Hey there! 👋 Check out this cool video about setting up the ELK Stack with Docker Swarm Cluster! It dives into Elasticsearch, Logstash, and Kibana, showing how they team up to monitor your apps. The video breaks down each part, explaining how they work together in a Docker Swarm environment. It's great for beginners or if you're brushing up on skills. They keep things simple, so anyone can follow. By the end, you'll get how ELK Stack in a Docker Swarm can help you find awesome insights in your data. They cover what ELK is, how the components work together, setting it up in Docker Swarm, and some cool use cases. Don't forget to like and share if you find it helpful! It's perfect for upping your DevOps game.

💬 @ELKStack

Yo, ELK enthusiasts! 🦌 Check out this awesome guide for setting up the ELK Stack on AWS EC2 instances! It walks you through installing Elasticsearch, Logstash, and Kibana on separate EC2 machines. You'll learn how to install Java first (it's needed for all three), then set up each component step-by-step. The guide covers everything from adding repository keys to configuring important files like elasticsearch.yml and kibana.yml. It even shows you how to start the services and verify they're running correctly. There are some cool security tips too, like restricting access and enabling authentication. Whether you're new to ELK or just need a refresher, this guide's got you covered with clear instructions and helpful commands. It's perfect for getting your log management and analysis system up and running on AWS!

💬 @ELKStack

Elastic Stack 8.x Cookbook: Over 80 recipes to perform ingestion, search, visualization, and monitoring for actionable insights

Unlock Elastic Stack for search, analytics, security, and observability in on-premise and cloud environments.

Key Features:
- Recipes to explore Elastic Stack.
- Build search apps, analyze data, observe cloud apps.
- Use machine learning and AI.
- Free PDF eBook included.

Book Description:
Maximize Elastic Stack (ELK Stack) for real-time data ingestion, search, analysis, and visualization with practical recipes.

Learn to install, ingest data, transform data, use semantic search, create Kibana dashboards, and apply machine learning. Covers Elastic Observability for monitoring and security.

What you will learn:
- Collect data from various sources.
- Visualize data with Kibana.
- Use machine learning and AI.
- Transform and format data.
- Build search solutions.
- Explore data with data science tools.
- Monitor and manage Elastic Stack.

Who this book is for:
For all levels of Elastic Stack users, developers, and data professionals. No prior knowledge needed.

💬 @ELKStack

I invite you to a unique podcast! Imagine tools teaching themselves to you, rather than you learning them...! A special recommendation to listen and follow - because it's going to be explosive!

https://linktr.ee/visionaryxtech

We‘ll have an Amazon Web Services (AWS) + LangChain + Elastic workshop for RAG in SF next Monday. Be quick if you want to join: https://lu.ma/rag-workshop
We‘ve approved almost 200 folks by now but another 100+ on the waitlist and we‘ll need to see how many we can actually squeeze in 😅

💬 @ELKStack

Hi we able to see logs from eks cluster by using EFK

@ Linkedin

How to Install Elastic SIEM along with Auditbeat

This article provides a step-by-step guide on how to set up Elastic SIEM using Elasticsearch, Kibana, and Auditbeat to gather logs from a Linux machine. It details the installation of Elasticsearch, configuration of the Kibana dashboard, and integration of Auditbeat to collect and send system logs for real-time monitoring.

💬 @ELKStack

Elastic Stack 8.15.3 released

💬 @ELKStack

This article is about the ELK Stack, a combination of three open-source tools: Elasticsearch, Logstash, and Kibana. The stack is designed for centralized log management and data analysis, allowing organizations to collect, process, and visualize large volumes of log data. ELK Stack enables real-time insights into system performance, helps detect anomalies, and ensures application reliability. It's widely used for monitoring the health of deployed models and systems, transforming organizations' approach from reactive to proactive management. The stack's components work together seamlessly: Elasticsearch stores and indexes data, Logstash collects and processes logs, and Kibana provides visualization, allowing teams to quickly identify issues and make informed decisions based on actionable insights.


💬 @ELKStack

This article outlines a comprehensive guide to setting up a scalable ELK Stack for log management, including Elasticsearch, Logstash, and Kibana. It covers the creation of three Debian 12 virtual machines (VMs) using VirtualBox, each with specific roles for data storage in hot, cold, and frozen tiers. It provides detailed installation and configuration steps for Elasticsearch, Logstash, and Kibana, including setting up SSH, configuring Elasticsearch with secure settings, and using Index Lifecycle Management (ILM) to manage log retention. Finally, it walks through creating a Kibana dashboard for visualizing logs and data analysis, ensuring a complete end-to-end log management solution.

💬 @ELKStack

This article explains how to configure a real-time continuous monitoring system using the ELK (Elasticsearch, Logstash, Kibana) stack within a Microsoft Azure environment for SIEM (Security Information and Event Management) purposes. The setup includes two virtual machines: an ELK-Server for centralized logging and a Filebeat-VM to ship logs. It covers network configuration, ELK stack deployment, log forwarding with Filebeat, and Apache installation for generating logs. The system adheres to Zero Trust principles through network segmentation, strict security rules, and continuous monitoring, enabling real-time detection and response to security threats.

💭 @ELKStsck

6 Best Practices for Setting Up & Configuring the ELK Stack

The ELK Stack (Elasticsearch, Logstash, and Kibana) is a powerful tool for managing, analyzing, and visualizing log data. Best practices for setting it up include careful planning of log scale and infrastructure needs, optimizing Elasticsearch configurations for performance and reliability, designing efficient Logstash pipelines, creating intuitive Kibana dashboards, securing the stack through authentication and encryption, and ensuring continuous monitoring and maintenance. These steps help organizations fully leverage log data for real-time monitoring and decision-making. Tetra offers expert services to support ELK Stack deployments and optimizations.


💬 @ELKStack

🔧 Automating Server Health Checks with Python, Bash, and PowerShell

This article emphasizes the importance of automating server health checks for system administrators and DevOps engineers. It provides examples of scripts in Python, Bash, and PowerShell to automate the monitoring of critical metrics such as CPU usage, memory consumption, and disk space. The goal is to detect potential issues early and send alerts before they escalate into major problems. Automating these checks ensures consistency, saves time, and enables proactive problem detection, helping maintain server performance and uptime in modern IT infrastructures.

💬 @ELKStack

To implement Elastic Security in your Elastic Stack environment, start by enabling security features such as TLS, user authentication, and role-based access control by modifying the elasticsearch.yml configuration file. Next, set up built-in users and define roles using the Elasticsearch Users tool or the Role API. Create API keys for service-to-service authentication to ensure secure interactions between components. Encrypt communications between nodes by enabling TLS for transport security and generating the necessary certificates with elasticsearch-certutil. Configure Kibana for Security Information and Event Management (SIEM) by updating the kibana.yml file to enable security settings and ensure it connects securely to Elasticsearch. Integrate threat detection rules through the Kibana interface or API to monitor and respond to potential threats effectively. Deploy Elastic Agents on your endpoints to collect and forward security-related data for comprehensive protection. Finally, set up alerts and manage incidents using Elastic Security’s built-in features to maintain robust security operations. These steps collectively enhance the security of your IT infrastructure, providing both reactive and proactive defense mechanisms within the Elastic Stack.

💬 @ELKStack

🎬 Hear the definition of metrics from Prometheus itself! In this clip from Episode 6 of Visionaryx, when Grafana asks about the nature of metrics, Prometheus eloquently describes them as the heartbeat of systems, providing a comprehensive list of vital metrics in modern infrastructure monitoring.

Watch the full conversation and more episodes on our YouTube channel. If you enjoy our content, don't forget to subscribe to support us and stay updated with new episodes! 🎥

https://youtube.com/playlist?list=PLtlxietbu1sdKdaZUpT9dZDBCUsmmt3-7&si=9W3ylTePm7cn2pSG

#Monitoring #DevOps #SRE #Prometheus #Grafana #Observability #CloudNative #TechTalk #DevOpsMetrics #SystemMonitoring #Performance #Kubernetes #TechPodcast #EngineeringLeadership #LinkedInTech

The article explores the concept of non-human identity (NHI) in the digital realm, which includes entities like IoT devices, AI agents, and APIs that require unique digital identities. Effective NHI management is critical for security and accountability across cloud and distributed systems. One key aspect of managing NHIs involves monitoring and auditing activities to detect anomalies and prevent security breaches. Tools like Elastic Stack (ELK) are highlighted as valuable for comprehensive logging, allowing organizations to track authentication, authorization, and access patterns of NHIs, ensuring real-time visibility and enhanced security within complex digital environments.

💬 @ELKStack

This article explores the use of the ELK Stack (Elasticsearch, Logstash, and Kibana) integrated with Blue Vela to enhance monitoring of complex AI infrastructures. This combination allows organizations to monitor system performance in real-time and quickly detect issues. With log aggregation and customizable Kibana dashboards, users gain deep insights into resource utilization. Additionally, integrating Prometheus and Grafana for telemetry and Thanos for long-term data storage makes this setup a comprehensive and efficient solution for AI operations.

💬 @ELKStack

This article presents an overview of the ELK Stack (Elasticsearch, Logstash, Kibana), widely used for centralized log management and real-time analysis, essential in cybersecurity and system performance monitoring. The ELK Stack enables organizations to gather logs from multiple sources, index and search this data through Elasticsearch, structure it with Logstash, and visualize insights via Kibana's dashboards. This cohesive setup facilitates rapid incident response by detecting anomalies and collecting evidence crucial for identifying patterns, enhancing both security posture and system visibility.

💬 @ELKStack

Monitoring and Analyzing Nginx Logs with the ELK Stack

The ELK Stack, which stands for Elasticsearch, Logstash, and Kibana, is a powerful suite for managing and analyzing logs, commonly used in DevOps for real-time data analytics and centralized monitoring. Elasticsearch serves as a search and analytics engine for rapid querying of extensive datasets. Logstash functions as a data processing pipeline that gathers and transforms data from various sources, sending it onward, often to Elasticsearch. Kibana, a visualization tool, enables users to create interactive dashboards and visualizations with Elasticsearch data. The stack is highly effective for monitoring systems like Nginx by analyzing access logs in real-time. Configurations, including JSON log formatting in Nginx, file shipping with Filebeat, and data processing in Logstash, are essential steps in setting up the stack for robust monitoring and troubleshooting across distributed environments.

💬 @ELKStack

ELK POC

This repository demonstrates a proof of concept for centralized logging using the ELK Stack, with Elasticsearch for log indexing and storage, Logstash for log pre-processing, Filebeat for log collection and forwarding, and Kibana for visualization. Setup involves configuring the ELK version in .env, launching with Docker Compose, running a sample Go application to generate logs, and accessing the Kibana dashboard at http://localhost:5601 to monitor results.

💬 @ELKStack