • In-depth understanding of Elasticsearch, Logstash, and Kibana
  • Proficiency in Logstash configuration and pipeline development
  • Advanced Elasticsearch querying and indexing techniques
  • Ability to design and develop complex visualizations and dashboards in Kibana
  • Experience with Elasticsearch cluster setup, configuration, and optimization
  • Knowledge of Elasticsearch data analysis and aggregation
  • Understanding of Elasticsearch security and access control


  • Extensive experience with Elasticsearch, Logstash, and Kibana
  • Expertise in Logstash performance tuning and optimization
  • Advanced knowledge of Elasticsearch query DSL and search optimization
  • Ability to design and implement scalable Elasticsearch architectures
  • Experience with advanced data modeling and mapping in Elasticsearch
  • Proficiency in Kibana plugin development and customization
  • Knowledge of Elasticsearch monitoring and troubleshooting
  • Understanding of Elasticsearch data replication and sharding

Expert/Team Lead

  • Deep expertise in all aspects of the ELK stack
  • Ability to architect and lead large-scale ELK deployments
  • Experience with ELK stack integration with other systems and tools
  • Knowledge of advanced Elasticsearch features such as machine learning and anomaly detection
  • Proficiency in ELK stack performance optimization and tuning
  • Ability to mentor and guide junior and middle-level developers
  • Understanding of ELK stack best practices and industry trends
  • Strong problem-solving and troubleshooting skills
  • Excellent communication and collaboration abilities
  • Experience in managing ELK stack projects and teams
  • Demonstrated leadership and project management skills

Pros & cons of ELK stack (Elasticsearch, Logstash, Kibana)

8 Pros of ELK stack (Elasticsearch, Logstash, Kibana)

  • Scalability: ELK stack is highly scalable, allowing you to handle large volumes of data effortlessly. Elasticsearch, the core component, is designed to scale horizontally, making it suitable for enterprise-level applications.
  • Real-time Data Analysis: With ELK stack, you can perform real-time analysis on your data. Elasticsearch powers the search functionality, enabling you to search and analyze data in near real-time.
  • Centralized Log Management: Logstash, one of the components in the ELK stack, enables you to collect, process, and centralize logs from various sources. This centralized log management simplifies troubleshooting and monitoring.
  • Flexible Data Processing: Logstash provides a wide range of plugins that allow you to process data in various formats and from multiple sources. This flexibility ensures that you can adapt the ELK stack to meet your specific data processing requirements.
  • Rich Visualization: Kibana, the visualization component of ELK stack, offers a wide range of interactive visualizations, including charts, graphs, and maps. These visualizations enable you to gain meaningful insights from your data.
  • Open-source and Community Support: ELK stack is open-source, which means you have access to the source code and a vibrant community of developers. This community support ensures continuous improvement and provides assistance when you encounter issues.
  • Integration Capabilities: ELK stack can easily integrate with other tools and systems, making it a versatile solution. Whether it’s integrating with cloud platforms, databases, or monitoring tools, ELK stack offers seamless integration options.
  • Cost-effective: ELK stack being open-source, eliminates the need for expensive licensing fees. This makes it a cost-effective solution for organizations of all sizes.

8 Cons of ELK stack (Elasticsearch, Logstash, Kibana)

  • Learning Curve: The ELK stack has a relatively steep learning curve, especially for beginners. Understanding the concepts and configuring the stack may require time and effort.
  • Resource Intensive: Elasticsearch, the core component of ELK stack, can be resource-intensive, especially when handling large amounts of data. Adequate hardware resources need to be allocated to ensure smooth performance.
  • Complex Setup: Setting up and configuring the ELK stack may require advanced technical knowledge. Proper planning and expertise are necessary to ensure a successful implementation.
  • Data Security: ELK stack does not provide built-in data security features. Additional measures need to be taken to secure the data and protect it from unauthorized access.
  • Monitoring Overhead: Monitoring the ELK stack itself can impose additional overhead on system resources. Proper monitoring tools and strategies need to be in place to prevent performance degradation.
  • Dependencies: ELK stack relies on multiple components, and any failure in one component can affect the entire stack’s functionality. Regular monitoring and maintenance are necessary to ensure all components are working correctly.
  • Upgrades and Compatibility: Upgrading the ELK stack requires careful consideration of compatibility between different versions of Elasticsearch, Logstash, and Kibana. Incompatibility issues can arise during the upgrade process.
  • Support Limitations: While the ELK stack has a strong community support base, official support options may have limitations for certain versions or editions. Enterprises may need to consider commercial support for critical deployments.

Join our Telegram channel


Talk to Our Talent Expert

Our journey starts with a 30-min discovery call to explore your project challenges, technical needs and team diversity.
Maria Lapko
Global Partnership Manager