Monitoring Cloud-Native Applications: Lead Agile Operations Confidently Using Open Source Software

✍ Scribed by Mainak Chakraborty

• Publisher: Apress
• Year: 2021
• Tongue: English
• Leaves: 253
• Edition: 1
• Category: Library

✦ Synopsis

Introduce yourself to the nuances of modern monitoring for cloud-native applications running on Kubernetes clusters. This book will help you get started with the concepts of monitoring, introduce you to popular open-source monitoring tools, and help with finding the correct set of use cases for their implementation. It covers the in-depth technical details of open-source software used in modern monitoring systems that are tailor made for environments running microservices.

Monitoring Cloud-Native Applications is divided into two parts. Part 1 starts with an introduction to cloud-native applications and the foundational concepts of monitoring. It then walks you through the various aspects of monitoring containerized workloads using Kubernetes as the de-facto orchestration platform. You will dive deep into the architecture of a modern monitoring system and look at its individual components in detail.

Part 2 introduces you to popular open-source tools which are used by enterprises and startups alike and are well established as the tools of choice for industry stalwarts. First off, you will look at Prometheus and understand its architecture and usage. You will also learn about InfluxDB, formerly called TICK Stack (Telegraf, InfluxDB, Chronograf, and Kapacitor). You will explore the technical details of its architecture and the use cases which it solves. In the next chapter, you will be introduced to Grafana, a multi-platform open source analytics and interactive visualization tool that can help you with visualization of data and dashboards.     

After reading this book, you will have a much better understanding of key terminologies and general concepts around monitoring and observability. You will also be able to select a suitable monitoring solution from the bouquet of open-source monitoring solutions available for applications, microservices, and containers. Armed with this knowledge, you will be better prepared to design and lead a successful agile operations team.

What You Will Learn

Monitor and observe of metrics, events, logs, and traces

Carry out infrastructure and application monitoring for microservices architecture

Analyze and visualize collected data

Use alerting, reporting, and automated actions for problem resolution

Who This Book Is For

DevOps administrators, cloud administrators, and site reliability engineers (SREs) who manage and monitor applications and cloud infrastructure on a day-to-day basis within their organizations.

✦ Table of Contents

Table of Contents
About the Authors
About the Technical Reviewer
Introduction
Part I: Architecture of Modern Monitoring Systems for Cloud Native Applications
Chapter 1: Introduction to Modern Monitoring
Microservices
Containers
Monitoring
Importance of Monitoring
DevOps—Roles and User Personas
Monitoring Domains
Reactive vs. Proactive Monitoring
Monitoring System
Need for a Monitoring System
Features of a Modern Monitoring System
Push vs. Pull Monitoring
Advent of AIOps
Kubernetes
Summary
Chapter 2: Observability
Observability
Three Pillars of Observability
Metrics
Time Series
Granularity/Resolution
Metadata Tags
Categories of Metrics
Work Metrics
Resource Metrics
Methods of Measurement
USE Method
RED Method
Four Golden Signals
Types of Metrics
Gauges
Counters
Timers
Histograms
Summary
Statistical Functions
Events
Observability of Kubernetes
Sources of Metrics in Kubernetes
Kubernetes API Server
cAdvisor
Kubernetes Metrics Server
Kube-State-Metrics
Kubernetes Internal Metrics
Operations in a Kubernetes Environment
Chapter 3: Architecture of a Modern Monitoring System
Modern Monitoring System Architecture
Data Collection
Instrumenting Your Code
Exposition
Bridges
Parsers
Third-Party Exporters
Agents
collectd
StatsD
Telegraf
fluentd
OpenTelemetry
OpenTelemetry Collector
OpenTelemetry Collector Architecture
Agent
Gateway
Open Telemetry Agent
Data Storage
LSM-Tree
Time-Series Data
TSDB
Time-Series Data Models
Modeling by Data Source
Modeling by Metrics
Data Analysis and Query Engine
Filter
Aggregation
Grouping
Downsampling
Auto-rollup
Data Visualization
Line Graphs
Stacked Graphs
Bar Graphs
Heatmaps
Summary Graphs
Aggregation
Alerting Engine
Alerting Strategy
Features of a Modern Alerting System
Log Aggregation
Log Aggregation Architecture
Ingestion Pipeline
Logging in a Kubernetes Environment
Best Practices for Logging
Summary
Part II: Open Source Monitoring Tools
Chapter 4: Prometheus
Installation
Architecture
Data Collection
Exposition Format
Service Discovery
Targets
Data Storage
Visualization
Alerting
Grouping
Routing
Inhibition
Silences
Chapter 5: TICK Stack
Installation
Key Concepts in InfluxDB
Organization
Creating an Organization
Renaming an Organization
Deleting an Organization
Members
Creating a New User
Updating a Username
Removing a Member
Deleting a User
Buckets
Data Collection
Scraper
Telegraf
Telegraf Installation
Manual Telegraf Configuration
Data Storage
InfluxDB Data Elements and Schema
Tables
Line Protocol
Influx Query Language
Alerting
Configuring a Check
Setting Thresholds
Connecting to a Notification Endpoint
Visualization
Summary
Chapter 6: Grafana
Installation
Adding a Data Source
Creating a Dashboard
Panels
Panel Editor
Visualization
Stat
Gauge
Bar Gauge
Display Settings
Dashboards
Dashboard Header
Rows
Manage Dashboards
Dashboard Folder
Playlists
Explore
Alerting
State History
Test Rule
Adding a Notification Channel
Summary
Index