Vector calculus, linear algebra, and differential forms, instructor's solution manual ( incomplete)

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 Description Get 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. Cover Title Page Copyright and Credits Contributors Table of Contents Preface Part 1 – Getting Started with Grafana Chapter 1: Introducing Data Visualization with Grafana Technical requirements Appreciating data and visualization Storing, retrieving, and visualizing data Why Grafana? Exploration Analysis Presentation Observability Choosing Grafana Installing Grafana Grafana in a Docker container Make and Makefile Grafana for macOS Grafana for Linux Grafana for Windows Grafana Cloud Connecting to the Grafana server Summary Further reading Chapter 2: Touring the Grafana Interface Technical requirements Exploring Grafana—the Home dashboard Introducing the Grafana search bar Grafana logo Organization menu Search box + (add) menu Help Grafana blog User menu Expanding Grafana’s main menu Home Starred Dashboards Explore Alerting Connections Administration Exploring the Grafana dashboard UI Grafana dashboard title bar Dashboard content Summary Chapter 3: Diving into Grafana's Time Series Visualization Touring the Grafana panel UI Creating a simple data source Creating a graph panel Generating data series in the Query tab What is a query? Query tab features Duplicating an existing query Transform Editing the panel settings Selecting panel visualizations The Panel options section The Tooltip section The Legend section The Axis section The Graph styles section The Standard options section The Data links section The Value mappings section The Thresholds section Monitoring with the Alert tab Further exploration Summary Part 2 – Real-World Grafana Chapter 4: Connecting Grafana to a Prometheus Data Source Technical requirements Installing the Prometheus server Installing Prometheus from Docker Configuring the Prometheus data source Exploring Prometheus Using Explore for investigation Configuring Grafana metrics Querying the Prometheus data source Typing in a metrics query Querying for process metrics Querying for memory metrics Detecting trends with aggregations Applying aggregations to our query data Understanding the data source limitations Querying limits for series aggregations Querying limits for time aggregations Exploring data source dashboards Summary Chapter 5: Extracting and Visualizing Data with InfluxDB and Grafana Technical requirements Making advanced queries Launching server Docker containers Writing the ETL script Running the script Setting up an InfluxDB database Configuring the InfluxDB data source Understanding the time series data visualization Displaying time-aggregated data Debugging queries with Query inspector Observing time interval effects Setting the minimum interval Setting the axis Setting axis units Converting temperature into Fahrenheit Autoscaling the Y axis Dual y axis display Working with legends Setting legend contents Enabling legend aggregations Summary Chapter 6: Shaping Data with Grafana Transformations About Grafana DataFrames and transformations Exploring the various transformation functions Installing the TestData data source Selecting transformations Adding fields Modifying fields Filtering results Reducing rows Combining tables Expanding analysis with a transformation Chaining transformations into a visualization pipeline Limitations of transformations Summary Chapter 7: Surveying Key Grafana Visualizations Technical requirements Launching server Docker containers Setting up the InfluxDB database Initializing the InfluxDB server Generating an API token Configuring the InfluxDB data source Building the Python Docker container Loading the data Reviewing the table visualization Comparing aggregations Overriding field settings Setting a display name Introducing the stat visualization Creating a stat visualization panel Setting stat styles Defining value mappings in a stat visualization Adding visual interest with a gauge Exploring the gauge options Setting the threshold values and colors Going linear with a bar gauge Exploring the bar gauge settings Building a bar gauge Summary Chapter 8: Surveying Additional Grafana Visualizations Technical requirements Launching server Docker containers Setting up the InfluxDB database Initializing the InfluxDB server Generating an API token Configuring the InfluxDB data source Building the Python Docker container Exploring spatial data with the Geomap visualization Ingesting a new earthquake dataset Mapping earthquake data with the Geomap visualization Displaying category data with a bar chart visualization Understanding histograms Producing histograms with transformations Displaying histogram data with the bar chart visualization Visualizing histogram data over time with the heatmap Summary Chapter 9: Creating Insightful Dashboards Technical requirements Launching server Docker containers Setting up the InfluxDB database Designing a dashboard Conveying information Determining the visual context Prioritizing elements of importance Creating a high information-density dashboard Ingesting the weather data Designing the dashboard Adding the first row Adding the second row Adding the third row Adding the fourth row Adding the fifth row Creating a high-information visibility dashboard Designing the dashboard Ingesting the earthquake data Adding the first row Adding the second row Adding the third row Parting thoughts Considering layout Automating ingestion Summary Chapter 10: Working with Advanced Dashboard Features and Elasticsearch Technical requirements Building the data server Connecting Grafana to Elasticsearch Querying with Elasticsearch Creating a template variable Adding template variables to the graph panel Templating additional variables Creating ad hoc filters Repeating rows and panels with template variables Creating a new dashboard Setting up the template variables Configuring the panels Linking dashboards Adding dashboard tags Locking down a template variable Creating dashboard links Annotating dashboards Annotating the graph panel Querying tagged annotations Creating Elasticsearch annotation queries Sharing dashboards Sharing dashboard links Sharing dashboards by exporting Sharing dashboard snapshots Summary Chapter 11: Streaming Real-Time IoT Data from Telegraf Agent to Grafana Live Technical requirements Streaming real-time data from Telegraf to Grafana Setting up Grafana for streaming Installing the Telegraf agent Configuring the Telegraf agent Running Telegraf Streaming IoT data with MQTT and Mosquitto Describing the pipeline architecture Configuring the Telegraf MQTT consumer Installing the Mosquitto broker Generating messages to an IoT data pipeline Examining the simulated metrics data Reviewing the mqtt_pub.py script Running the mqtt_pub.py script Exploring the IoT data Summary Chapter 12: Monitoring Data Streams with Grafana Alerts Technical requirements Monitoring and observability Monitoring processes Monitoring system resources Monitoring applications Capturing metrics for alerting Alerting in Grafana Alert rules Labels Notification policies Contact points Defining alert rules What condition... What metrics... How long... Monitoring systems Monitoring applications Alert messaging to contact points Configuring an email contact point Configuring a PagerDuty contact point Configuring a Slack contact point Routing alerts with notification policies Specific routing Mute timings On your own Summary Chapter 13: Exploring Log Data with Grafana’s Loki Technical requirements Loading system logs into Loki Networking our services Installing Promtail Installing Loki Launching Grafana Creating a Loki data source Visualizing Loki log data with Explore Simulating logs with flog Configuring promtail Promtail in Docker Compose Alternative Docker log capture Querying logs and metrics with Explore Summary Part 3 – Managing Grafana Chapter 14: Organizing Dashboards and Folders Managing dashboards and folders Naming a dashboard Dashboard naming tips Working with dashboard folders Tips to manage dashboard folders Starring and tagging dashboards Marking dashboards as favorites Tagging dashboards Building and running dashboard playlists Creating a playlist Displaying a playlist Displaying playlists in normal mode Displaying playlists in TV mode Displaying playlists in Kiosk mode Displaying playlists with auto fit panels Editing a playlist Exploring the Dashboard list panel Setting Dashboard list panel options Duplicating dashboards Internal dashboard duplications External dashboard duplications Summary Chapter 15: Managing Permissions for Users, Teams, and Organizations Understanding key permission concepts Organizations Users Roles Teams Adding users Adding users – by invitation only Adding users – a self-service model Setting permissions Setting organization roles Setting folder permissions Setting dashboard permissions Establishing teams Setting up a team Permission rules Administering users and organizations Managing users Organization admin and Super Admin roles Managing organizations Summary Chapter 16: Authenticating Grafana Logins Using LDAP or OAuth 2 Providers Authenticating with OpenLDAP Setting up an OpenLDAP server Configuring Grafana to use LDAP Securing the bind password Testing the Grafana configuration Adding a user to OpenLDAP Looking up a user in Grafana Authenticating with OAuth 2 GitHub OAuth 2 authentication Google OAuth 2 authentication Authenticating with Okta Summary Chapter 17: Cloud Monitoring AWS, Azure, and GCP Configuring an AWS CloudWatch data source Creating the policy Creating the user Configuring a new Grafana connection for AWS CloudWatch Configuring a Microsoft Azure Monitor data source Registering the Grafana application Setting the application role Generating application secrets Configuring a new Grafana connection for Azure Monitor Configuring Azure Log Analytics Configuring a GCM data source Enabling a Google Cloud API Creating a Google service account Configuring a new Grafana connection for GCM Summary Index Other Books You May Enjoy