About Elastic Stack (Elasticsearch, Logstash, Kibana)
The ELK Stack and Splunk are two widely used platforms in data analytics and management. Although the tools serve similar purposes, key differences set them apart.This article presents ELK Stack vs. Splunk - the ultimate comparison to help you choose the right platform.ELK Stack vs. Splunk: DefinitionsThe ELK Stack (now known as the Elastic Stack) and Splunk are powerful tools for collecting, analyzing, and visualizing machine data.Both platforms offer robust solutions for log management, security analysis, compliance monitoring, and business analytics and provide a range of features, user-friendly interfaces, and scalable architecture. While both platforms serve similar purposes, distinctions exist.What is ELK Stack?The Elastic Stack is an open-source toolset that collects, searches, and visualizes large volumes of machine data. It's flexible and suitable for various use cases. Initially, the stack consisted of Elasticsearch, Logstash, and Kibana (ELK), but then Beats was added:Elasticsearch. A search and analytics engine that enables fast and scalable full-text searching, real-time analytics, and data visualization. It acts as a NoSQL database built on Apache Lucene.Logstash. A data processing and transportation pipeline that collects, parses, and transforms logs from various sources before indexing the data in Elasticsearch.Kibana. A user-friendly visualization dashboard that facilitates exploration, analysis, and report generation based on the indexed data stored permanently in Elasticsearch.Beats. Local data collectors that gather and send data from different sources to Elasticsearch or Logstash. Beats are resource-friendly and suitable for deployment on various systems, including servers, containers, and edge devices. However, the data is sometimes collected only by Logstash
Key features of the Elastic Stack (Elasticsearch, Logstash, Kibana) that are enabled through these drivers include:
- ELI5: Elasticsearch, Kibana and Logstash (and Beats) : r/elastic
- How to Set Up Elasticsearch, Logstash, and Kibana (Elastic
- Cara Instalasi Elasticsearch, Logstash, dan Kibana (Elastic
- Comment installer Elasticsearch, Logstash et Kibana (Elastic
- Installieren von Elasticsearch, Logstash und Kibana (Elastic
- Elastic (Elastic Stack: Elasticsearch, Kibana, Logstash
- Elastic Stack (Elasticsearch, Logstash, Kibana)
Easier to use. One such improvement is the ability to generate alerts based on endpoint CPU and RAM usage.Other Endpoint improvements and bug fixes include increasing the maximum number of Endpoints per test to 65,000 and a network Sankey diagram that now shows all network devices by default. There are also additional improvements aimed at making it easier to view and act on your Endpoint data efficiently.ELK Stack (Elasticsearch, Logstash, and Kibana) IntegrationWe have an extensive list of integrations and we’re happy to announce that ELK stack is now joining our ecosystem of technical partners.As anyone working with it knows, [ELK Stack]( stack&gclid=EAIaIQobChMI-Nva7YW98gIVzNvVCh2RewchEAAYASAAEgIOEfD_BwE) is a fantastic way to help process big data. It’s a distributed, free, and open search and analytics engine for all types of data, including textual, numerical, geospatial, structured, and unstructured. It comprises three open-source products: Elasticsearch, Logstash, and Kibana.With Hercules, we are excited to be introducing two methods of integration with ELK Stack:Catchpoint pushes data to ELK Stack – This method uses Catchpoint's Test Data Webhook API to send data directly to Elasticsearch. Each time a Catchpoint test runs with the Test Data Webhook enabled, the results are pushed to Elasticsearch via a public-facing endpoint accessible over http or https.ELK Stack pulls data from Catchpoint – This integration relies on Logstash to pull test data from Catchpoint’s REST API. Logstash dynamically ingests and transforms the data using csv filters, and then ships it to the Elasticsearch engine.Once Elasticsearch has received the Catchpoint data by either method, you can apply visualizations and perform data analysis using Kibana.Octopus Deploy IntegrationOctopus Deploy is an automated deployment and release-management tool used by leading continuous-delivery teams worldwide. We’re happy to let you know that DevOps teams can now configure Octopus Deploy to register each successful deployment as an Event in Catchpoint. This adds a marker in the Catchpoint Portal so that you can see how changes to your application correlate with changes in the user experience.Learn More TodayIf you are interested in testing out Catchpoint, check out our Guided Test Drive.This is some text inside of a div block.
