This document provides an agenda and overview for a Splunk getting started user training workshop. The agenda covers getting started with Splunk, searching, alerts, dashboards, deployment and integration, the Splunk community, and getting help. It also provides explanations and examples of key Splunk concepts like searching, fields, saved searches, alerts, reports, dashboards, deployment options, and support resources. The goal is to introduce users to the essential functionality and capabilities of the Splunk platform.
SplunkLive! Zürich 2014 Beginner Workshop: Getting started with SplunkGeorg Knon
The document is an agenda for a Splunk technical workshop on getting started with Splunk user training. The agenda covers installing and starting Splunk, performing searches, creating alerts and dashboards, deployment and integration functionality, and getting support through the Splunk community.
Getting Started with Splunk Break out SessionGeorg Knon
This document provides an agenda and overview for a Splunk getting started user training workshop. The agenda includes introductions to getting started with Splunk, searching, alerts, dashboards, deployment and integration, the Splunk community, and a question and answer session. It also provides information on installing Splunk, Splunk licenses, the Splunk web interface, search basics, saved searches and alerts, deployment and integration options like forwarding data to Splunk, and where to find support resources.
This document provides an agenda for a Splunk technical workshop on getting started with Splunk. The agenda covers installing and starting Splunk, indexing sample data, performing basic searches, creating alerts, building reports and dashboards. It also discusses Splunk deployment and integration topics like distributed search, high availability, licensing, and integrating external user directories.
SplunkLive! Getting Started with Splunk EnterpriseSplunk
The document provides an agenda and overview for a Splunk getting started user training workshop. The summary covers the key topics:
- Getting started with Splunk including downloading, installing, and starting Splunk
- Core Splunk functions like searching, field extraction, saved searches, alerts, reporting, dashboards
- Deployment options including universal forwarders, distributed search, and high availability
- Integrations with other systems for data input, user authentication, and data output
- Support resources like the Splunk community, documentation, and technical support
This document provides an overview of getting data into Splunk through various input methods. It discusses setting up a Universal Forwarder to send data to Splunk Enterprise indexes. It also covers configuring the inputs.conf file to monitor files, blacklist/whitelist files, and collect Windows events. Additional input methods described include network inputs via TCP/UDP, scripted inputs, and the HTTP Event Collector. The document also touches on best practices for line breaking, timestamp recognition, and using modular and Splunk Stream inputs.
This document provides an overview and agenda for a Machine Data 101 presentation. The presentation covers Splunk fundamentals including the Splunk architecture and components, data sources both traditional and non-traditional, data enrichment techniques including tags, field aliases, calculated fields, event types, and lookups. Labs are included to help attendees get hands-on experience with indexing sample data, performing data discovery, and enriching data.
This document discusses Splunk's data onboarding process, which provides a systematic way to ingest new data sources into Splunk. It ensures new data is instantly usable and valuable. The process involves several steps: pre-boarding to identify the data and required configurations; building index-time configurations; creating search-time configurations like extractions and lookups; developing data models; testing; and deploying the new data source. Following this process helps get new data onboarding right the first time and makes the data immediately useful.
MOLOCH: Search for Full Packet Capture (OA Cyber Summit)Open Analytics
Moloch is an open source packet capture system built using Elasticsearch for storage and indexing and a Node.js web interface for searching. It consists of a capture process that extracts session profile information from packets and writes it to Elasticsearch, allowing the packet data and metadata to be queried and browsed through a web GUI or APIs. It is designed for scalability, supporting clustering across multiple nodes to handle large packet volumes.
SplunkLive! Zürich 2014 Beginner Workshop: Getting started with SplunkGeorg Knon
The document is an agenda for a Splunk technical workshop on getting started with Splunk user training. The agenda covers installing and starting Splunk, performing searches, creating alerts and dashboards, deployment and integration functionality, and getting support through the Splunk community.
Getting Started with Splunk Break out SessionGeorg Knon
This document provides an agenda and overview for a Splunk getting started user training workshop. The agenda includes introductions to getting started with Splunk, searching, alerts, dashboards, deployment and integration, the Splunk community, and a question and answer session. It also provides information on installing Splunk, Splunk licenses, the Splunk web interface, search basics, saved searches and alerts, deployment and integration options like forwarding data to Splunk, and where to find support resources.
This document provides an agenda for a Splunk technical workshop on getting started with Splunk. The agenda covers installing and starting Splunk, indexing sample data, performing basic searches, creating alerts, building reports and dashboards. It also discusses Splunk deployment and integration topics like distributed search, high availability, licensing, and integrating external user directories.
SplunkLive! Getting Started with Splunk EnterpriseSplunk
The document provides an agenda and overview for a Splunk getting started user training workshop. The summary covers the key topics:
- Getting started with Splunk including downloading, installing, and starting Splunk
- Core Splunk functions like searching, field extraction, saved searches, alerts, reporting, dashboards
- Deployment options including universal forwarders, distributed search, and high availability
- Integrations with other systems for data input, user authentication, and data output
- Support resources like the Splunk community, documentation, and technical support
This document provides an overview of getting data into Splunk through various input methods. It discusses setting up a Universal Forwarder to send data to Splunk Enterprise indexes. It also covers configuring the inputs.conf file to monitor files, blacklist/whitelist files, and collect Windows events. Additional input methods described include network inputs via TCP/UDP, scripted inputs, and the HTTP Event Collector. The document also touches on best practices for line breaking, timestamp recognition, and using modular and Splunk Stream inputs.
This document provides an overview and agenda for a Machine Data 101 presentation. The presentation covers Splunk fundamentals including the Splunk architecture and components, data sources both traditional and non-traditional, data enrichment techniques including tags, field aliases, calculated fields, event types, and lookups. Labs are included to help attendees get hands-on experience with indexing sample data, performing data discovery, and enriching data.
This document discusses Splunk's data onboarding process, which provides a systematic way to ingest new data sources into Splunk. It ensures new data is instantly usable and valuable. The process involves several steps: pre-boarding to identify the data and required configurations; building index-time configurations; creating search-time configurations like extractions and lookups; developing data models; testing; and deploying the new data source. Following this process helps get new data onboarding right the first time and makes the data immediately useful.
MOLOCH: Search for Full Packet Capture (OA Cyber Summit)Open Analytics
Moloch is an open source packet capture system built using Elasticsearch for storage and indexing and a Node.js web interface for searching. It consists of a capture process that extracts session profile information from packets and writes it to Elasticsearch, allowing the packet data and metadata to be queried and browsed through a web GUI or APIs. It is designed for scalability, supporting clustering across multiple nodes to handle large packet volumes.
This document provides an overview of Splunk, including how to install Splunk, configure licenses, perform searches, set up alerts and reports, and manage deployments. It discusses indexing data, extracting fields, tagging events, and using the web interface. The goal is to get users started with the basic functions of Splunk like searching, reporting and monitoring.
Slides for a college course based on "Incident Response & Computer Forensics, Third Edition" by by Jason Luttgens, Matthew Pepe, and Kevin Mandia.
Teacher: Sam Bowne
Twitter: @sambowne
Website: https://samsclass.info/121/121_F16.shtml
H-Hypermap - Heatmap Analytics at Scale: Presented by David Smiley, D W Smile...Lucidworks
This document provides an agenda and overview for a presentation on H-Hypermap, a project to build a search platform called the Billion Object Platform (BOP) to index and search over billions of geo-tagged tweets in near real-time. The presentation will cover the architecture using Apache Kafka, Solr sharding, and techniques for fast geo-spatial queries and heatmaps. It will also discuss experiences using technologies like Kotlin, Dropwizard, Docker and Kontena.
Getting Started with Splunk Breakout SessionSplunk
This document provides an overview and agenda for a presentation on getting started with Splunk Enterprise. The presentation covers an overview of Splunk Inc. and the Splunk platform, a live demonstration of using Splunk to install, index, search, create reports and dashboards, and set alerts. It also discusses deploying Splunk in distributed architectures, the Splunk community resources, and support options. The goal is to help attendees understand how to use the key capabilities of Splunk Enterprise.
This document provides an overview of a data science conference where the keynote speaker will discuss using Apache Solr and Apache Spark together for data science applications. The speaker is the CTO of Lucidworks and will cover getting started with Solr and Spark, demoing how to index data, run analytics like clustering and classification, and more. Resources for learning more about Solr, Spark, and Lucidworks Fusion are also provided.
Learning to Rank in Solr: Presented by Michael Nilsson & Diego Ceccarelli, Bl...Lucidworks
This document summarizes Bloomberg's use of machine learning for search ranking within their Solr implementation. It discusses how they process 8 million searches per day and need machine learning to automatically tune rankings over time as their index grows to 400 million documents. They use a Learning to Rank approach where features are extracted from queries and documents, training data is collected, and a ranking model is generated to optimize metrics like click-through rates. Their Solr Learning to Rank plugin allows this model to re-rank search results in Solr for improved relevance.
QuickStart your Sumo Logic service with this exclusive webinar. At these monthly live events you will learn how to capitalize on critical capabilities that can amplify your log analytics and monitoring experience while providing you with meaningful business and IT insights.
Live Webinar is found here: https://youtu.be/Q1yWlInxWVs
Slides for a college course based on "Incident Response & Computer Forensics, Third Edition" by by Jason Luttgens, Matthew Pepe, and Kevin Mandia, at City College San Francisco.
Website: https://samsclass.info/152/152_F18.shtml
This document provides an overview and agenda for the Splunk App for Stream, including:
- The architecture of the Stream Forwarder for capturing wire data and routing it to Splunk.
- The architecture of the App for Stream for analyzing wire data in Splunk.
- Examples of deployment architectures for ingesting wire data.
- A customer use case where wire data from the network helped provide visibility that log data could not due to access restrictions.
Building a real time big data analytics platform with solrTrey Grainger
Having “big data” is great, but turning that data into actionable intelligence is where the real value lies. This talk will demonstrate how you can use Solr to build a highly scalable data analytics engine to enable customers to engage in lightning fast, real-time knowledge discovery.
At CareerBuilder, we utilize these techniques to report the supply and demand of the labor force, compensation trends, customer performance metrics, and many live internal platform analytics. You will walk away from this talk with an advanced understanding of faceting, including pivot-faceting, geo/radius faceting, time-series faceting, function faceting, and multi-select faceting. You’ll also get a sneak peak at some new faceting capabilities just wrapping up development including distributed pivot facets and percentile/stats faceting, which will be open-sourced.
The presentation will be a technical tutorial, along with real-world use-cases and data visualizations. After this talk, you'll never see Solr as just a text search engine again.
Grant Ingersoll presented on using Apache Solr and Apache Spark for data engineering. He discussed how Solr can be used for indexing and searching large amounts of data, while Spark enables large-scale processing on the indexed data. Lucidworks' Fusion product combines Solr and Spark capabilities to allow search-driven applications and machine learning on indexed content.
Thoth - Real-time Solr Monitor and Search Analysis Engine: Presented by Damia...Lucidworks
Thoth is a real-time Solr monitoring system developed at Trulia to understand search infrastructure without accessing logs. It collects Solr request data, indexes it in another Solr core for search and analysis, and provides a dashboard and APIs for monitoring metrics. It also uses machine learning to predict query times and identify query patterns through topic modeling. The system was designed to be modular and its components like data collection, indexing, dashboard and monitoring are open-sourced.
This document provides an overview of a workshop on Lucene performance given by Lucid Imagination, Inc. It discusses common Lucene performance issues, introduces Lucid Gaze for Lucene (LG4L) as a tool for monitoring Lucene performance statistics and examples of using it to analyze indexing and search performance. LG4L provides statistics on indexing, analysis, searching and storage through logs, a persistent database and an API. It can help identify causes of poor performance and was shown to have low overhead.
Twitter provides a platform for user-generated content in the form of short messages called tweets. It handles a massive volume of data, with over 230 million tweets and 2 billion search queries per day. Twitter has developed a customized search and indexing system to handle this scale. It uses a modular system that is scalable, cost-effective, and allows for incremental development. The system includes components for crawling Twitter data, preprocessing and aggregating tweets, building an inverted index, and distributing the index across server machines for low-latency search.
Dashboards are fantastic, but how do I get notified of critical events? This webinar will cover how to create alerts that will allow your team to effectively monitor business-critical events. Alert channels include email or webhooks into Slack, PagerDuty, DataDog, ServiceNow, or any other webhook you want to develop. What about running custom scripts triggered from alerts? Let's do it.
Getting Started with Splunk Breakout SessionSplunk
This document provides an overview and introduction to Splunk Enterprise. It begins with an agenda that outlines discussing Splunk Enterprise, a live demonstration of using Splunk, deployment architecture, the Splunk community, and a Q&A. It then discusses how Splunk can unlock insights from machine data generated from various sources. The live demo shows installing Splunk, forwarding sample data, and performing searches. It also discusses deploying Splunk at scale, distributed architectures, and support resources available through the Splunk community.
DEEPSEC 2013: Malware Datamining And AttributionMichael Boman
Greg Hoglund explained at BlackHat 2010 that the development environments that malware authors use leaves traces in the code which can be used to attribute malware to a individual or a group of individuals. Not with the precision of name, date of birth and address but with evidence that a arrested suspects computer can be analysed and compared with the "tool marks" on the collected malware sample.
Splunk is a powerful platform that can harness your machine data and turn it into valuable information thereby enabling your business to make informed decisions, taking your organization from reactive to proactive. Just like any other platform, Splunk is only as powerful as the data it has access to, therefore in this session we will be conducting a walk thru of how to successfully on-board data, with samples of data ranging from simple to complex. We will also be taking a look at how to use common TA’s to bring valuable data into Splunk. This session is designed to give you a better understanding of how to onboard data into Splunk enabling you to unlock the power of your data.
The Splunk App for Microsoft Exchange provides real-time monitoring and reporting of Microsoft Exchange environments. It collects logs and metrics from Exchange Server and related systems. This allows administrators to view dashboards on server health, message flow, client usage, and capacity planning. Issues can be quickly identified and addressed to maintain high service availability and performance.
This document provides an overview of Splunk, Inc. including:
- Splunk is a software company founded in 2004 that provides data platforms for machine data including on-premise, cloud, and SaaS solutions.
- They have over 5,200 customers including 63 of the Fortune 100 and can process up to 100 terabytes per day for their largest license.
- Splunk's software delivers value across IT operations and security as well as business analytics by enabling users to gain operational visibility and real-time insights from machine data.
- Splunk supports use cases across various industries including retail, media, telecommunications, and manufacturing by helping customers turn machine data into valuable business insights.
This document provides an overview of Splunk, including how to install Splunk, configure licenses, perform searches, set up alerts and reports, and manage deployments. It discusses indexing data, extracting fields, tagging events, and using the web interface. The goal is to get users started with the basic functions of Splunk like searching, reporting and monitoring.
Slides for a college course based on "Incident Response & Computer Forensics, Third Edition" by by Jason Luttgens, Matthew Pepe, and Kevin Mandia.
Teacher: Sam Bowne
Twitter: @sambowne
Website: https://samsclass.info/121/121_F16.shtml
H-Hypermap - Heatmap Analytics at Scale: Presented by David Smiley, D W Smile...Lucidworks
This document provides an agenda and overview for a presentation on H-Hypermap, a project to build a search platform called the Billion Object Platform (BOP) to index and search over billions of geo-tagged tweets in near real-time. The presentation will cover the architecture using Apache Kafka, Solr sharding, and techniques for fast geo-spatial queries and heatmaps. It will also discuss experiences using technologies like Kotlin, Dropwizard, Docker and Kontena.
Getting Started with Splunk Breakout SessionSplunk
This document provides an overview and agenda for a presentation on getting started with Splunk Enterprise. The presentation covers an overview of Splunk Inc. and the Splunk platform, a live demonstration of using Splunk to install, index, search, create reports and dashboards, and set alerts. It also discusses deploying Splunk in distributed architectures, the Splunk community resources, and support options. The goal is to help attendees understand how to use the key capabilities of Splunk Enterprise.
This document provides an overview of a data science conference where the keynote speaker will discuss using Apache Solr and Apache Spark together for data science applications. The speaker is the CTO of Lucidworks and will cover getting started with Solr and Spark, demoing how to index data, run analytics like clustering and classification, and more. Resources for learning more about Solr, Spark, and Lucidworks Fusion are also provided.
Learning to Rank in Solr: Presented by Michael Nilsson & Diego Ceccarelli, Bl...Lucidworks
This document summarizes Bloomberg's use of machine learning for search ranking within their Solr implementation. It discusses how they process 8 million searches per day and need machine learning to automatically tune rankings over time as their index grows to 400 million documents. They use a Learning to Rank approach where features are extracted from queries and documents, training data is collected, and a ranking model is generated to optimize metrics like click-through rates. Their Solr Learning to Rank plugin allows this model to re-rank search results in Solr for improved relevance.
QuickStart your Sumo Logic service with this exclusive webinar. At these monthly live events you will learn how to capitalize on critical capabilities that can amplify your log analytics and monitoring experience while providing you with meaningful business and IT insights.
Live Webinar is found here: https://youtu.be/Q1yWlInxWVs
Slides for a college course based on "Incident Response & Computer Forensics, Third Edition" by by Jason Luttgens, Matthew Pepe, and Kevin Mandia, at City College San Francisco.
Website: https://samsclass.info/152/152_F18.shtml
This document provides an overview and agenda for the Splunk App for Stream, including:
- The architecture of the Stream Forwarder for capturing wire data and routing it to Splunk.
- The architecture of the App for Stream for analyzing wire data in Splunk.
- Examples of deployment architectures for ingesting wire data.
- A customer use case where wire data from the network helped provide visibility that log data could not due to access restrictions.
Building a real time big data analytics platform with solrTrey Grainger
Having “big data” is great, but turning that data into actionable intelligence is where the real value lies. This talk will demonstrate how you can use Solr to build a highly scalable data analytics engine to enable customers to engage in lightning fast, real-time knowledge discovery.
At CareerBuilder, we utilize these techniques to report the supply and demand of the labor force, compensation trends, customer performance metrics, and many live internal platform analytics. You will walk away from this talk with an advanced understanding of faceting, including pivot-faceting, geo/radius faceting, time-series faceting, function faceting, and multi-select faceting. You’ll also get a sneak peak at some new faceting capabilities just wrapping up development including distributed pivot facets and percentile/stats faceting, which will be open-sourced.
The presentation will be a technical tutorial, along with real-world use-cases and data visualizations. After this talk, you'll never see Solr as just a text search engine again.
Grant Ingersoll presented on using Apache Solr and Apache Spark for data engineering. He discussed how Solr can be used for indexing and searching large amounts of data, while Spark enables large-scale processing on the indexed data. Lucidworks' Fusion product combines Solr and Spark capabilities to allow search-driven applications and machine learning on indexed content.
Thoth - Real-time Solr Monitor and Search Analysis Engine: Presented by Damia...Lucidworks
Thoth is a real-time Solr monitoring system developed at Trulia to understand search infrastructure without accessing logs. It collects Solr request data, indexes it in another Solr core for search and analysis, and provides a dashboard and APIs for monitoring metrics. It also uses machine learning to predict query times and identify query patterns through topic modeling. The system was designed to be modular and its components like data collection, indexing, dashboard and monitoring are open-sourced.
This document provides an overview of a workshop on Lucene performance given by Lucid Imagination, Inc. It discusses common Lucene performance issues, introduces Lucid Gaze for Lucene (LG4L) as a tool for monitoring Lucene performance statistics and examples of using it to analyze indexing and search performance. LG4L provides statistics on indexing, analysis, searching and storage through logs, a persistent database and an API. It can help identify causes of poor performance and was shown to have low overhead.
Twitter provides a platform for user-generated content in the form of short messages called tweets. It handles a massive volume of data, with over 230 million tweets and 2 billion search queries per day. Twitter has developed a customized search and indexing system to handle this scale. It uses a modular system that is scalable, cost-effective, and allows for incremental development. The system includes components for crawling Twitter data, preprocessing and aggregating tweets, building an inverted index, and distributing the index across server machines for low-latency search.
Dashboards are fantastic, but how do I get notified of critical events? This webinar will cover how to create alerts that will allow your team to effectively monitor business-critical events. Alert channels include email or webhooks into Slack, PagerDuty, DataDog, ServiceNow, or any other webhook you want to develop. What about running custom scripts triggered from alerts? Let's do it.
Getting Started with Splunk Breakout SessionSplunk
This document provides an overview and introduction to Splunk Enterprise. It begins with an agenda that outlines discussing Splunk Enterprise, a live demonstration of using Splunk, deployment architecture, the Splunk community, and a Q&A. It then discusses how Splunk can unlock insights from machine data generated from various sources. The live demo shows installing Splunk, forwarding sample data, and performing searches. It also discusses deploying Splunk at scale, distributed architectures, and support resources available through the Splunk community.
DEEPSEC 2013: Malware Datamining And AttributionMichael Boman
Greg Hoglund explained at BlackHat 2010 that the development environments that malware authors use leaves traces in the code which can be used to attribute malware to a individual or a group of individuals. Not with the precision of name, date of birth and address but with evidence that a arrested suspects computer can be analysed and compared with the "tool marks" on the collected malware sample.
Splunk is a powerful platform that can harness your machine data and turn it into valuable information thereby enabling your business to make informed decisions, taking your organization from reactive to proactive. Just like any other platform, Splunk is only as powerful as the data it has access to, therefore in this session we will be conducting a walk thru of how to successfully on-board data, with samples of data ranging from simple to complex. We will also be taking a look at how to use common TA’s to bring valuable data into Splunk. This session is designed to give you a better understanding of how to onboard data into Splunk enabling you to unlock the power of your data.
The Splunk App for Microsoft Exchange provides real-time monitoring and reporting of Microsoft Exchange environments. It collects logs and metrics from Exchange Server and related systems. This allows administrators to view dashboards on server health, message flow, client usage, and capacity planning. Issues can be quickly identified and addressed to maintain high service availability and performance.
This document provides an overview of Splunk, Inc. including:
- Splunk is a software company founded in 2004 that provides data platforms for machine data including on-premise, cloud, and SaaS solutions.
- They have over 5,200 customers including 63 of the Fortune 100 and can process up to 100 terabytes per day for their largest license.
- Splunk's software delivers value across IT operations and security as well as business analytics by enabling users to gain operational visibility and real-time insights from machine data.
- Splunk supports use cases across various industries including retail, media, telecommunications, and manufacturing by helping customers turn machine data into valuable business insights.
Data models in Splunk provide a way to abstract raw machine data and encapsulate domain knowledge. They allow non-technical users to explore and report on data through a simplified pivot interface without needing to understand the underlying search language. A data model consists of a hierarchical set of objects that map to events, searches, or groups of events/searches. Objects define constraints and attributes to extract fields from raw data. The data model acceleration feature allows for faster analytics by pre-computing search results.
1) The document discusses how Splunk can be used as a platform for analyzing big data from a variety of sources in real time.
2) It explains that machine-generated data is one of the fastest growing and most complex segments of big data, including sources like sensors, servers, and mobile devices.
3) Splunk allows users to search, monitor, and analyze this large, complex data from many different sources through an interface that supports ad hoc searches, dashboards, alerts and more.
Daten anonymisieren und pseudonymisieren in Splunk Enterprisejenny_splunk
This document discusses data obfuscation techniques in Splunk Enterprise, including anonymization and pseudonymization. It covers securing data in flight using encryption and authentication. For data at rest, it discusses integrity controls and encryption using OS, devices, or Vormetric. It then details how Splunk supports anonymization through SEDCMD transforms or at search time. Pseudonymization techniques include hashing or duplicating data to different indexes. The document demonstrates modular inputs and a custom data handler to encrypt and anonymize fields before indexing.
This document outlines an agenda for a Splunk getting started user training workshop. The agenda includes introducing Splunk functionality like search, alerts, dashboards, deployment and integration. It also covers installing Splunk, indexing data, search basics, field extraction, saved searches, alerting and reporting dashboards. The workshop aims to help users get started with the core Splunk features.
Getting started with Splunk - Break out SessionGeorg Knon
This document provides an overview and getting started guide for Splunk. It discusses what Splunk is for exploring machine data, how to install and start Splunk, add sample data, perform basic searches, create saved searches, alerts and dashboards. It also covers deployment and integration topics like scaling Splunk, distributing searches across data centers, forwarding data to Splunk, and enriching data with lookups. The document recommends resources like the Splunk community for further support.
This document provides an overview and getting started guide for Splunk. It discusses what Splunk is for exploring machine data, how to install and start Splunk, add sample data, perform basic searches, create saved searches, alerts and dashboards. It also covers deployment and integration topics like scaling Splunk, distributing searches across data centers, forwarding data to Splunk, and enriching data with lookups. The document recommends resources like the Splunk community for support.
This document provides an overview and introduction to Splunk, an enterprise software platform for searching, monitoring, and analyzing machine-generated big data, such as logs, metrics, and events. The agenda covers what Splunk is, how to get started with Splunk including installing and licensing, basic search functionality, creating alerts and dashboards, deployment and integration options to scale Splunk across multiple sites and systems, and resources for support and the Splunk community. Key capabilities highlighted include searching and analyzing structured and unstructured machine data, indexing petabytes of data per day, role-based access controls, high availability, and integrating with third-party systems.
Getting started with Splunk Breakout SessionSplunk
This document provides a summary of a presentation about Splunk. It discusses what Splunk is and how it works, including that Splunk is a platform for searching, monitoring, and analyzing machine-generated big data in real-time. It also covers key Splunk concepts like indexing, searching, reporting, alerting, and deployment options. The presentation demonstrates how to install Splunk, add sample data, perform searches, extract fields, create alerts and dashboards, and discusses integration, support resources, and the Splunk developer platform.
Splunk is a software platform that allows users to search, monitor, and analyze machine-generated big data for security, business intelligence, and other uses. It collects and indexes data in real-time from various sources and enables users to search and investigate the data, create alerts, reports, and visualizations. Splunk has over 5,200 customers worldwide across various industries and can be used for applications including IT operations, security, and business analytics.
This document summarizes key learnings from a presentation about SharePoint 2013 and Enterprise Search. It discusses how to run a successful search project through planning, development, testing and deployment. It also covers infrastructure needs and capacity testing findings. Additionally, it provides examples of how to customize the user experience through display templates and Front search. Methods for crawling thousands of file shares and enriching indexed content are presented. The document concludes with discussions on relevancy, managing property weighting, changing ranking models, and tuning search results.
Sumo Logic QuickStart Webinar - Jan 2016Sumo Logic
QuickStart your Sumo Logic service with this exclusive webinar. At these monthly live events you will learn how to capitalize on critical capabilities that can amplify your log analytics and monitoring experience while providing you with meaningful business and IT insights
QuickStart your Sumo Logic service with this exclusive webinar. At these monthly live events you will learn how to capitalize on critical capabilities that can amplify your log analytics and monitoring experience while providing you with meaningful business and IT insights.
QuickStart your Sumo Logic service with this exclusive webinar. At these monthly live events you will learn how to capitalize on critical capabilities that can amplify your log analytics and monitoring experience while providing you with meaningful business and IT insights.
More info: sumologic.com/training
This document provides an overview of Splunk Enterprise, including what it is, how it deploys and integrates, and its capabilities around real-time search, alerting, and reporting. Splunk Enterprise is an industry-leading platform for machine data that allows users to search, monitor, and analyze machine data from any source, location, or volume in real-time or historically. It deploys easily in 4 steps and scales to handle hundreds of terabytes of data per day from diverse sources like servers, applications, sensors, and more.
This document outlines an agenda for an advanced Splunk user training workshop. The workshop covers topics like field aliasing, common information models, event types, tags, dashboard customization, index replication for high availability, report acceleration, and lookups. It provides overviews and examples for each topic and directs attendees to additional documentation resources for more in-depth learning. The workshop also includes demonstrations of dashboard customization techniques and discusses support options through the Splunk community.
Taking Splunk to the Next Level - Architecture Breakout SessionSplunk
This document discusses strategies for scaling a Splunk deployment. It begins by describing how customers typically start with a single use case but then need to scale to handle more data and use cases. It then covers strategies for scaling the forwarding, indexing, search, and management components of Splunk. Key topics include load balancing forwarders, using indexer clustering for high availability, scaling search heads by clustering, and using the deployment server and distributed management console for centralized management. The document emphasizes planning storage capacity and I/O when scaling indexers and considering Splunk's application support when scaling search heads.
This document provides an overview of how Garmin International uses Splunk to monitor and analyze machine data. It introduces Tyler Rutschman, a Linux systems administrator at Garmin, and describes how Garmin started using Splunk in 2009 to help with Sarbanes-Oxley compliance. Splunk has provided benefits like reduced mean time to resolution, better reporting capabilities, cost savings, and improved compliance. The implementation collects up to 150 GB of data per day from sources like servers, databases, and load balancers. Future plans include indexer upgrades and adding more Garmin application data to Splunk.
Taking Splunk to the Next Level – ArchitectureSplunk
Are you outgrowing your initial Splunk deployment? Is Splunk becoming mission critical and you need to make sure it's Enterprise ready? Attend this session led by Splunk experts to learn about taking your Splunk deployment to the next level. Learn about Splunk high availability architectures with Splunk Search Head Clustering and Index Replication. Additionally, learn how to manage your deployment with Splunk’s operational and management controls to manage Splunk capacity and end user experience.
SplunkLive! Frankfurt 2018 - Data Onboarding OverviewSplunk
Presented at SplunkLive! Frankfurt 2018:
Splunk Data Collection Architecture
Apps and Technology Add-ons
Demos / Examples
Best Practices
Resources and Q&A
Getting Started with Splunk Enterprise Hands-OnSplunk
This document provides an overview and demonstration of Splunk software. The agenda includes downloading Splunk, an overview of its key features for searching machine data, field extraction, dashboards, alerting, and analytics. The presenter then demonstrates installing and onboarding sample data, performing searches, and using pivots. deployment architectures are discussed along with scaling to hundreds of terabytes per day. Questions areas like documentation, support, and the Splunk user conference are also mentioned.
What is Splunk? At the end of this session you’ll have a high-level understanding of the pieces that make up the Splunk Platform, how it works, and how it fits in the landscape of Big Data. You’ll see practical examples that differentiate Splunk while demonstrating how to gain quick time to value.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
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See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
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- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
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4. Splunk Delivers Value Across IT and the Business
App Dev
and
App Mgmt.
IT
Operations
Security and
Compliance
Digital
Intelligence
Business
Analytics
Developer Platform (REST API, SDKs)
Small Data. Big Data. Huge Data.
Industrial Data
and Internet
of Things
5. Install Splunk
www.splunk.com/download
32 or 64 Bit?
Indexer or Universal Forwarder?
Splunk Home
WIN: Program FilesSplunk
Other: /opt/splunk (Applications/splunk)
Start Splunk
WIN: Program FilesSplunkbinsplunk.exe start (services start)
*NIX: /opt/splunk/bin/splunk start
6. Splunk Licenses
Free Download Limits Indexing to 500MB/day
Enterprise Trial License expires after 60 days
Reverts to Free License
Features Disabled in Free License
Multiple user accounts and role-based access controls
Distributed search
Forwarding to non-Splunk Instances
Deployment management
Scheduled saved searches and alerting
Summary indexing
Other License Types
Enterprise, Forwarder, Trial
7. Splunk Web Basics
Default installation on: http://localhost:8000
Browser Support
Firefox 10.x and latest
Internet Explorer 7, 8, 9 and 10
Safari (latest)
Chrome (latest)
Index data
Add data
Getting Started App
Install an App (Splunk for Windows, *NIX)
7
8. Splunk Web Basics continued…
Splunk Home
•
Provides Interactive portal to the Apps & data.
•
Includes a search bar and three panels:
1 – Apps 2 – Data 3 - Help
Splunk Apps
•
Splunk Home Find more apps
•
Provide different contexts for your data out of
sets of views, dashboards, and configurations
•
Default Search App
•
You can create your own!
8
10. Best Practice Suggestion:
Create an individual Index based on
sourcetype.
• Easier to re-index data if you make a
mistake.
• Easier to remove data.
• Easier to define permissions and data
retention.
11
12. current view
Search app – Summary view
app navigation
time range
picker
search box
start
search
Selecting Data
Summary:
• Host
• Source
• Sourcetype
global stats
13. Searching
Search > *
Select Time Range
•
Historical, custom, or real-time
Select Mode
•
Smart, Fast, Verbose
Using the timeline
•
Click events and zoom in and out
•
Click and drag over events for a specific range
14
14. Everything is searchable
Everything is searchable
fail*
•
* wildcards supported
fail* nfs
•
Search terms are case insensitive
•
Booleans AND, OR, NOT
–
–
–
•
Booleans must be uppercase
Implied AND between terms
Use () for complex searches
Quote phrases
error OR 404
error OR failed OR (sourcetype=access_*(500 OR 503))
"login failure"
15
16. Search Assistant
Contextual Help
- advanced type-ahead
updates as you type
shows examples and help
History
- search
- commands
Search Reference
- short/long description
- examples
suggests search terms
toggle off / on
17
17. Job Management
Searches can be managed as
asynchronous processes
Modify Job Settings
finalize
Jobs can be
•
•
•
•
•
•
Scheduled
Moved to background tasks
Paused, stopped, resumed, finalized
Managed
Archived
Cancelled
pause
delete
18
18. Search Commands
Search > error | head 1
Search results are “piped” to the command
Commands for:
•
Manipulating fields
•
Formatting
•
Handling results
•
Reporting
19
21. Fields
Default fields
•
host, source, sourcetype, linecount, etc.
•
View on left panel in search results or all in field picker
Where do fields come from?
•
Pre-defined by sourcetypes
•
Automatically extracted key-value pairs
•
User defined
22
22. Sources, Sourcetypes, Hosts
•
Host
- hostname, IP address,
or name of the network
host from which the
events originated
•
Source
- the name of the file,
stream, or other input
•
Sourcetype
- a specific data type or
data format
2
3
23. Tagging and Event Typing
Eventtypes for more human-readable reports
to categorize and make sense of mountains of data
punctuation helps find events with similar patterns
Search > eventtype=failed_login instead of
Search > “failed login” OR “FAILED LOGIN” OR “Authentication failure” OR “Failed to
………………authenticate user”
Tags are labels
apply ad-hoc knowledge
create logical divisions or groups
tag hosts, sources, fields, even eventtypes
Search > tag=web_servers instead of
Search > host=“apache1.splunk.com” OR host=“apache2.splunk.com” OR
…………….host=“apache3.splunk.com”
24
27. Saved Searches
Leverage Searches for future Insights!
Reports
Dashboards
Alerts
Eventtypes
Add a Time Range Picker
Preset
Relative
Real-time
Date-Range
Date & Time Range
Advanced
28
29. Alerting Continued…
Searches run on a schedule and fire an alert
•
Example: Run a search for “Failed password” every 15 min
over the last 15 min and alert if the number of events is
greater than 10
Searches are running in real-time and fire an alert
•
Example: Run a search for “Failed password user=john.doe” in
a 1 minute window and alert if an event is found
30
32. Reporting
Build reports from
results of any search
Define your Search and set your time range,
accelerate you search and more
Choose the type of chart (line, area, column, etc) and
other formatting options
33
33. Reporting Examples
• Use wizard or reporting commands (timechart, top, etc)
• Build real-time reports with real-time searches
• Save reports for use on dashboards
34
36. Manager Settings
For All of that Cool Stuff
You Just Created (and more!)
•
•
•
•
•
•
Permissions
Saved Searches/Reports
Custom Views
Distributed Splunk
Deployment Server
License Usage….
37
38. Splunk Has Four Primary Functions
•
Searching and Reporting (Search Head)
•
Indexing and Search Services (Indexer)
•
Local and Distributed Management (Deployment Server)
•
Data Collection and Forwarding (Forwarder)
A Splunk install can be one or all roles…
39
39. Getting Data Into Splunk
Agent and Agent-less Approach for Flexibility
Local File Monitoring
syslog
log files, config files
dumps and trace files
TCP/UDP
syslog compatible hosts
and network devices
Mounted File Systems
hostnamemount
Scripted Inputs
WMI
Event Logs Performance
shell scripts custom
parsers batch loading
Active
Directory
Windows Inputs
Event Logs
performance counters
registry monitoring
Active Directory monitoring
code
shell
perf
virtual
host
Unix, Linux and Windows hosts
Custom apps and scripted API connections
Windows hosts
Splunk Forwarder
Agent-less Data Input
40
Windows hosts
40. Understanding the Universal Forwarder
Forward data without negatively impacting production performance.
Universal Forwarder
Regular (Heavy) Forwarder
Monitor All
Supported
Inputs
✔
✔
Routing,
Filtering,
Cloning
✔
Universal Forwarder Deployment
✔
Logs
Splunk Web
✔
Scripted
Inputs
Metrics
Scripts
✔
Event Based
Routing
Configurations
✔
Python
Libraries
Messages
✔
Central Deployment Management
Monitor files, changes and the system registry; capture metrics and status.
41
41. Horizontal Scaling
Load balanced search and indexing for massive, linear scale out.
Distributed Search
Forwarder
Auto Load
Balancing
42
42. Multiple Datacenters
Index and store locally. Distribute searches to datacenters, networks & geographies.
Headquarters
Distributed Search
London
Hong Kong
Tokyo
43
New York
43. High Availability, On Commodity Servers and Storage
Index Replication
As Splunk collects data, it keeps
multiple identical copies
If indexer fails, incoming data
continues to get indexed
Splunk Universal
Forwarder Pool
Indexed data continues to be
searchable
Easy setup and administration
Constant
Uptime
Data integrity and resilience
without a SAN
44
44. High Availability
Combine auto load balancing and cloning for HA at every Splunk tier.
Shared Storage
Distributed Search
Distributed Search
Clone Group 2 : Complete Dataset
Clone Group 1 : Complete Dataset
Data Cloning &
Auto Load Balancing
45
45. Send Data to Other Systems
Route raw data in real time or send alerts based on searches.
Service Desk
Event Console
SIEM
46
46. Integrate External Data
Extend search with lookups to external data sources.
Watch
Lists
LDAP, AD
CMDB
CRM/ER
P
Correlate IP addresses with locations, accounts with regions
47
47. Integrate Users and Roles
Integrate authentication with LDAP and Active Directory.
LDAP, AD
Users and Groups
Problem Investigation
Splunk Flexible Roles
Capabilities & Filters
Manage
Indexes
Problem Investigation
Share
Searches
Save
Searches
Problem Investigation
Manage
Users
NOT
tag=PCI
App=ERP
Map LDAP & AD groups to flexible Splunk roles. Define any search as a filter.
48
…
52. Where to Go for Help
•
Documentation
– http://www.splunk.com/base/Documentation
•
Technical Support
– http://www.splunk.com/support
•
Videos
– http://www.splunk.com/videos
•
Education
– http://www.splunk.com/goto/education
•
Community
– http://answers.splunk.com
•
Splunk Book
– http://splunkbook.com
53
Follow along if you like!See full list of supported platforms in Installation Manual.Can choose different directory during installation.
Good analogy for Apps is iPhone/iPad. Same data, many uses. Apps change the presentation layer.
Illustrate add data, illustrate creating a new index, illustrate the *nix app to show performance metrics.Also, new splunk overview app that ships with test data for DM and Pivot etc,
This is the unix app in action. In this example, we’re pulling a number of scripted inputs such as top, iostat, network, etc.
1. Wildcards are supported - *2. Search terms are case insensitive.3. Boolean searches are supported with AND, OR, NOT. Just remember that Booleans must be uppercase.4. There is an implied AND between the search terms, and for complex searches, use parenthesis. (error OR failed)5. You can also quote phrases such as “Login Failure”6. Search Modes!
1. Wildcards are supported - *2. Search terms are case insensitive.3. Boolean searches are supported with AND, OR, NOT. Just remember that Booleans must be uppercase.4. There is an implied AND between the search terms, and for complex searches, use parenthesis. (error OR failed)5. You can also quote phrases such as “Login Failure”6. Search Modes!
This is an example of a search by host excluding events with an error log level
The search assistant offers quick reference for the Splunk search language that updates as you type. That includes links to online documentation, and shows matching searches along with their count, matching terms and examples. It also shows you your history of searches.
A search becomes a job for Splunk to process. While a search is processing, this job can be Canceled, Paused, sent to the background and Finalized. The ability to cancel is handy if you made a mistake or chose the wrong time range.Finalized = stop processing events but build the "number of events" count. Jobs can be accessed while running or after through the jobs menu. There, Paused Jobs can be resumed and those sent to the background can be accessed. Jobs results are kept for a configurable time of 10 minutes by default.
Splunk search language is very unix-like—use the pipe symbol to pass search results to search commands. Search commands can be chained. You can even create your own custom search commands.These are common commands we find most useful to analyze and filter data. <review each command>Search reference is available online in addition to the search assistance and covers all search commands.
Much like *nix* operating systems, chances are you’re not going to memorize all of the commands. You’ll memorize a handful, and rely on the “man pages” to get additional context to commands. We SEs here at Splunk use maybe twenty terms in our day to day.
Fields give you much more precision in searches. Fields are key value pairs associated with your data by Splunk. So, an example would be host=www1, status=503. Now there are two specific types of fields. There are default fields, (source, sourcetype and host) which are added to every event by Splunk during indexing.And there are data-specific fields. These would be action=“purchase” or status=“503”.
What’s the difference between Sources, sourcetypes, and hosts?A host would be the hostname, IP address or name of the network host from which events originate. An example might be a single windows server would be a host or specific firewall.A Source is the name of a file, a stream or some other input, such as a config file, process, application or event log, on a server. So per our Windows server example, sources on that server, might include Windows event logs, exchange logs, DNS/DHCP logs, performance metrics as well as the windows event logs from the windows event viewer. Each of these is a different source.A Sourcetype is a specific data format. Sourcetype would beALL exchange logs or ALL Cisco ASA. It’s a high level group. Running your searches against a sourcetype of Windows Event Log Security across multiple servers.
Event types can help you automatically identify events based on a search. An event type is a field based on a search, it’s a way of classifying data for searching and reporting and it’s useful for user knowledge capture and sharing.Tags are different, in that they allow you to search for events with related field values. You can assign any field/value combination. So as an example, server names aren’t always helpful. Sometimes they contain ambiguous information. Using tags you can use a more meaningful term.The Splunk Manager allows you to enable/disable, copy, delete and edit tags that you’ve created.
Extracting fields that aren’t already pulled out at search time is a necessary step to doing more with your data like reporting.Show example of field extraction with IFX and an example using rex.Show other field extractor.
Extracting fields that aren’t already pulled out at search time is a necessary step to doing more with your data like reporting.Show example of field extraction with IFX and an example using rex.Show other field extractor.
Use the time range picker to set time boundaries on your searches. You can restrict the search to Preset time ranges, custom Relative time ranges, and custom Real-time time ranges. You can also specify a Date Range, a Date & Time Range, and use more advanced options for specifying the time ranges for a search.
Real-time alerts always trigger immediately for every returned resultReal-time monitored alerts monitor a real-time window and can trigger immediately, or you can define conditionsScheduled alerts run a search on a regular interval that you define and triggers based on conditions that you define
Run alert in Splunk.Splunk alerts are based on searches and can run either on a regular scheduled interval or in real-time.Alerts are triggered when the results of the search meet a specific condition that you define.Based on your needs, alerts can send emails, trigger scripts and write to RSS feeds.
Consider how you might use a scripted alert.
Demo building a traditional report. Reports can also be dashboards mailed out.
Demo building a report and dashboard.
Demo new dashboard workflow
Show dashboard examples:
Why with the same settings is the shadow so dark?
Splunk can be divided into four logical functions. First, from the bottom up, collection. Splunk forwarders come in two packages; the full Splunk distribution or a dedicated “Universal Forwarder”. The full Splunk distribution can be configured to filter data before transmitting, execute scripts locally, or run SplunkWeb. This gives you several options depending on the footprint size your endpoints can tolerate. The universal forwarder is an ultra-lightweight agent designed to collect data in the smallest possible footprint. Both flavors of forwarder come with automatic load balancing, SSL encryption and data compression, and the ability to route data to multiple Splunk instances or third party systems. To manage your distributed Splunk environment, there is the Deployment Server. Deployment server helps you synchronize the configuration of your search heads during distributed searching, as well as your forwarders to centrally manage your distributed data collection. Of course, Splunk has a simple flat-file configuration system, so feel free to use your own config management tools if your more comfortable with what you already have. The core of the Splunk infrastructure is indexing. An indexer does two things – it accepts and processes new data, adding it to the index and compressing it on disk. The indexer also services search requests, looking through the data it has via it’s indices and returning the appropriate results to the searcher over a compressed communication channel. Indexers scale out almost limitlessly and with almost no degradation in overall performance, allowing Splunk to scale from single-instance small deployments to truly massive Big Data challenges. Finally, the Splunk most users see is the search head. This is the webserver and app interpreting engine that provides the primary, web-based user interface. Since most of the data interpretation happens as-needed at search time, the role of the search head is to translate user and app requests into actionable searches for it’s indexer(s) and display the results. The Splunk web UI is highly customizable, either through our own view and app system, or by embedding Splunk searches in your own web apps via includes or our API.
Getting data into Splunk is designed to be as flexible and easy as possible. Because the indexing engine is so flexible and doesn’t generally require configuration for most IT data, all that remains is how to collect and ship the data to your Splunk. There are many options. First, you can collect data over the network, without an agent. The most common network input is syslog; Splunk is a fully compliant and customizable syslog listener over both TCP and UDP. Further, because Splunk is just software, any remote file share you can mount or symlink to via the operating system is available for indexing as well. To facilitate remote Windows data collection, Splunk has a its own WMI query tool that can remotely collect Windows Event logs and performance counters from your Windows systems. Finally, Splunk has a AD monitoring tool that can connect to AD and get your user meta data to enhance your searching context and monitor AD for replication, policy or user security changes. When Splunk is running locally as an indexer or forwarder, you have additional options and greater control. Splunk can directly monitor hundreds or thousands of local files, index them and detect changes. Additionally, many customers use our out-of-the-box scripts and tools to generate data – common examples include performance polling scripts on *nix hosts, API calls to collect hypervisor statistics and for detailed monitoring of custom apps running in debug modes. Also, Splunk has Windows-specific collection tools, including native Event Log access, registry monitoring drivers, performance monitoring and AD monitoring that can run locally with a minimal footprint.
Historically, a Splunk forwarder was a stripped down version of the full Splunk distribution. Certain features, such as Splunk Web, were turned off to decrease footprint on a remote host. Our customers asked us for something even lighter and we delivered. The Universal Forwarder is a new, dedicated package specifically designed for collecting and sending data to Splunk. It’s super light on resources, easy to install, but still includes all the current Splunk inputs, without requiring python. Most deployments should only require the use of the Universal Forwarder but we have kept all features of forwarding in the Regular (or Heavy) Forwarder for cases when you need specific capabilities.
A single indexers it can index 50-100gigabytes per day depending the data sources and load from searching. If you have terabytes a day you can linearly scale a single, logical Splunk deployment by adding index servers, using Splunk’s built in forwarderload balancing to distribute the data and using distributed search to provide a single view across all of these servers. Unlike some log management products you get full consolidated reporting and alerting not simply merged query results. When in doubt, the first rule of scaling is ‘add another commodity indexer.’ Splunk indexers are designed to enable nearly limitless fan-out with linear scalability by leveraging techniques like MapReduce to fan-out work in a highly efficient manner.
Leverage distributed search to give each locale access to their own data, while providing a combined view to central teams back at headquarters. Whether to optimize your network traffic or meet data segmentation requirements, feel free to build your Splunk infrastructure as it makes sense for your organization. Further, each distributed search head automatically creates the correct app and user context while searching across other datasets. No specific custom configuration management is required; Splunk handles it for you.
The insights from your data are mission-critical. With Splunk Enterprise 5 we wanted to deliver a highly available system, with enterprise-grade data resiliency, even as you scale on commodity storage. And we wanted to maintain Splunk’s robust, real-time and ease of use features.Splunk indexers can now be grouped together to replicate each other’s data, maintaining multiple copies of all data – preventing data loss and delivering highly available data for Splunk search. Using index replication, if one or more indexers fail, incoming data continues to get indexed and indexed data continues to be searchable.By spreading data across multiple indexers, searches can read from many indexers in parallel, improving parallelism of operations and performance. All as you scale on commodity servers and storage. And without a SAN.
For high availability and scale out, combine auto load balancing with data cloning. Each clone group has one complete set of the overall data for redundancy, while load balancing within each clone group spreads the load and the data between indexers for efficient scaling. So long as one indexer remains in a clone group, that group will remain synced with the entirety of the data. Search Head Pooling can share the same application and user configurations and coordinate the scheduling of searches. This allows for one logical pool of search heads to service large numbers of users with minimal downtime should a search head become unavailable.Additionally, by leveraging LDAP authentication, such as Active Directory, users can be directed to any search head as needed for load balancing or failover. NOTE: the second indexers needs to be licensed with an HA license 50% of regular enterprise license
Splunk isn’t the only technology that can benefit from IT data collection, so let Splunk help send the data to those systems that need it. For those systems that want a direct tap into the raw data, Splunk can forward all or a subset of data in real time via TCP as raw text or RFC-compliant syslog. This can be done on the forwarder or centrally via the indexer without incrementing your daily indexing volume. Separately, Splunk can schedule sophisticated correlation searches and configure them to open tickets or insert events into SIEMs or operation event consoles. This allows you to summarize, mash-up and transform the data with the full power of the search language and import data into these other systems in a controlled fashion, even if they don’t natively support all the data types Splunk does. MSSP, Cloud Services, etc.
Your logs and other IT data are important but often cryptic. You can extend Splunk’s search with lookups to external data sources as well as automate tagging of hosts, users, sources, IP addresses and other fields that appear in your IT data. This enables you to find and summarize IT data according to business impact, logical application, user role and other logical business mappings. In the example shown, Splunk is looking up the server’s IP address to determine which domain the servicing web host is located in, and the customer account number to show which local market the customer is coming from. Using these fields, a search user could create reports pivoted on this information easily. Illustrate Lookups:
Splunk allows you to extend your existing AAA systems into the Splunk search system for both security and convenience. Splunk can connect to your LDAP based systems, like AD, and directly map your groups and users to Splunk users and roles. From there, define what users and groups can access Splunk, which apps and searches they have access to, and automatically (and transparently) filter their results by any search you can define. That allows you to not only exclude whole events that are inappropriate for a user to see, but also mask or hide specific fields in the data – such as customer names or credit card numbers – from those not authorized to see the entire event.
Centralized License Management provides for a holistic approach in your multi-indexer distributed Splunk environment. You can aggregate compatible licenses into stacks of available license volume and define pools of indexers to use license volume from a given stack.
Splunk deployments can grow to encompass thousands of Splunk instances, including forwarders, indexers, and search heads. Splunk offers a deployment monitor app that helps you to effectively manage medium- to large-scale deployments, keeping track of all your Splunk instances and providing early warning of unexpected or abnormal behavior.The deployment monitor provides chart-rich dashboards and drilldown pages that offer a wealth of information to help you monitor the health of your system. These are some of the things you can monitor:Index throughput over timeNumber of forwarders connecting to the indexer over timeIndexer and forwarder abnormalitiesDetails for individual forwarders and indexers, such as status and forwarding volume over timeSource types being indexed by the systemLicense usage
With thousands of enterprise customers and an order of magnitude more actual users, we have a thriving community.We launched a dev portal a few months back and already have over 1,000 unique visitors per week.We have over 300 apps contributed by ourselves, our partners and our community.Our knowledge exchange Answers site has over 20,000+ questions answered.And in August 2012 we ran our 3rd users’ conference with over 1,000 users in attendance, over 100 sessions of content, customers presenting.Best of all, this community demands more from Splunk and gives us incredible feedback