Splunk 7 essentials :: demystify machine data by leveraging datasets, building reports, and sharing powerful insights /
Transform machine data into powerful analytical intelligence using Splunk Key Features Analyze and visualize machine data to step into the world of Splunk! Leverage the exceptional analysis and visualization capabilities to make informed decisions for your business This easy-to-follow, practical boo...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham, UK :
Packt Publishing,
2018.
|
| Ausgabe: | Third edition. |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | Transform machine data into powerful analytical intelligence using Splunk Key Features Analyze and visualize machine data to step into the world of Splunk! Leverage the exceptional analysis and visualization capabilities to make informed decisions for your business This easy-to-follow, practical book can be used by anyone - even if you have never managed data before Book Description Splunk is a search, reporting, and analytics software platform for machine data, which has an ever-growing market adoption rate. More organizations than ever are adopting Splunk to make informed decisions in areas such as IT operations, information security, and the Internet of Things. The first two chapters of the book will get you started with a simple Splunk installation and set up of a sample machine data generator, called Eventgen. After this, you will learn to create various reports, dashboards, and alerts. You will also explore Splunk's Pivot functionality to model data for business users. You will then have the opportunity to test-drive Splunk's powerful HTTP Event Collector. After covering the core Splunk functionality, you'll be provided with some real-world best practices for using Splunk, and information on how to build upon what you've learned in this book. Throughout the book, there will be additional comments and best practice recommendations from a member of the SplunkTrust Community, called "Tips from the Fez". What you will learn Install and configure Splunk for personal use Store event data in Splunk indexes, classify events into sources, and add data fields Learn essential Splunk Search Processing Language commands and best practices Create powerful real-time or user-input dashboards Be proactive by implementing alerts and scheduled reports Tips from the Fez: best practices using Splunk features and add-ons Understand security and deployment considerations for taking Splunk to an organizational level Who this book is for This book is for the beginners who want to get well versed in the services offered by Splunk 7. If you want to be a data/business analyst or want to be a system administrator, this book is what you want. No prior knowledge of Splunk is required |
| Beschreibung: | 1 online resource (1 volume) : illustrations |
| Bibliographie: | Includes bibliographical references. |
| ISBN: | 9781788830126 1788830121 |
Internformat
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| 100 | 1 | |a Contreras, J-P, |e author. | |
| 245 | 1 | 0 | |a Splunk 7 essentials : |b demystify machine data by leveraging datasets, building reports, and sharing powerful insights / |c J-P Contreras, Erickson Delgado, Betsy Page Sigman. |
| 246 | 3 | |a Splunk seven essentials | |
| 250 | |a Third edition. | ||
| 264 | 1 | |a Birmingham, UK : |b Packt Publishing, |c 2018. | |
| 264 | 4 | |c ©2018 | |
| 300 | |a 1 online resource (1 volume) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 520 | |a Transform machine data into powerful analytical intelligence using Splunk Key Features Analyze and visualize machine data to step into the world of Splunk! Leverage the exceptional analysis and visualization capabilities to make informed decisions for your business This easy-to-follow, practical book can be used by anyone - even if you have never managed data before Book Description Splunk is a search, reporting, and analytics software platform for machine data, which has an ever-growing market adoption rate. More organizations than ever are adopting Splunk to make informed decisions in areas such as IT operations, information security, and the Internet of Things. The first two chapters of the book will get you started with a simple Splunk installation and set up of a sample machine data generator, called Eventgen. After this, you will learn to create various reports, dashboards, and alerts. You will also explore Splunk's Pivot functionality to model data for business users. You will then have the opportunity to test-drive Splunk's powerful HTTP Event Collector. After covering the core Splunk functionality, you'll be provided with some real-world best practices for using Splunk, and information on how to build upon what you've learned in this book. Throughout the book, there will be additional comments and best practice recommendations from a member of the SplunkTrust Community, called "Tips from the Fez". What you will learn Install and configure Splunk for personal use Store event data in Splunk indexes, classify events into sources, and add data fields Learn essential Splunk Search Processing Language commands and best practices Create powerful real-time or user-input dashboards Be proactive by implementing alerts and scheduled reports Tips from the Fez: best practices using Splunk features and add-ons Understand security and deployment considerations for taking Splunk to an organizational level Who this book is for This book is for the beginners who want to get well versed in the services offered by Splunk 7. If you want to be a data/business analyst or want to be a system administrator, this book is what you want. No prior knowledge of Splunk is required | ||
| 505 | 0 | |a Cover; Title Page; Copyright and Credits; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Splunk -- Getting Started; Your Splunk account; Obtaining a Splunk account; Installing Splunk on Windows; Installing Splunk on Linux; Logging in for the first time; Running a simple search; Creating a Splunk app; Populating data with Eventgen; Using the CLI to configure Eventgen; Installing the Eventgen add-on (Windows and Linux); Controlling Splunk; Configuring Eventgen; Viewing the Destinations app; Creating your first dashboard; Summary; Chapter 2: Bringing in Data. | |
| 505 | 8 | |a Splunk and big dataStreaming data; Analytical data latency; Sparseness of data; Splunk data sources; Machine data; Web logs; Data files; Social media data; Relational database data; Other data types; Creating indexes; Buckets; Log files as data input; Splunk events and fields; Extracting new fields; Summary; Chapter 3: Search Processing Language; Anatomy of a search; Search pipeline; Time modifiers; Filtering search results; Search command -- stats; Search command -- top/rare; Search commands -- chart and timechart; Search command -- eval; Search command -- rex; Summary. | |
| 505 | 8 | |a Chapter 4: Reporting, Alerts, and Search OptimizationData classification with Event Types; Data normalization with Tags; Data enrichment with Lookups; Creating and scheduling reports; Creating alerts; Search and Report acceleration; Scheduling options; Summary indexing; Summary; Chapter 5: Dynamic Dashboarding; Creating effective dashboards; Types of dashboards; Gathering business requirements; Dynamic form-based dashboard; Creating a Status Distribution panel; Creating the Status Types Over Time panel; Creating the Hits vs Response Time panel; Arrange the dashboard; Panel options. | |
| 505 | 8 | |a Pie chart -- Status DistributionStacked area chart -- Status Types Over Time; Column with overlay combination chart -- Hits vs Response Time; Form inputs; Creating a time range input; Creating a radio input; Creating a drop-down input; Static real-time dashboard; Single-value panels with color ranges; Creating panels by cloning; Single-value panels with trends; Real-time column charts with line overlays; Creating a choropleth map; Summary; Chapter 6: Data Models and Pivot; Creating a data model; Adding attributes to objects; Creating child objects. | |
| 505 | 8 | |a Creating an attribute based on a regular expressionData model acceleration; The Pivot editor; Creating a Pivot and a chart; Creating an area chart; Creating a pie chart; Single value with trending sparkline; Rearranging your dashboard; Summary; Chapter 7: HTTP Event Collector; What is the HEC?; How does the HEC work?; How data flows to the HEC; Logging data; Using a token with data; Sending out the data request; Verifying the token; Indexing the data; Enabling the HEC; Generating an HEC authentication token; Seeing the HEC in action with cURL; Indexer acknowledgement; Summary. | |
| 504 | |a Includes bibliographical references. | ||
| 650 | 0 | |a Big data. |0 http://id.loc.gov/authorities/subjects/sh2012003227 | |
| 650 | 0 | |a Data mining. |0 http://id.loc.gov/authorities/subjects/sh97002073 | |
| 650 | 0 | |a Automatic data collection systems. |0 http://id.loc.gov/authorities/subjects/sh85010095 | |
| 650 | 2 | |a Data Mining |0 https://id.nlm.nih.gov/mesh/D057225 | |
| 650 | 6 | |a Données volumineuses. | |
| 650 | 6 | |a Exploration de données (Informatique) | |
| 650 | 6 | |a Collecte automatique des données. | |
| 650 | 7 | |a Operational research. |2 bicssc | |
| 650 | 7 | |a Database design & theory. |2 bicssc | |
| 650 | 7 | |a Data capture & analysis. |2 bicssc | |
| 650 | 7 | |a Information architecture. |2 bicssc | |
| 650 | 7 | |a Enterprise software. |2 bicssc | |
| 650 | 7 | |a Computers. |x Data Processing. |2 bisacsh | |
| 650 | 7 | |a Computers. |x Data Modeling & Design. |2 bisacsh | |
| 650 | 7 | |a Computers. |x Enterprise Applications |x Business Intelligence Tools. |2 bisacsh | |
| 650 | 7 | |a Automatic data collection systems |2 fast | |
| 650 | 7 | |a Big data |2 fast | |
| 650 | 7 | |a Data mining |2 fast | |
| 700 | 1 | |a Sigman, Betsy Page, |e author. | |
| 700 | 1 | |a Delgado, Erickson, |e author. | |
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| author | Contreras, J-P Sigman, Betsy Page Delgado, Erickson |
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| contents | Cover; Title Page; Copyright and Credits; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Splunk -- Getting Started; Your Splunk account; Obtaining a Splunk account; Installing Splunk on Windows; Installing Splunk on Linux; Logging in for the first time; Running a simple search; Creating a Splunk app; Populating data with Eventgen; Using the CLI to configure Eventgen; Installing the Eventgen add-on (Windows and Linux); Controlling Splunk; Configuring Eventgen; Viewing the Destinations app; Creating your first dashboard; Summary; Chapter 2: Bringing in Data. Splunk and big dataStreaming data; Analytical data latency; Sparseness of data; Splunk data sources; Machine data; Web logs; Data files; Social media data; Relational database data; Other data types; Creating indexes; Buckets; Log files as data input; Splunk events and fields; Extracting new fields; Summary; Chapter 3: Search Processing Language; Anatomy of a search; Search pipeline; Time modifiers; Filtering search results; Search command -- stats; Search command -- top/rare; Search commands -- chart and timechart; Search command -- eval; Search command -- rex; Summary. Chapter 4: Reporting, Alerts, and Search OptimizationData classification with Event Types; Data normalization with Tags; Data enrichment with Lookups; Creating and scheduling reports; Creating alerts; Search and Report acceleration; Scheduling options; Summary indexing; Summary; Chapter 5: Dynamic Dashboarding; Creating effective dashboards; Types of dashboards; Gathering business requirements; Dynamic form-based dashboard; Creating a Status Distribution panel; Creating the Status Types Over Time panel; Creating the Hits vs Response Time panel; Arrange the dashboard; Panel options. Pie chart -- Status DistributionStacked area chart -- Status Types Over Time; Column with overlay combination chart -- Hits vs Response Time; Form inputs; Creating a time range input; Creating a radio input; Creating a drop-down input; Static real-time dashboard; Single-value panels with color ranges; Creating panels by cloning; Single-value panels with trends; Real-time column charts with line overlays; Creating a choropleth map; Summary; Chapter 6: Data Models and Pivot; Creating a data model; Adding attributes to objects; Creating child objects. Creating an attribute based on a regular expressionData model acceleration; The Pivot editor; Creating a Pivot and a chart; Creating an area chart; Creating a pie chart; Single value with trending sparkline; Rearranging your dashboard; Summary; Chapter 7: HTTP Event Collector; What is the HEC?; How does the HEC work?; How data flows to the HEC; Logging data; Using a token with data; Sending out the data request; Verifying the token; Indexing the data; Enabling the HEC; Generating an HEC authentication token; Seeing the HEC in action with cURL; Indexer acknowledgement; Summary. |
| ctrlnum | (OCoLC)1033544459 |
| dewey-full | 005.74 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
| dewey-raw | 005.74 |
| dewey-search | 005.74 |
| dewey-sort | 15.74 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| edition | Third edition. |
| format | Electronic eBook |
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| id | ZDB-4-EBA-on1033544459 |
| illustrated | Illustrated |
| indexdate | 2024-11-27T13:28:20Z |
| institution | BVB |
| isbn | 9781788830126 1788830121 |
| language | English |
| oclc_num | 1033544459 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (1 volume) : illustrations |
| psigel | ZDB-4-EBA |
| publishDate | 2018 |
| publishDateSearch | 2018 |
| publishDateSort | 2018 |
| publisher | Packt Publishing, |
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| spelling | Contreras, J-P, author. Splunk 7 essentials : demystify machine data by leveraging datasets, building reports, and sharing powerful insights / J-P Contreras, Erickson Delgado, Betsy Page Sigman. Splunk seven essentials Third edition. Birmingham, UK : Packt Publishing, 2018. ©2018 1 online resource (1 volume) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Online resource; title from digital title page (viewed on July 29, 2019). Transform machine data into powerful analytical intelligence using Splunk Key Features Analyze and visualize machine data to step into the world of Splunk! Leverage the exceptional analysis and visualization capabilities to make informed decisions for your business This easy-to-follow, practical book can be used by anyone - even if you have never managed data before Book Description Splunk is a search, reporting, and analytics software platform for machine data, which has an ever-growing market adoption rate. More organizations than ever are adopting Splunk to make informed decisions in areas such as IT operations, information security, and the Internet of Things. The first two chapters of the book will get you started with a simple Splunk installation and set up of a sample machine data generator, called Eventgen. After this, you will learn to create various reports, dashboards, and alerts. You will also explore Splunk's Pivot functionality to model data for business users. You will then have the opportunity to test-drive Splunk's powerful HTTP Event Collector. After covering the core Splunk functionality, you'll be provided with some real-world best practices for using Splunk, and information on how to build upon what you've learned in this book. Throughout the book, there will be additional comments and best practice recommendations from a member of the SplunkTrust Community, called "Tips from the Fez". What you will learn Install and configure Splunk for personal use Store event data in Splunk indexes, classify events into sources, and add data fields Learn essential Splunk Search Processing Language commands and best practices Create powerful real-time or user-input dashboards Be proactive by implementing alerts and scheduled reports Tips from the Fez: best practices using Splunk features and add-ons Understand security and deployment considerations for taking Splunk to an organizational level Who this book is for This book is for the beginners who want to get well versed in the services offered by Splunk 7. If you want to be a data/business analyst or want to be a system administrator, this book is what you want. No prior knowledge of Splunk is required Cover; Title Page; Copyright and Credits; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Splunk -- Getting Started; Your Splunk account; Obtaining a Splunk account; Installing Splunk on Windows; Installing Splunk on Linux; Logging in for the first time; Running a simple search; Creating a Splunk app; Populating data with Eventgen; Using the CLI to configure Eventgen; Installing the Eventgen add-on (Windows and Linux); Controlling Splunk; Configuring Eventgen; Viewing the Destinations app; Creating your first dashboard; Summary; Chapter 2: Bringing in Data. Splunk and big dataStreaming data; Analytical data latency; Sparseness of data; Splunk data sources; Machine data; Web logs; Data files; Social media data; Relational database data; Other data types; Creating indexes; Buckets; Log files as data input; Splunk events and fields; Extracting new fields; Summary; Chapter 3: Search Processing Language; Anatomy of a search; Search pipeline; Time modifiers; Filtering search results; Search command -- stats; Search command -- top/rare; Search commands -- chart and timechart; Search command -- eval; Search command -- rex; Summary. Chapter 4: Reporting, Alerts, and Search OptimizationData classification with Event Types; Data normalization with Tags; Data enrichment with Lookups; Creating and scheduling reports; Creating alerts; Search and Report acceleration; Scheduling options; Summary indexing; Summary; Chapter 5: Dynamic Dashboarding; Creating effective dashboards; Types of dashboards; Gathering business requirements; Dynamic form-based dashboard; Creating a Status Distribution panel; Creating the Status Types Over Time panel; Creating the Hits vs Response Time panel; Arrange the dashboard; Panel options. Pie chart -- Status DistributionStacked area chart -- Status Types Over Time; Column with overlay combination chart -- Hits vs Response Time; Form inputs; Creating a time range input; Creating a radio input; Creating a drop-down input; Static real-time dashboard; Single-value panels with color ranges; Creating panels by cloning; Single-value panels with trends; Real-time column charts with line overlays; Creating a choropleth map; Summary; Chapter 6: Data Models and Pivot; Creating a data model; Adding attributes to objects; Creating child objects. Creating an attribute based on a regular expressionData model acceleration; The Pivot editor; Creating a Pivot and a chart; Creating an area chart; Creating a pie chart; Single value with trending sparkline; Rearranging your dashboard; Summary; Chapter 7: HTTP Event Collector; What is the HEC?; How does the HEC work?; How data flows to the HEC; Logging data; Using a token with data; Sending out the data request; Verifying the token; Indexing the data; Enabling the HEC; Generating an HEC authentication token; Seeing the HEC in action with cURL; Indexer acknowledgement; Summary. Includes bibliographical references. Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Automatic data collection systems. http://id.loc.gov/authorities/subjects/sh85010095 Data Mining https://id.nlm.nih.gov/mesh/D057225 Données volumineuses. Exploration de données (Informatique) Collecte automatique des données. Operational research. bicssc Database design & theory. bicssc Data capture & analysis. bicssc Information architecture. bicssc Enterprise software. bicssc Computers. Data Processing. bisacsh Computers. Data Modeling & Design. bisacsh Computers. Enterprise Applications Business Intelligence Tools. bisacsh Automatic data collection systems fast Big data fast Data mining fast Sigman, Betsy Page, author. Delgado, Erickson, author. has work: Splunk 7 Essentials (Work) https://id.oclc.org/worldcat/entity/E39PCYpTy8JyCdgQwybxMWPQyH https://id.oclc.org/worldcat/ontology/hasWork FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1775081 Volltext |
| spellingShingle | Contreras, J-P Sigman, Betsy Page Delgado, Erickson Splunk 7 essentials : demystify machine data by leveraging datasets, building reports, and sharing powerful insights / Cover; Title Page; Copyright and Credits; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Splunk -- Getting Started; Your Splunk account; Obtaining a Splunk account; Installing Splunk on Windows; Installing Splunk on Linux; Logging in for the first time; Running a simple search; Creating a Splunk app; Populating data with Eventgen; Using the CLI to configure Eventgen; Installing the Eventgen add-on (Windows and Linux); Controlling Splunk; Configuring Eventgen; Viewing the Destinations app; Creating your first dashboard; Summary; Chapter 2: Bringing in Data. Splunk and big dataStreaming data; Analytical data latency; Sparseness of data; Splunk data sources; Machine data; Web logs; Data files; Social media data; Relational database data; Other data types; Creating indexes; Buckets; Log files as data input; Splunk events and fields; Extracting new fields; Summary; Chapter 3: Search Processing Language; Anatomy of a search; Search pipeline; Time modifiers; Filtering search results; Search command -- stats; Search command -- top/rare; Search commands -- chart and timechart; Search command -- eval; Search command -- rex; Summary. Chapter 4: Reporting, Alerts, and Search OptimizationData classification with Event Types; Data normalization with Tags; Data enrichment with Lookups; Creating and scheduling reports; Creating alerts; Search and Report acceleration; Scheduling options; Summary indexing; Summary; Chapter 5: Dynamic Dashboarding; Creating effective dashboards; Types of dashboards; Gathering business requirements; Dynamic form-based dashboard; Creating a Status Distribution panel; Creating the Status Types Over Time panel; Creating the Hits vs Response Time panel; Arrange the dashboard; Panel options. Pie chart -- Status DistributionStacked area chart -- Status Types Over Time; Column with overlay combination chart -- Hits vs Response Time; Form inputs; Creating a time range input; Creating a radio input; Creating a drop-down input; Static real-time dashboard; Single-value panels with color ranges; Creating panels by cloning; Single-value panels with trends; Real-time column charts with line overlays; Creating a choropleth map; Summary; Chapter 6: Data Models and Pivot; Creating a data model; Adding attributes to objects; Creating child objects. Creating an attribute based on a regular expressionData model acceleration; The Pivot editor; Creating a Pivot and a chart; Creating an area chart; Creating a pie chart; Single value with trending sparkline; Rearranging your dashboard; Summary; Chapter 7: HTTP Event Collector; What is the HEC?; How does the HEC work?; How data flows to the HEC; Logging data; Using a token with data; Sending out the data request; Verifying the token; Indexing the data; Enabling the HEC; Generating an HEC authentication token; Seeing the HEC in action with cURL; Indexer acknowledgement; Summary. Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Automatic data collection systems. http://id.loc.gov/authorities/subjects/sh85010095 Data Mining https://id.nlm.nih.gov/mesh/D057225 Données volumineuses. Exploration de données (Informatique) Collecte automatique des données. Operational research. bicssc Database design & theory. bicssc Data capture & analysis. bicssc Information architecture. bicssc Enterprise software. bicssc Computers. Data Processing. bisacsh Computers. Data Modeling & Design. bisacsh Computers. Enterprise Applications Business Intelligence Tools. bisacsh Automatic data collection systems fast Big data fast Data mining fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh2012003227 http://id.loc.gov/authorities/subjects/sh97002073 http://id.loc.gov/authorities/subjects/sh85010095 https://id.nlm.nih.gov/mesh/D057225 |
| title | Splunk 7 essentials : demystify machine data by leveraging datasets, building reports, and sharing powerful insights / |
| title_alt | Splunk seven essentials |
| title_auth | Splunk 7 essentials : demystify machine data by leveraging datasets, building reports, and sharing powerful insights / |
| title_exact_search | Splunk 7 essentials : demystify machine data by leveraging datasets, building reports, and sharing powerful insights / |
| title_full | Splunk 7 essentials : demystify machine data by leveraging datasets, building reports, and sharing powerful insights / J-P Contreras, Erickson Delgado, Betsy Page Sigman. |
| title_fullStr | Splunk 7 essentials : demystify machine data by leveraging datasets, building reports, and sharing powerful insights / J-P Contreras, Erickson Delgado, Betsy Page Sigman. |
| title_full_unstemmed | Splunk 7 essentials : demystify machine data by leveraging datasets, building reports, and sharing powerful insights / J-P Contreras, Erickson Delgado, Betsy Page Sigman. |
| title_short | Splunk 7 essentials : |
| title_sort | splunk 7 essentials demystify machine data by leveraging datasets building reports and sharing powerful insights |
| title_sub | demystify machine data by leveraging datasets, building reports, and sharing powerful insights / |
| topic | Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Automatic data collection systems. http://id.loc.gov/authorities/subjects/sh85010095 Data Mining https://id.nlm.nih.gov/mesh/D057225 Données volumineuses. Exploration de données (Informatique) Collecte automatique des données. Operational research. bicssc Database design & theory. bicssc Data capture & analysis. bicssc Information architecture. bicssc Enterprise software. bicssc Computers. Data Processing. bisacsh Computers. Data Modeling & Design. bisacsh Computers. Enterprise Applications Business Intelligence Tools. bisacsh Automatic data collection systems fast Big data fast Data mining fast |
| topic_facet | Big data. Data mining. Automatic data collection systems. Data Mining Données volumineuses. Exploration de données (Informatique) Collecte automatique des données. Operational research. Database design & theory. Data capture & analysis. Information architecture. Enterprise software. Computers. Data Processing. Computers. Data Modeling & Design. Computers. Enterprise Applications Business Intelligence Tools. Automatic data collection systems Big data Data mining |
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