Elastic

Log & event management

Enterprise Open Source Search & Logging. Search and analyze your data in real time – logs, metrics, security events and full-text search. Everything in one stack, built for you by specialists.

Our offer

From the idea to the running stack

You don’t have to build Elastic alone. We accompany you step by step – and stay by your side afterwards.

Step 1

Analysis & concept

We look at your data sources and infrastructure and plan together which logs, metrics and data should be indexed. We know the pitfalls from hundreds of projects - this is how you avoid a sprawling data volume and a cluster that collapses under the load.

Step 2

Structure & integration

We set up clusters, index structures, ingest pipelines and Kibana dashboards precisely for your teams and systems. Well thought-out data mapping saves you expensive re-indexing later on - we rely on a structure that scales with your data growth right from the start.

Step 3

Commissioning & visualization

Your stack goes live, data flows in in real time and becomes visible in meaningful dashboards. In this way, you can avoid data graves in which nobody can find anything - relevant information is immediately searchable and understandable at a glance.

Step 4

Support & Operation

On request, we can take over ongoing operations completely (outsourcing) or support your team with support and training. Cluster updates, shard management and availability cost a lot of time internally - we keep your stack performant and stable so that you can concentrate on analyzing your data.

Elastic features

Turn raw logs and mountains of data into usable knowledge: Elastic makes your data searchable, visible and analyzable in real time – whether for troubleshooting, security or well-founded decisions.

Real-time analysis

Search and analyze huge amounts of structured and unstructured data almost in real time – with precise full-text searches instead of long waits for results.

Visualization and dashboards

Kibana turns your data into interactive dashboards, diagrams and maps – complex relationships become understandable at a glance.

Consolidate data centrally

With Beats and Logstash, you can collect logs and metrics from all sources and bring them together in one place – no more scattered data silos.

Safety at a glance

Suspicious patterns and anomalies stand out immediately. This allows you to use Elastic as the basis for your SIEM and detect security incidents before they become a problem.

Scaled with your data

From individual nodes to distributed clusters: Elastic grows with your data volume and remains reliable thanks to redundancy, even if individual nodes fail.

Fast troubleshooting

Instead of digging through log files, you can find the right information in seconds with a simple query language and auto-complete – and solve problems faster.

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.

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Start small, make clear progress

You don’t have to start a big project right away. Choose the entry point that suits your situation – each step provides you with a concrete result.

Elastic Review

Are you already using Elastic? We'll look at it together and show you where it's stuck.

plus Value added tax2.000 €*

Analysis of your existing clusters & architecture
Review of performance, shard strategy and index lifecycle
Check your ingest pipelines and mappings
Concrete, prioritized recommendations for action
Joint discussion of the results with your team
Our approach: In a joint day with you, we discuss the open issues, work out our recommendations and finally present the results to you.
Your result: A clear to-do list that lets you know exactly where things are stuck and what needs to be done next.

Strategy workshop

Together we will clarify which data you want to analyze and the best way to do this.

plus Value added tax4.000 €*

Recording your requirements, goals and framework conditions
Evaluation of your current data and logging landscape
Architecture recommendation suitable for your environment (sizing, hot/warm/cold)
Tooling recommendation (Elastic & useful additions such as Beats, Logstash)
Concrete implementation roadmap with next steps
Our approach: In a joint day with you, we discuss the open topics, create the roadmap for your environment and then present the results to you in detail.
Your result: a resilient plan that your team can use to tackle implementation immediately and without detours.

Proof of concept

We set up an initial executable search and log environment with you - for you to touch.

plus Value added tax8.000 €*

Set up a test environment with real data from your systems
Setting up the first Kibana dashboards for an overview
Configuration of a functioning search and alerting logic
Integration of an exemplary data source (e.g. logs or metrics)
Knowledge transfer and training of your team on the environment
Our approach: In a joint day with you, we discuss the open topics, create a PoC (in cooperation with you) and finally present the result to you.
Your result: A functioning demo environment as a tangible basis for the decision and the subsequent real system.

*If the appointments take place on site, the travel costs valid at the time the order is placed will also be charged.

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!

Learn more

Know-how

More know-how about Elastic

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.

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