Elastic
Enterprise SIEM and log management
All data at a glance
With Elastic, we provide you with an open source platform that allows you to search and analyze large amounts of data in real time. We use it to create powerful search functions for your applications, visualize data and monitor systems to give you a complete overview
Related products & services
Elastic features
Real-time analysis
With Elasticsearch, we help you to search through large volumes of structured and unstructured data and analyze it in near real time. Elastic enables fast, precise full-text searches and supports complex queries via a RESTful API. This allows you to identify data patterns, analyze trends and make informed decisions based on your data.
Visualization and dashboards
By using Kibana, we offer you the opportunity to visually analyze your data and create interactive dashboards. You can create reports, charts and maps that present your data in an understandable way. This function gives you real-time insights and allows you to monitor the performance of your systems or identify business trends.
Collecting and processing data
With Beats and Logstash, you can collect and process data from various sources and forward it to Elasticsearch. Beats is a lightweight data collection platform, while Logstash offers powerful ETL functionalities for data processing. These tools help you to efficiently process a wide range of data – from logs to metrics – and store it centrally for subsequent analysis.
Elastic web interface
The screenshot shows an overview of the Elastic web interface, in which the various components and functions of the dashboard are clearly explained.
Quick navigation between individual dashboards.
Visualize your log data in tabular form or with a variety of graphical views.
Get a quick overview of which systems are part of the view.
Get quick access to your log information with detailed information.
Adjust the time period for the information displayed quickly and with just a few clicks.
Use a simple query language with auto-complete functions to quickly filter for specific fields and content.
Elastic Consulting
We help you with the design, installation and integration of Elastic in your environment – for more power, know-how and peace of mind!
Power
We have been successfully supporting our customers in the operation of their IT infrastructures for many years. Whether it’s different industries, tools or operating systems – we’ve seen, operated and built it all. With extensive experience in best practices around Grafana, Prometheus, InfluxDB and other open source technologies, especially in the Linux environment, we are at your side with our know-how.
Know-how
We not only understand your IT systems and services, but also the big picture – the numerous aspects that make up the operation of complex IT infrastructures. In a world where IT is becoming increasingly complex and constantly changing, there is often a lack of time and personnel. This is exactly where we come in to provide you with optimum support.
Targeted reinforcement
As Linux generalists and open source experts, we are broadly positioned and deeply networked in the open source communities. With us by your side, you are never alone! Whether as an IT consultant, engineer, support or architect – we strengthen your team, relieve you and take over the work so that you can concentrate on the essentials.
Elastic training
Learn real-time data processing and visualization with the Elastic Stack
Get an introduction to the Elastic Stack in our Elastic Stack training and learn the basic techniques of log transfer, processing, storage, evaluation and analysis!
Know-how
More know-how about Elastic
Infrastructure as Code (IaC): Grundlagen, Geschichte und Praxis mit Ansible und GitLab
Introduction The way in which IT infrastructure is provided and operated has changed significantly in recent decades. In the early years of system administration, everyday…
Observability vs Monitoring
The term observability is on everyone’s lips and is often touted as a modern solution to dusty old, static monitoring. All manufacturers offer it, all…
Icinga Web Module for Performance Data Graphs
After we forked the Grafana module for Icinga Web last year, we thought about whether there are other ways to graphically display Icinga performance data…
The Icinga Web Grafana module has found a new home
We are happy to announce that the Icinga Web Grafana module has found a new home! Originally developed by Carsten (Mikesch-mp), this module is a…
Katello as a package mirror for Icinga
This article is about setting up Katello as a package mirror for Icinga. Specifically, Icinga for Windows, Debian / Ubuntu, Red Hat Enterprise Linux and…
NIS 2 – The current status in January 2025
Since its adoption, the EU Directive NIS 2 (Network and Information Security Directive 2) has been a central element of the European cyber security strategy.…
Show users in MySQL
In MySQL, user management plays a crucial role in making database access secure and efficient. But how do you display existing users? In this blog…
Icinga 2 Security Release – November 2024
Critical error in the Icinga 2 core Today, November 12, 2024, the Icinga team has released a security fix that is classified as CRITICAL. The…
Data collection with the Support Collector
Last updated: 22.11.2024 What is the Support Collector and how does it work? The Support Collector offers an easy way to automatically record all important…
Questions & Answers
The most frequently asked questions about Elastic:
Who uses Elasticsearch?
Elasticsearch is used by companies and organizations that need to search and analyse large amounts of data quickly, such as in the area of log management, business analytics or for search functions on websites. Companies such as Netflix, Uber and Wikipedia use Elasticsearch to enable real-time searches in their applications. Development teams and data engineers also use it to efficiently search and visualize structured and unstructured data.
Is Elasticsearch a database?
Elasticsearch is not a classic relational database, but a search and analysis engine based on the open source software Apache Lucene. It is specially designed to quickly search and analyze large volumes of text-based and unstructured data in real time. Although Elasticsearch offers some database-like features such as data storage and retrieval, the focus is on powerful full-text search and analysis, not complex relational queries.
What is an Elasticsearch index?
An Elasticsearch index is a structure used to store, organize and manage data within Elasticsearch, similar to a database in traditional database systems. Each index consists of documents, which in turn contain fields with different data types. Indexes enable the quick search and analysis of stored data by saving and organizing it in segmented and distributed formats.
What is the Elastic Stack?
The Elastic Stack, formerly known as the ELK stack, consists of Elasticsearch, Logstash, Kibana and Beats, which together provide a powerful platform for search, analysis and visualization. Logstash processes and forwards data to Elasticsearch, where it is stored and searched, while Kibana visualizes this data in dashboards. Beats are lightweight data collectors that gather information from servers or applications and transfer it to the Elastic Stack.
What can I do with Elasticsearch?
With Elasticsearch, you can search and filter large amounts of data at lightning speed, such as log files, text documents or metadata. You can perform complex analyses on this data in real time to identify patterns, trends or anomalies. Elasticsearch can also be used to implement customized search functions for websites or applications that deliver relevant results immediately.
What is Elastic Beats?
Elastic Beats is a lightweight data collection and delivery platform that is part of the Elastic Stack. Beats consists of various agents that collect specific data sources such as logs, metrics or network data and send them to Elasticsearch or Logstash. This enables Beats to efficiently record and forward data in order to analyze or visualize it in real time.
What is an Elasticsearch Cluster?
An Elasticsearch cluster consists of multiple Elasticsearch nodes that work together to store, search and analyze large amounts of data. Each node takes on a specific role, such as storing data or processing queries, and all nodes share the load to increase efficiency. A cluster enables scalability and redundancy so that it continues to function reliably even if individual nodes fail.
What does Elasticsearch do?
Elasticsearch searches and analyzes large amounts of data at lightning speed by indexing data and making it accessible in real time. It processes both structured and unstructured data and offers powerful full-text search, filters and aggregations. In addition, Elasticsearch enables the creation of customized search solutions and analyses for applications, log management and business intelligence.
Why Elasticsearch?
Elasticsearch is a powerful, distributed search and analysis engine that has been specially developed for fast full-text search and data analysis in large amounts of data. It is based on Lucene and offers a scalable and flexible architecture that makes it possible to access structured and unstructured data in real time. Typical use cases include searching log files, indexing text content and providing fast, relevant search results in web applications.