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SplunkLive! London 2016 Splunk Overview
Splunk is an industry-leading platform for machine data that allows users to access, analyze, and take action on data from any source. It uses universal indexing to ingest data in real-time from various sources without needing predefined schemas. This enables search, reporting, and alerting across all machine data. Splunk can scale to handle large volumes and varieties of data, provides a developer platform for customization, and supports both on-premises and cloud deployments.
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SplunkLive! London 2016 Splunk Overview
- 1. Copyright © 2016Splunk Inc. Splunk Overview
- 2. Agenda What is SplunkEnterprise? Deployment & Integration Real-Time Search, Alert & Reporting Universal Indexing Explained Splunk Developer Platform
- 3. Make machine dataaccessible, usable and valuable to everyone.
- 4. Industry Leading PlatformFor Machine Data Machine Data: Any Location, Type, Volume Platform Support (Apps / API / SDKs) Enterprise Scalability Universal Indexing Answer Any Question Custom dashboards Report and analyze Monitor and alert Developer Platform Ad hoc search Online Services Web Services Servers Security GPS Location Storage Desktops Networks Packaged Applications Custom ApplicationsMessaging Telecoms Online Shopping Cart Web Clickstreams Databases Energy Meters Call Detail Records Smartphones and Devices RFID On- Premises Private Cloud Public Cloud
- 5. Industry Leading PlatformFor Machine Data Machine Data: Any Location, Type, Volume Platform Support (Apps / API / SDKs) Enterprise Scalability Universal Indexing Answer Any Question Custom dashboards Report and analyze Monitor and alert Developer Platform Ad hoc search Online Services Web Services Servers Security GPS Location Storage Desktops Networks Packaged Applications Custom ApplicationsMessaging Telecoms Online Shopping Cart Web Clickstreams Databases Energy Meters Call Detail Records Smartphones and Devices RFID On- Premises Private Cloud Public Cloud Any amount, any location, any source Schema- on-the-fly Universal indexing No back-end RDBMS No need to filter data
- 6.
- 7. 1. 2. 3. 4. Simple Steps toDeploy Splunk Enterprise Download Install Forward Data Search Four steps: DatabasesNetworks Servers Virtual Machines Smartphones and Devices Custom Applications Security Web Server Sensors
- 8. Product Roles Searching andReporting (Search Head) Indexing and Search Services (Indexer) Data Collection and Forwarding (Forwarder) Data Governor (Cluster Master) Distributed Management (Deployment Server) DatabasesNetworks Servers Virtual Machines Smartphones and Devices Custom Applications Security Web Server Sensors
- 9. Scales to Hundredsof TBs/Day Enterprise-Class Scale, Resilience and Interoperability Send data from thousands of servers using any combination of Splunk Forwarders Auto load-balanced forwarding to Splunk Indexers Offload search load to Splunk Search Heads
- 10. 1. 2. 3. Simple Steps toDeploy Splunk Cloud Sign Up Forward Data Search Three steps: DatabasesNetworks Servers Virtual Machines Smartphones and Devices Custom Applications Security Web Server Sensors
- 11. Visibility Across Datacenters Distributedsearch unifies the view across locations Role-based access controls how far a given user's search will span New York Tokyo London Cloud
- 12. Ingests Data FromHeterogeneous Data Sources Agent-Less and Agent Approach for Flexibility and Optimization perf shell API Mounted File Systems hostnamemount syslog TCP/UDP Event Logs Performance Active Directory syslog hosts and network devices Unix, Linux and Windows hosts Local File Monitoring Splunk Forwarder virtual host Windows Scripted or Modular Inputs shell scripts, API subscriptions Mainframes*nix Wire Data Splunk App for Stream DevOps/IoT HTTP Event Collector
- 13. Forwards Events toThird-Party Systems Service Desk Event Console SIEM RAW Formatted
- 14. REPLICATION Delivers Mission-Critical Availability •Data replication – maintain searchability even if servers go down • Multi-site capable – maintain searchability even if a site goes down • Search Affinity – optimizes searches by fetching from the closest/fastest location Clustering Portland Datacenter New York Datacenter
- 15. Integrates with Third-PartyBusiness Tools Analyst Splunk admin Requirement s STEP 1 Business user communicates data requirements to Splunk admin STEP 2 Splunk admin authors saved searches in Splunk Enterprise thereby making the searches available to ODBC driver STEP 3 Business user uses tool to access saved searches and retrieve data from Splunk Enterprise ODBC driver (SQL to SPL translation layer) Analyst Saved Searches
- 16. Real-Time Search, Alerting &Reporting
- 17. Turn Machine DataInto Operational Intelligence Answer Any Question Platform Support (Apps / API / SDKs) Enterprise Scalability Universal Indexing Custom Dashboards Report and Analyze Monitor and Alert Developer Platform Ad hoc Search
- 18. Search All YourMachine Data • Real-time and historical data on- premises, in the cloud or both • Over 140 commands including anomaly detection and machine learning Data ParsingQueue Parsing Pipeline • Source, event typing • Character set normalization • Line breaking • Timestamp identification • Regex transforms Indexing Pipeline Real- Time Buffer Raw Data Index Files Real- Time Search Process Monitor Input IndexQueue TCP/UDP Input Scripted Input Splunk Index Search all your data Results right away Schema-on-the-fly
- 19.
- 20. Extract Fields Anytime •Highlight-to-extract multiple fields at once • Apply keyword search filters • Specify required text in extractions • View diverse and rare events • Validate extracted values with field stats Simple field extraction
- 21. Enrich Raw Datato Make It More Meaningful Create additional fields from the raw data with a lookup to an external data source LDAP, AD Watch Lists CRM/ERP CMDB External Data Sources Insight comes out Data goes in
- 22. Actionable Alerting Alerts • Createalerts based on any search • Customize content and format of email alerts • Trigger a script • Custom Alert Actions – Allows packaged integration with third-party applications – Enable custom workflows – Developers can build, package and publish alert actions
- 23. Reports Dynamic Reporting Chart onany search Choose visualization Save as a report • Visually represent the results of a search • Run on an ad hoc basis or save the report to view later • Share it with others on the team or a different group • Add reports to a new or existing dashboard
- 24. Custom Visualizations • Openframework to create or customize any visual • Visuals shared via Splunkbase library • Available for any use: search, dashboards, reports • Visuals for IT, security, IoT and business analytics Visualize Any Data
- 25. Define Relationships inMachine Data Data Model • Describes how underlying machine data is represented and accessed • Defines meaningful relationships in the data • Enables single authoritative view of underlying raw data Hierarchical object view of underlying data Add constraints to filter out events
- 26. Transparent Acceleration ● Automaticallycollected – Handles timing issues, backfill… ● Automatically maintained – Uses acceleration window ● Stored on the indexers – Peer to the buckets ● Fault tolerant collection Time window of data that is accelerated Check to enable acceleration of data model High Performance Analytics Store
- 27. Event Sampling • Powerfulsearch option provides unbiased sample results • Useful to quickly determine dataset characteristics • Speeds large-scale data investigation and discovery Sample Random Events
- 28. Easy-to-Use Analytics ● Drag-and-dropinterface enables any user to analyze data ● Create complex queries and reports without learning search language ● Click to visualize any chart type; reports dynamically update when fields change Select fields from data model Time window All chart types available in the chart toolbox Save report to share Pivot
- 29. Combine Reports toCreate Dashboards Use the built-in dashboard editor Or embed the reports into external sites like a wiki
- 30.
- 31. Inside Universal Indexing Accuratesearching and trending by time across all data Automatic event boundary identification Automatic timestamp normalization
- 32.
- 33. Preview and ConfigureData Select or create sourcetype Set desired parameters
- 34. FrozenWARM COLDHOT Index How theData is Stored and Aged in Splunk Hot – Newest buckets of data that are still open for write Warm – Recent data but closed for writing (read only) Cold – Oldest data, commonly on cheaper, slower storage Frozen – No longer searchable, commonly archived or deleted data Optional TSIDX Reduction
- 35. Extend storage withHDFS or AWS S3 Hadoop ClustersWARM COLD FROZEN Drive Down Costs by Archiving Historical Data to Commodity Hardware • Archive historical data to Hadoop or S3 • Unified search across all data in real time • Also analyze archived data using Hadoop tools
- 36.
- 37. Powerful Developer Platform RESTAPI Build Splunk Apps Extend and Integrate Splunk Simple XML JavaScript HTML5 Web Framework Java JavaScript Python Ruby C# PHP Data Models Search Extensibility Modular Inputs SDKs
- 38. Accelerate Your Deployment Apps– Leverage packaged searches and dashboards already built on top of Splunk Education – Focused training programs online or in a classroom Professional Services – Harness the knowledge and speed of the experts Cloud – No need to wait for infrastructure, use Splunk AMIs or Splunk Cloud
- 39. Summary ● Real-Time Architecture ●Schema-on-the-fly ● Massive Scalability ● Easy Reporting and Analytics ● Platform for All Machine Data
- 40.
Editor's Notes
- #4 As a company our mission is to make machine data accessible, usable and valuable to everyone. This overarching mission is what drives our company and product priorities.
- #5 Splunk is the platform for machine data, it digests all machine data and allow users to quickly analyze their data and rapidly obtain insight. The platform was designed around the premise of being able to consume any machine data even if the format changes. A relational database would cannot effectively support constantly changing underlying schemas. Splunk solves this by creating a schema on the fly… Splunk Cloud is only available in the U.S. and Canada.
- #6 Splunk is the platform for machine data, it digests all machine data and allow users to quickly analyze their data and rapidly obtain insight. The platform was designed around the premise of being able to consume any machine data even if the format changes. A relational database would cannot effectively support constantly changing underlying schemas. Splunk solves this by creating a schema on the fly… Splunk Cloud is only available in the U.S. and Canada.
- #8 It only takes minutes to download and install Splunk on the platform of your choice. Once Splunk has been downloaded and installed the next step is to forward data to the Splunk instance. At that point all data is searchable from a single place! Since Splunk stores a copy of the raw data, searches won’t affect the end devices. Having a central place to search your data not only simplifies things, it also decreases risk since a user doesn’t have to log into the end devices. The software can be installed on a single small instance, such as a laptop, or installed on multiple servers to scale as needed. When installed on multiple servers the functions can be split up to meet any performance, security, or availability requirements.
- #9 These are the five logical roles, a Splunk instance can be one or more of the roles. The search head is what most users interact with. It 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 or our API. Additional search heads can be deployed to scale with user or search load. 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 secure 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. The Splunk forwarder is an optional component that can be installed to forward data from servers, desktops, mainframes, and even ARM based devices. There are two types of forwarders; 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. The Cluster Master coordinates which indexers have copies of which buckets to ensure we have met the proper number of replication and searchable copies of each bucket. All clustered Indexers check in with the Master to alert them of their status, and the status of each of their replicated indexes and buckets. We will talk more about buckets later. And at the bottom there is the there is the Deployment Server, which can be used to manage your distributed Splunk environment. 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.
- #10 By allowing Splunk Enterprise to be split into multiple roles, any portion of Splunk can be scaled as needed. Customers are using Splunk to index hundreds of TB/s a day and search over petabytes of data. Splunk can take a single search and query as many indexers as are needed to complete the job, allowing you to use inexpensive commodity hardware in massively parallel clusters. Besides achieve massive scale, splitting the roles enabled user to meet location and data segmentation requirements.
- #11 If you're looking for all the benefits of Splunk Enterprise with all the benefits of software-as-a-service, then look no further. Splunk Cloud is backed by a 100% uptime SLA, scales to over 10TB/day, and offers a highly secure environment. It makes life easy so you can go home early. Steps to deploy are even simpler as all you need to do is signup, forward your data, and search! Splunk Cloud delivers all the features of award-winning Splunk Enterprise, as a cloud-based service. The platform provides access to Splunk Enterprise Security and the Splunk App for AWS and enables centralized visibility across cloud, hybrid and on-premises environments. Instant: Instant trial and instant conversion from POC to production. Secure: Completed SOC2 Type 2 Attestation*. Dedicated cloud environments for each customer. Reliable: 100% uptime SLA. All the features of Splunk Enterprise, including apps, APIs, SDKs. 10TB+/day scalability and up to 10x bursting over licensed data volumes**. Hybrid: Centralized visibility across Splunk Cloud (SaaS) and Splunk Enterprise (software) deployments.
- #12 Searches can be distributed from a single search head to any number of indexers. These indexers can all be local for massive parallelization for Big Data problems, or spread across a global enterprise to help you keep data wherever makes the most sense for your network, availability, and security requirements. Splunk Enterprise can be deployed on premise, in the cloud, or a combination of both. There is also an Amazon Machine Image available or if you don’t want to host or administer Splunk, it can be managed as a service by our experts using “Splunk Cloud”.
- #13 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 machine data, all that remains is how to collect and ship the data to your Splunk. There are many options. When Splunk is running locally as an indexer or lightweight 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 and more.
- #14 Splunk isn’t the only technology that can benefit from collecting machine data, 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.
- #15 Splunk’s clustering technology allows you to choose how many raw copies and searchable copies of your data you would like to keep. It also allows you to chose which indexers you want to store the copies on. This capability allows servers or even datacenters to go down without losing the ability to access the data. In addition, the search affinity capability allows users to fetch data from the closest or fastest location where there is a copy of the data which can not only save the time it takes to do a search but bandwidth by eliminating the need to use the WAN when there is a local copy.
- #16 Splunk ODBC Driver lets you interact with, manipulate and visualize machine data stored in Splunk Enterprise using existing business software tools, such as Microsoft Excel or Tableau Desktop. This flexibility gives you the features available in Excel or Tableau Desktop as well as the advanced analytics capabilities of Splunk Enterprise. Splunk Administrators need to create saved searches once. Business users then use a tool they are already familiar with to access those saved searches. Time savings and increased productivity are benefits everyone experiences.
- #18 Searching and reporting allows you to turn machine data into operational intelligence After the data has been indexed, users can : Search and Investigate using the Splunk Processing Language or Pivot Add knowledge with lookups and data models Monitor and Alert based on their needs And of course, build reports and analyze the data. Let’s take a look at each of these. Splunk Cloud is only available in the U.S. and Canada.
- #19 Allows you to search all your data in one place in real time. The search interface operates very similar to doing a search on any web search engine. Any user can become powerful very quickly with preexisting knowledge of using a search engine; however, Splunk has created over 100 commands (135 published) to make analyzing the data quicker and easier. <This is a great time to start a demo and show the search language if giving a demo> The schema on the fly approach is a key differentiator with Splunk.
- #20 Applying a schema at the last possible moment allows for the greatest flexibility when asking questions of your data. Splunk enterprise will atomically extract the values from the fields in events. If the data source is updated and new fields are added or the format of the events change Splunk does not need to re-index the data.
- #21 If Splunk doesn’t automatically extract the fields you desire you can simply select the fields and add them for future searches. Sometimes the raw event doesn’t contain useful enough information and it needs to be enriched….
- #22 The data for example may have a userid but you want to search on a name. Splunk’s lookup capability can enrich the raw data by adding additional fields at search time by. Some common use cases including event and error code description fields. Think “Page not Found” instead of “404”. Enriching your data can lead to entirely new insight. In the example shown, Splunk took the userid and looked up the name and role of the user from an HR database. Similarly, it determined the location of the failed log in attempt by correlating the IP address. Even though these fields don’t exist in the raw data, Splunk allows you to search or pivot on them at any time. You can also mask data. For example, you may want social security numbers to be replaced with all X’s for regular users but not masked for others. Removing data can also be useful, such as filtering PII, before writing it to an index in Splunk.
- #23 Alerts are triggered when certain conditions are met by the results of the search upon which it is based. Alerts can be based on both historical and real-time searches. When an alert is triggered, it performs an alert action. This action can be the sending of the alert information to a designated set of email addresses, or the posting of the alert information to an RSS feed. Alerts can also be set up to run a custom script when they are triggered. You can base these alerts on a wide range of threshold and trend-based scenarios, including empty shopping carts, brute force firewall attacks, and server system errors.
- #25 Release 6.4 delivers an array of new pre-built visualizations, a visualization developer framework, and an open library to make it simple for customers to access, develop and share interactive visualizations More than a dozen pre-built visualizations help customers analyze and interact with data sets commonly found in IT, security, and machine learning analysis A new developer framework allows customers and partners to easily create or customize any visualization to suit their needs Splunkbase now contains a growing library of visualizations provided by Splunk, our partners and our community Doubles the visualizations in Splunk today and creates an open environment for the unlimited creation and sharing of new visualizations Once a visual is imported from SplunkBase it is treated the same as any native Splunk feature, and is available for general use in the Visualizations dropdown.
- #26 Data Models are created using the Data Model Builder and are usually designed and implemented by users who understand the format and semantics of their indexed data, and who are familiar with the Splunk Search Processing Language (SPL). They define meaningful relationships in the data. Unlike data models in the traditional structured world, Splunk Data Models focus on machine data and data mashups between machine data and structured data. Splunk software is founded on the ability to flexibly search and analyze highly diverse machine data employing late-binding or search-time techniques for schematization (“schema-on-the-fly”). And Data Models are no exception. They define relationships in the underlying data, while leaving the raw machine data intact, and map these relationships at search time. They are therefore highly flexible and designed to enable users to rapidly iterate. Security is also a key consideration and data models are fully permissionable in Splunk 6.
- #27 Data Models are accelerated using the High Performance Analytics Store, new in Splunk 6. The High Performance Analytics Store represents a breakthrough innovation from Splunk that dramatically accelerates analytical operations across massive data sets by up to 1000x over Splunk 5. The Analytics Store contain a separate store of pre-extracted values derived from the underlying Splunk index. This data is organized in columns for rapid retrieval and powers dramatic improvements in the performance of analytical operations. Once created the Analytics Store is used seamlessly by Data Models and in turn the Pivot interface. For users more comfortable with the Splunk Search Processing Language (SPL), The Analytics Store can also be used directly in the search language. The Splunk Analytics Store is different from traditional Columnar databases – it is based on the Splunk lexicon and optimized for data retrieval (versus updates) by the Splunk Data Model or directly from the Splunk Search Processing Language. With the Analytics Store, Splunk Enterprise now uniquely optimizes data retrieval for both rare term searches and now analytical operations all in the same software platform. The new Pivot interface, combined with Data Models and the Analytics Store makes it dramatically easier for non-technical users and technical users alike to analyze and visualize data in Splunk and represent an important step towards Splunk’s mission of making machine data accessible, usable and valuable to everyone.
- #28 Sometimes you don't need accelerated data, rather you just need a sample over time for example to see a trend. Event Sampling makes it faster to characterize very large datasets and focus your investigations. It is an integrated option of Search, offering a dropdown menu to control sampling 1 per 10, per 100, 1000, 10,000 or a custom value. This can make searches exponentially faster.
- #29 The Pivot interface enables non-technical and technical users alike to quickly generate sophisticated charts, visualizations and dashboards using simple drag and drop and without learning the Search Processing Language (SPL). Users can access different chart types from the Splunk toolbox to easily visualize their data different ways. Queries using the Pivot interface are powered by underlying “data models” which define the relationships in Machine Data.
- #30 After reports have been created either via search or pivot they can be combined to create a dashboard. Reports can even been embedded into other webpages such as an wiki or SharePoint. This allows you to share reports with users who may not even have a Splunk account. If the native dashboarding capabilities aren’t enough, the Splunk Web Framework, REST API, and SDKs can be leveraged to meet the needs of almost any imagination.
- #32 To build an index on the data, Splunk Enterprise will first take the raw data, compress it, and put it in “buckets”. It will also perform a number of actions, including: Configuring character set encoding. Identifying line termination using linebreaking rules. While many events are short and only take up a line or two, others can be long. Identifying timestamps or creating them if they don't exist. At the same time that it processes timestamps, Splunk identifies event boundaries. Extracting a set of default fields for each event, including host, source, and sourcetype.
- #33 When running a search, the search head will fetch the events from disk which could be from multiple indexers, then it will sort and summarize the events, and format into the final results as requested before displaying it to the user. Splunk Enterprise search is incredibly powerful because it….
- #34 A sourcetype is simply a default field that identifies the type of the event and information about the event, such as what is the beginning or end of an event and where the timestamp is or which timestamp to use if the data has multiple. It's important that you assign the right source type to your data. That way, the indexed version of the data will look the way you expect it to, with appropriate timestamps and event breaks. This will make it a lot easier to search your data later on. For the most part, it's pretty easy to assign the right source type to your data. Splunk Enterprise comes with a large number of predefined source types. When consuming data, Splunk Enterprise will usually select the correct source type automatically. Sometimes, though, Splunk Enterprise needs your help. In such a case, tpreview capability, as shown in the images here, can be used to set or create a custom sourcetype.
- #35 As the data ages it will transition between hot, warm, and cold buckets. Each index can be configured to move the data based on amount of disk used or the age of the data. For example, there may be a mandate to keep security data for 7 years, but only the last year is ever really searched. The data older than a year can be sent to cheaper disks (or even archived on tape). TSIDX Reduction (Optional) – For more information see Slide 42 in the Appendix. In 6.4 Users have the ability to reduce Splunk performance optimization data (TSIDX) files – yielding a smaller footprint. 40-80% reduction in data footprint No functionality loss Limited performance tradeoff
- #36 Splunk Enterprise customers can drive down their TCO by archiving historical data to Hadoop on commodity hardware. Store old data cheaper in Hadoop commodity batch storage instead of SANs Archive buckets to Hadoop (HDFS) instead of freezing buckets or throwing data away
- #38 BUILD SPLUNK APPS The Splunk Web Framework makes building a Splunk app looks and feels like building any modern web application. The Simple Dashboard Editor makes it easy to BUILD interactive dashboards and user workflows as well as add custom styling, behavior and visualizations. Simple XML is ideal for fast, lightweight app customization and building. Simple XML development requires minimal coding knowledge and is well-suited for Splunk power users in IT to get fast visualization and analytics from their machine data. Simple XML also lets the developer “escape” to HTML with one click to do more powerful customization and integration with JavaScript. Developers looking for more advanced functionality and capabilities can build Splunk apps from the ground up using popular, standards-based web technologies: JavaScript and HTML5. The Splunk Web Framework lets developers quickly create Splunk apps by using prebuilt components, styles, templates, and reusable samples as well as supporting the development of custom logic, interactions, components, and UI. Developers can choose to program their Splunk app using Simple XML, JavaScript or HTML5 (or any combination thereof). EXTEND AND INTEGRATE SPLUNK Splunk Enterprise is a robust, fully-integrated platform that enables developers to INTEGRATE data and functionality from Splunk software into applications across the organization using Software Development Kits (SDKs) for Java, JavaScript, C#, Python, PHP and Ruby. These SDKs make it easier to code to the open REST API that sits on top of the Splunk Engine. With almost 200 endpoints, the REST API lets developers do programmatically what any end user can do in the UI and more. The Splunk SDKs include documentation, code samples, resources and tools to make it faster and more efficient to program against the Splunk REST API using constructs and syntax familiar to developers experienced with Java, Python, JavaScript, PHP, Ruby and C#. Developers can easily manage HTTP access, authentication and namespaces in just a few lines of code. Developers can use the Splunk SDKs to: - Run real-time searches and retrieve Splunk data from line-of-business systems like Customer Service applications - Integrate data and visualizations (charts, tables) from Splunk into BI tools and reporting dashboards - Build mobile applications with real-time KPI dashboards and alerts powered by Splunk - Log directly to Splunk from remote devices and applications via TCP, UDP and HTTP - Build customer-facing dashboards in your applications powered by user-specific data in Splunk - Manage a Splunk instance, including adding and removing users as well as creating data inputs from an application outside of Splunk - Programmatically extract data from Splunk for long-term data warehousing Developers can EXTEND the power of Splunk software with programmatic control over search commands, data sources and data enrichment. Splunk Enterprise offers search extensibility through: - Custom Search Commands - developers can add a custom search script (in Python) to Splunk to create own search commands. To build a search that runs recursively, developers need to make calls directly to the REST API - Scripted Lookups: developers can programmatically script lookups via Python. - Scripted Alerts: can trigger a shell script or batch file (we provide guidance for Python and PERL). - Search Macros: make chunks of a search reuseable in multiple places, including saved and ad hoc searches. Splunk also provides developers with other mechanisms to extend the power of the platform. - Data Models: allow developers to abstract away the search language syntax, making Splunk queries (and thus, functionality) more manageable and portable/shareable. - Modular Inputs: allow developers to extend Splunk to programmatically manage custom data input functionality via REST.
- #39 The reports and dashboards can be bundled into “Splunk Apps” which can be downloaded and shared. Hundreds of apps are available at apps.splunk.com, the large majority of which are free. Multiple education options are available: Virtual: Instructor Led Public Classes Virtual: Instructor Led Dedicated Classes Classroom: Instructor Led Public Classes Classroom: Dedicated Onsite eLearning: Self-Paced Learning Custom Designed Solutions Professional Services can certainly help you deploy faster but also provides a variety of other services: Implementation services over the full deployment lifecycle System health optimization and best practices reviews Deployment workshops Upgrade services Splunk Cloud is the enterprise service enables you to use Splunk without having to wait for hardware or staffing resources.