Loki Log
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Operational Loki for Log Aggregation
"Operational Loki for Log Aggregation" "Operational Loki for Log Aggregation" is a comprehensive and authoritative guide for engineers, architects, and SREs looking to master log aggregation with Grafana Loki. The book delves into modern log aggregation architectures, contrasting centralized, distributed, and event-driven models, while providing an in-depth exploration of Loki’s microservices architecture, labeling strategies, and unique operational workflows. Readers are equipped with a solid foundation in data modeling, ingestion paradigms, and an insightful comparison of Loki with other leading log stacks such as ELK and PLG, ensuring a clear understanding of the evolving standards and best practices in log management. This volume provides actionable blueprints for Loki deployment across diverse environments, including Kubernetes, Docker, cloud-native platforms, and traditional bare metal. Covering topics from high availability, infrastructure automation using tools like Terraform and Helm, to advanced scaling and migration strategies, the book is a complete lifecycle manual. Extensive treatment is given to log collection pipelines, including Promtail and alternative agents, performance tuning, security considerations, compliance, and end-to-end governance, empowering readers to build robust, secure, and highly available log aggregation systems. Beyond technical implementation, "Operational Loki for Log Aggregation" explores advanced querying with LogQL, operational monitoring, alerting, and observability, along with extensibility through custom plugins, machine learning, and real-time event workflows. Case studies of large-scale deployments, incident retrospectives, and forward-looking trends offer practical insights and strategic guidance. Whether integrating with SIEM systems, supporting multi-tenancy, or preparing for edge and serverless futures, this book is an indispensable resource for organizations committed to operational excellence and a culture of observability.
Modern Network Observability
Learn how to use modern monitoring tools for building network observability solutions that enhance operations and promote an effective automation strategy, with step-by-step guidance and practical examples Key Features Craft a dynamic observability stack with real-world, practical applications Build intuitive dashboards and alerts by collecting and normalizing diverse network data Leverage observability data to strengthen automation strategies for network operations Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAs modern IT services and software architectures such as microservices rely increasingly on network performance, the relevance of networks has never been greater. Network observability has emerged as a critical evolution of traditional monitoring, providing the deep visibility needed to manage today’s complex, dynamic environments. In Modern Network Observability, authors David Flores, Christian Adell, and Josh VanDeraa share their extensive experience to guide you through building and deploying a flexible observability stack using open-source tools. This book begins by addressing the limitations of monolithic monitoring solutions, showing you how to transform them into a composable, flexible observability stack. Through practical implementations, you’ll learn how to collect, normalize, and analyze network data from diverse sources, build intuitive dashboards, and set up actionable alerts that help you stay ahead of potential issues. Later, you’ll cover advanced topics, such as integrating observability data into your network automation strategy, ensuring your network operations align with business objectives. By the end of this book, you'll be able to proactively manage your network, minimize downtime, and ensure resilient, efficient, and future-proof operations.What you will learn Collect and normalize data from various sources using Telegraf and Logstash Enrich operational data with crucial context from a Source of Truth such as Nautobot Visualize data and create insightful dashboards with Grafana Automate alerts and responses for your network operations strategy using Prefect Understand when to build or buy an observability stack, with tips and best practices Explore practical machine learning techniques to enhance observability data value Who this book is for This book is for all network engineering roles such as network analysts, administrators, architects, security personnel, support staff, and managers working in both on-premises and cloud environments who are tasked with implementing or using network monitoring solutions. Basic programming knowledge in Python and Go, familiarity with networking concepts, and a fundamental understanding of Docker containers for lab scenarios will be required.
Learn Grafana 10.x
Author: Eric Salituro
language: en
Publisher: Packt Publishing Ltd
Release Date: 2023-12-20
Get up and running with building data pipelines and creating interactive dashboards to visualize, monitor, and present a wide variety of time-series data with this comprehensive introductory guide Key Features Install, set up, and configure Grafana for real-time data analysis, visualization, and alerting Visualize and monitor data using data sources such as InfluxDB, Telegraf, Prometheus, and Elasticsearch Explore Grafana's cloud support with Microsoft Azure, Amazon CloudWatch, and Google Cloud Monitoring Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGet ready to unlock the full potential of the open-source Grafana observability platform, ideal for analyzing and monitoring time-series data with this updated second edition. This beginners guide will help you get up to speed with Grafana’s latest features for querying, visualizing, and exploring logs and metrics, no matter where they are stored. Starting with the basics, this book demonstrates how to quickly install and set up a Grafana server using Docker. You’ll then be introduced to the main components of the Grafana interface before learning how to analyze and visualize data from sources such as InfluxDB, Telegraf, Prometheus, Logstash, and Elasticsearch. The book extensively covers key panel visualizations in Grafana, including Time Series, Stat, Table, Bar Gauge, and Text, and guides you in using Python to pipeline data, transformations to facilitate analytics, and templating to build dynamic dashboards. Exploring real-time data streaming with Telegraf, Promtail, and Loki, you’ll work with observability features like alerting rules and integration with PagerDuty and Slack. As you progress, the book addresses the administrative aspects of Grafana, from configuring users and organizations to implementing user authentication with Okta and LDAP, as well as organizing dashboards into folders, and more. By the end of this book, you’ll have gained all the knowledge you need to start building interactive dashboards.What you will learn Learn the techniques of data visualization using Grafana Get familiar with the major components of Time series visualization Explore data transformation operations, query inspector, and time interval settings Work with advanced dashboard features, such as annotations, variable-based templating, and dashboard linking and sharing Connect user authentication through Okta, Google, GitHub, and other external providers Discover Grafana’s monitoring support for cloud service infrastructures Who this book is for This book is for business intelligence developers, business analysts, data analysts, and anyone interested in performing time-series data analysis and monitoring using Grafana. You’ll also find this book useful if you’re looking to create and share interactive dashboards or get up to speed with the latest features of Grafana. Although no prior knowledge of Grafana is required, basic knowledge of data visualization and some Python programming experience will help you understand the concepts covered in the book.