SlideShare a Scribd company logo
1 of 65
Copyright © 2015 Splunk Inc.
Splunk @ Level++
Steve Dvorak
2
Customer Discovery
2
• Activity brief in the box folder:
– https://splunk.box.com/SLPhx
• In the room:
– Door2door’s Splunk Architect (Steve)
– Splunk SE (Nate)
3
Splunk at the Next Level
Time to move beyond initial Splunk environment
• More use cases – how to tackle?
• More data – how do we scale?
• Splunk is mission critical == HA
• Global deployments
• Splunk user experience Screenshot here
4
Agenda
Use cases  Business Cases
Simple Scaling
Indexer Clustering (+Cross-site Clustering, Search Affinity)
Search Head Clustering
Distributed Management Console
Centralized Configuration Management
Splunk Cloud & Hybrid Deployments
Architecture workshop
Q&A
5
Growing your Splunk Deployment
Many customers start with a single use case…
• Ex: Monitor the web servers
• Help ensure up-time & response times
• Track usage, errors
• Provides business value
6
Growing your Splunk Deployment
Value statement for each overall service
Your services exist in a larger context than just one app, or one tier.
What is the value of the service as a whole?
What are CIO commitments for the service?
• The company’s web store is one of the most critical parts of the business.
• Performance of the overall environment must be maintained at all times.
• Failures in any portion of the web store must be quickly identified, send
notification to the appropriate parties.
• Dependencies on external processes must be monitored as well.
7
Growing your Splunk Deployment
The larger context
• Failure in one system cascades
• Map dependencies, estimate costs
• Use Splunk to track all dependencies.
• What happens when it is down?
Dependencies often include:
• Networking dependencies
• Shared storage
• Databases, middleware, custom apps
• Virtualization layer
Screenshot here
8
Scaling
Multiple factors
Indexer: IOPs, daily rate
Storage: Usage & retention
Search Head usage
9
Scaling - Indexers
Sizing for index performance
Indexers are usually storage-bound
Indexers: 150 to 250 GB per day each. (With suitable storage)
Ref HW: 12 cores (2 GHz+), 12 GB RAM, 800+ IOPs
Optimal HW (normal disk): 16 CPU cores, 48 GB RAM
Optimal HW (SSD): 24 CPU cores, 132 GB RAM
Questions?
10
SSD Advantage
http://blogs.splunk.com/2012/05/10/quantifying-the-benefits-of-
splunk-with-ssds/
• Low cost random seeks
• Writes are not that much faster – no great improvement with Indexing
• Significant improvements with Sparse/needle-haystack searches
• Dense searches become CPU bound
• Searches run faster allowing for more completed searches/min
11
Scaling - Storage
Simple storage to complex
Raw data rate  net compression of ~ 50% on disk.
Simple: rate * compression * retention
200 GB / day * 50% * 100 days = 10TB
Consider cold storage on NAS
– Changes storage story.
– Retention on fast, retention on slow
Clustering
– Changes storage story
12
Scaling - Storage
Sizing Calculator: http://splunk-sizing.appspot.com/
13
Scaling - Storage
RAID + SSD deep dive
• For spinning disks, Splunk recommends RAID 1+0 with 1k IOPs
• SSDs provide extremely high IOPs (45,000 +)
• RAID 5 SSD arrays give great Splunk performance in most
scenarios.
Additional details: Splunk Docs, Capacity Planning Manual
15
Indexer Clustering
High-Availability, Out of the Box
Splunk indexer clustering
Active-Active= better performance
Specific terms:
– Master Node
– Peer Node
– Search Factor
– Replication Factor
Additional details: Splunk Docs, Distributed Deployment Manual
16
Cross-site Clustering
Search Affinity by location
“Search locally”, “Store Globally”
DR scenarios
17
Scaling the Search Heads
Splunk Search is critical, too!
Splunk Search high availability needs
Scale to handle # of concurrent queries
18
SHP vs SHC
SHC
• SHP
• Available since v4.2
• Sharing configurations through NFS
• Single point of failure
• Performance issues
• No NFS
• Replication using local storage
• Commodity hardware
NFS
19
Search Head Clustering
20
Search Head Clustering
Use “Captain” for Master to avoid confusion with Index-Clustering
Minimum 3 nodes required. Odd is always preferred.
Cluster takes certain key decisions based on *majority* (consensus)
In multi-site setup have more nodes in main datacenter
21
Distributed Management Console
Manage Splunk 6.2 environments
Replaces Deployment Monitor App
Incorporates SOS app prior to 6.2
22
Deployment Server
Central management of Splunk Forwarders
Deployment Server manages Apps, Configs
Select one or more classes for each host
Class defines apps & configs
Works by phone-home
Notes:
DS does not push forwarder binaries
Use Cluster Master to manage indexers in cluster, not DS
23
Cloud & Hybrid
Scale without waiting for hardware
24
25
Discovery
2
• 1Tb/day peak ingest
• Up to 50 concurrent users
• All data is being generated from a single data center
• Fault tolerant design for high availability of Splunk
• 90 days data retention
• Standard hardware models in the Activity Brief
Forwarding Architecture
27
Forwarding Tier
2
Design Factors
• Syslog Collectors (HA)
• DBConnect Inputs
– McAfee EPO data
• TA Inputs
– CheckPoint
• Assorted Inputs
– Microsoft AD logs
– MicroSoft Exchange Server
– Microsoft Sharepoint logs
– Log4j, Linux, IIS
28
Syslog Collectors
2
• Best Practice to use dedicated syslog servers
• Syslog-NG/rSyslog recommended
• Syslog can write events to dedicated log files allowing for easy sourcetype classification on inputs
29
Syslog Collectors
2
• Using a Load Balancer/VIP
with Linux Heartbeat to
provide failover for the syslog
listener
• Syslog-NG PE Client-side
failover
High Availability
30
Forwarder for TA’s
3
• TA-McAfee requires DBConnect
to pull endpoint events
• TA-Checkpoint uses the LEA Client
to retrieve Firewall log events
• Not a HA design, but could be
hosted on a VM to standby or
failover
31
Deployment Server
3
● Deployment Server to manage Linux and
Windows forwarders
● Not a HA design, but could be hosted on a VM to
standby or failover
32
Forwarding Tier
3
33
Forwarding Tier BOM
3
Role Type Config #
Syslog Server F
4vCPU/12Gb/200
Gb
2
HWF E
2vCPU/8Gb/20G
b
1
Deployment
Server
F
4vCPU/12Gb/200
Gb
1
Load Balancer - - -
34
Forwarding Tier Design Best Practices
3
• Use a Syslog Server for Syslog data
• Be careful with Intermediate forwarders
– They can introduce bottlenecks
– Reduce the distribution of events across Indexers
• AutoLB will spread over all available indexers, but don’t assume
evenly!
– Enable forceTimebasedAutoLB
• May need to increase UF thruput setting for high velocity sources
– [thruput]
– maxKBps
Indexing Architecture
36
Indexing Tier
3
Design Factors
• 1 Tb/day (1000Gb/day) peak ingest
• High Availability – Indexer Replication
(RF=3/SF=2)
• 10% Disk Space Contingency
• 90 days minimum data retention
• • Cluster Sizing Calculator
• o http://splunk-
sizing.appspot.com
37
Storage Calculations
3
• RAID Configuration
– Amount of raw disk
– Fault tolerance
– Available IOPS
• Filesystem Overhead
– inodes consume space
• Wiggle room
– Additional replicated buckets when a node fails
– Unbalanced replicated buckets
• Splunk internal logs, Summary Indexes, Report Acceleration,
Accelerated Data Models
38
Indexer IOPS
3
•
39
Storage Types
3
• Local vs Direct Attached vs SAN vs NAS
• SSD/Flash vs Spinning Disk
– SSDs offer much higher IOPS with no latency
– Significant performance increases with Sparse Searches
40
Cluster Master Server
4
• Indexer Apps are deployed via CM
• Not a HA design, but could be hosted on a VM to standby or failover
41
Indexing Tier
4
42
Indexing Tier BOM – Solution A
4
Role Type Config #
Indexer A
16CPU/64Gb/12*
1Tb (RAID10)
20
Cluster Master F
4vCPU/12Gb/200
GB
1
43
Indexing Tier BOM – Solution B
4
Role Type Config #
Indexer C
24CPU/96Gb/6*8
00Gb(RAID6)+6*
2Tb(RAID10)
13
Cluster Master F
4vCPU/12Gb/200
GB
1
44
Indexing Tier Design Best Practices
4
• Depending on Searchload 100-250Gb max/idx/day***
• Max # of Indexes (indices) when clustering is enabled
45
How Clustering Affects Sizing
• Increased storage:
– 15% of raw usage for every replica copy
– 35% MORE to make that searchable
• Increased processing
– Incoming data to indexer is streamed to indexing peers to satisfy required
number of copies
• More hosts
– Need “replication factor” + 2 (search head, cluster master)
4
46
Benefits of Clustering
• Data redundancy
• Data availability
• Indexer resiliency
• Simpler management of indexers
• Simpler setup of distributed search
• Multi-site clustering allows site-specific search to reduce WAN traffic
4
47
Downsides of Clustering
• Increased Storage
• Extra machine (cluster master) required
• Increased bandwidth
• Hard to manage with DS (read: don’t)
4
Search Architecture
49
Search Tier
4
Design Factors
• High Availability
• Search Head Clustering
• # users
• # concurrent searches
• Forward all data to indexers
50
SHC & Deployer
5
• Search Head Cluster Apps need to be installed by the Deployer
• A minimum of 3 Search Heads are required for a SHC
• No Exchange or VMware app with SHC
– Anything leveraging tscollect based searches will need modification
51
Search Tier
5
52
Search Tier BOM
5
Role Type Config #
Search Head B
16CPU/64Gb/2*8
00Gb
3
Deployer E
2vCPU/8Gb/20G
b
1
License Server E
2vCPU/8Gb/20G
b
1
Load Balancer - - -
53
Search Tier Design Best Practices
5
• ES will still require a Separate Search Head or dedicated SHC
• Use LDAP/AD/SSO for user Authentication
• Load Balancer configured for sticky sessions
Final Design
55
Putting it all together
5
Migration
57
Hybrid Approach
5
• Add the existing Splunk
instance as a search peer
until the data retention
period has expired
• Disable scheduled searches
on the old instance
• Migrate any Summary
Index data to new Indexers
Review
59
Top 5 things to consider
5
• Indexer Storage requirements – Size and IOPS
• Minimum buy-in for a SHC is 3
• Use VMs for CM/LS/DS/Deployer if possible
• Consider a dedicated SH for a Distributed Management Console
• When in doubt – add another Indexer
60
How Apps Affect Sizing
• Enterprise Security – Requires a dedicated search head
• Don’t share hosts with other services
– Not co-located with Exchange, Active Directory, Hypervisors
• Don’t let anti-virus run on the Splunk partition
• Some data collection apps require a full instance (heavy forwarder)
– VMWare
– Checkpoint LEA
6
61
Sizing Considerations
• http://docs.splunk.com/Documentation/Splunk/latest/Installation/Cap
acityplanningforalargerSplunkdeployment
– Amount of incoming data
– Amount of indexed (stored) data
– Number of concurrent users
– Number of saved searches
– Types of searches
– Specific Splunk apps
• http://docs.splunk.com/Documentation/Splunk/latest/Installation/Perf
ormancechecklist
62
Required Reading
• Distributed Deployment Manual
– http://docs.splunk.com/Documentation/Splunk/latest/Deploy/Distributedoverv
iew
• Highlights
– Reference hardware specs
– How searches affect performance
 Dense / Rare / Sparse
– App considerations
– Summary table
6
63
63
The 6th Annual Splunk Worldwide Users’ Conference
• September 21-24, 2015
• The MGM Grand Hotel, Las Vegas
• 4000 IT & Business Professionals
• 2 Keynote Sessions
• 3 days of technical content
– 165+ sessions
• 3 days of Splunk University
– Sept 19-21, 2015
– Get Splunk Certified for FREE!
– Get CPE credits for CISSP, CAP, SSCP, etc.
– Save thousands on Splunk education!
• 80 Customer Speakers
• 80 Splunk Speakers
• 35+ Apps in Splunk Apps Showcase
• 65 Technology Partners
• Ask The Experts and Security Experts,
Birds of a Feather, Chalk Talks and a new
& improved Partner Pavilion!
• Register at conf.splunk.com
64 6
www.splunk.com/apptitude
July 20th, 2015 Submission deadline
65
We Want to Hear your Feedback!
After the Breakout Sessions conclude
Text Splunk PHX to 878787
And be entered for a chance to win a $100 AMEX gift card!
Thank You

More Related Content

What's hot

Deep Dive: Scaling Up to Your First 10 Million Users
Deep Dive: Scaling Up to Your First 10 Million UsersDeep Dive: Scaling Up to Your First 10 Million Users
Deep Dive: Scaling Up to Your First 10 Million UsersAmazon Web Services
 
Architecting-for-the-cloud-Best-Practices
Architecting-for-the-cloud-Best-PracticesArchitecting-for-the-cloud-Best-Practices
Architecting-for-the-cloud-Best-PracticesAmazon Web Services
 
Disaster Recovery Site on AWS - Minimal Cost Maximum Efficiency (STG305) | AW...
Disaster Recovery Site on AWS - Minimal Cost Maximum Efficiency (STG305) | AW...Disaster Recovery Site on AWS - Minimal Cost Maximum Efficiency (STG305) | AW...
Disaster Recovery Site on AWS - Minimal Cost Maximum Efficiency (STG305) | AW...Amazon Web Services
 
Intro to Amazon S3
Intro to Amazon S3Intro to Amazon S3
Intro to Amazon S3Yu Lun Teo
 
Build Data Engineering Platforms with Amazon EMR (ANT204) - AWS re:Invent 2018
Build Data Engineering Platforms with Amazon EMR (ANT204) - AWS re:Invent 2018Build Data Engineering Platforms with Amazon EMR (ANT204) - AWS re:Invent 2018
Build Data Engineering Platforms with Amazon EMR (ANT204) - AWS re:Invent 2018Amazon Web Services
 
Introduction to Amazon CloudFront - Pop-up Loft Tel Aviv
Introduction to Amazon CloudFront - Pop-up Loft Tel AvivIntroduction to Amazon CloudFront - Pop-up Loft Tel Aviv
Introduction to Amazon CloudFront - Pop-up Loft Tel AvivAmazon Web Services
 
Big Data Architectural Patterns and Best Practices on AWS
Big Data Architectural Patterns and Best Practices on AWSBig Data Architectural Patterns and Best Practices on AWS
Big Data Architectural Patterns and Best Practices on AWSAmazon Web Services
 
Presentation of Apache Cassandra
Presentation of Apache Cassandra Presentation of Apache Cassandra
Presentation of Apache Cassandra Nikiforos Botis
 
Amazon RDS & Amazon Aurora: Relational Databases on AWS - SRV206 - Atlanta AW...
Amazon RDS & Amazon Aurora: Relational Databases on AWS - SRV206 - Atlanta AW...Amazon RDS & Amazon Aurora: Relational Databases on AWS - SRV206 - Atlanta AW...
Amazon RDS & Amazon Aurora: Relational Databases on AWS - SRV206 - Atlanta AW...Amazon Web Services
 
Introduction to Amazon Kinesis Analytics
Introduction to Amazon Kinesis AnalyticsIntroduction to Amazon Kinesis Analytics
Introduction to Amazon Kinesis AnalyticsAmazon Web Services
 
Stream Processing – Concepts and Frameworks
Stream Processing – Concepts and FrameworksStream Processing – Concepts and Frameworks
Stream Processing – Concepts and FrameworksGuido Schmutz
 
Amazon EMR Deep Dive & Best Practices
Amazon EMR Deep Dive & Best PracticesAmazon EMR Deep Dive & Best Practices
Amazon EMR Deep Dive & Best PracticesAmazon Web Services
 
Kafka and Machine Learning in Banking and Insurance Industry
Kafka and Machine Learning in Banking and Insurance IndustryKafka and Machine Learning in Banking and Insurance Industry
Kafka and Machine Learning in Banking and Insurance IndustryKai Wähner
 
【AI:ML#16】Amazon Lexを用いたチャットボットの構築.pdf
【AI:ML#16】Amazon Lexを用いたチャットボットの構築.pdf【AI:ML#16】Amazon Lexを用いたチャットボットの構築.pdf
【AI:ML#16】Amazon Lexを用いたチャットボットの構築.pdfTakeshiFukae
 
Need for Time series Database
Need for Time series DatabaseNeed for Time series Database
Need for Time series DatabasePramit Choudhary
 
How Rovio Uses Amazon CloudFront for Secure API Acceleration (CTD315) - AWS r...
How Rovio Uses Amazon CloudFront for Secure API Acceleration (CTD315) - AWS r...How Rovio Uses Amazon CloudFront for Secure API Acceleration (CTD315) - AWS r...
How Rovio Uses Amazon CloudFront for Secure API Acceleration (CTD315) - AWS r...Amazon Web Services
 

What's hot (20)

Deep Dive: Scaling Up to Your First 10 Million Users
Deep Dive: Scaling Up to Your First 10 Million UsersDeep Dive: Scaling Up to Your First 10 Million Users
Deep Dive: Scaling Up to Your First 10 Million Users
 
Architecting-for-the-cloud-Best-Practices
Architecting-for-the-cloud-Best-PracticesArchitecting-for-the-cloud-Best-Practices
Architecting-for-the-cloud-Best-Practices
 
Disaster Recovery Site on AWS - Minimal Cost Maximum Efficiency (STG305) | AW...
Disaster Recovery Site on AWS - Minimal Cost Maximum Efficiency (STG305) | AW...Disaster Recovery Site on AWS - Minimal Cost Maximum Efficiency (STG305) | AW...
Disaster Recovery Site on AWS - Minimal Cost Maximum Efficiency (STG305) | AW...
 
Intro to Amazon S3
Intro to Amazon S3Intro to Amazon S3
Intro to Amazon S3
 
Build Data Engineering Platforms with Amazon EMR (ANT204) - AWS re:Invent 2018
Build Data Engineering Platforms with Amazon EMR (ANT204) - AWS re:Invent 2018Build Data Engineering Platforms with Amazon EMR (ANT204) - AWS re:Invent 2018
Build Data Engineering Platforms with Amazon EMR (ANT204) - AWS re:Invent 2018
 
Amazon Kinesis
Amazon KinesisAmazon Kinesis
Amazon Kinesis
 
Introduction to Amazon CloudFront - Pop-up Loft Tel Aviv
Introduction to Amazon CloudFront - Pop-up Loft Tel AvivIntroduction to Amazon CloudFront - Pop-up Loft Tel Aviv
Introduction to Amazon CloudFront - Pop-up Loft Tel Aviv
 
Big Data Architectural Patterns and Best Practices on AWS
Big Data Architectural Patterns and Best Practices on AWSBig Data Architectural Patterns and Best Practices on AWS
Big Data Architectural Patterns and Best Practices on AWS
 
Presentation of Apache Cassandra
Presentation of Apache Cassandra Presentation of Apache Cassandra
Presentation of Apache Cassandra
 
Amazon RDS & Amazon Aurora: Relational Databases on AWS - SRV206 - Atlanta AW...
Amazon RDS & Amazon Aurora: Relational Databases on AWS - SRV206 - Atlanta AW...Amazon RDS & Amazon Aurora: Relational Databases on AWS - SRV206 - Atlanta AW...
Amazon RDS & Amazon Aurora: Relational Databases on AWS - SRV206 - Atlanta AW...
 
Introduction to Amazon Kinesis Analytics
Introduction to Amazon Kinesis AnalyticsIntroduction to Amazon Kinesis Analytics
Introduction to Amazon Kinesis Analytics
 
Stream Processing – Concepts and Frameworks
Stream Processing – Concepts and FrameworksStream Processing – Concepts and Frameworks
Stream Processing – Concepts and Frameworks
 
AWS Kinesis
AWS KinesisAWS Kinesis
AWS Kinesis
 
Real-Time Streaming Data on AWS
Real-Time Streaming Data on AWSReal-Time Streaming Data on AWS
Real-Time Streaming Data on AWS
 
Amazon Aurora
Amazon AuroraAmazon Aurora
Amazon Aurora
 
Amazon EMR Deep Dive & Best Practices
Amazon EMR Deep Dive & Best PracticesAmazon EMR Deep Dive & Best Practices
Amazon EMR Deep Dive & Best Practices
 
Kafka and Machine Learning in Banking and Insurance Industry
Kafka and Machine Learning in Banking and Insurance IndustryKafka and Machine Learning in Banking and Insurance Industry
Kafka and Machine Learning in Banking and Insurance Industry
 
【AI:ML#16】Amazon Lexを用いたチャットボットの構築.pdf
【AI:ML#16】Amazon Lexを用いたチャットボットの構築.pdf【AI:ML#16】Amazon Lexを用いたチャットボットの構築.pdf
【AI:ML#16】Amazon Lexを用いたチャットボットの構築.pdf
 
Need for Time series Database
Need for Time series DatabaseNeed for Time series Database
Need for Time series Database
 
How Rovio Uses Amazon CloudFront for Secure API Acceleration (CTD315) - AWS r...
How Rovio Uses Amazon CloudFront for Secure API Acceleration (CTD315) - AWS r...How Rovio Uses Amazon CloudFront for Secure API Acceleration (CTD315) - AWS r...
How Rovio Uses Amazon CloudFront for Secure API Acceleration (CTD315) - AWS r...
 

Viewers also liked

Taking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout SessionTaking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout SessionSplunk
 
Taking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout SessionTaking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout SessionSplunk
 
Taking Splunk to the Next Level - Technical
Taking Splunk to the Next Level - TechnicalTaking Splunk to the Next Level - Technical
Taking Splunk to the Next Level - TechnicalSplunk
 
Splunk Enterprise 6.3 - Splunk Tech Day
Splunk Enterprise 6.3 - Splunk Tech DaySplunk Enterprise 6.3 - Splunk Tech Day
Splunk Enterprise 6.3 - Splunk Tech DayZivaro Inc
 
Taking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout SessionTaking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout SessionSplunk
 
Softcat Splunk Discovery Day Manchester, March 2017
Softcat Splunk Discovery Day Manchester, March 2017Softcat Splunk Discovery Day Manchester, March 2017
Softcat Splunk Discovery Day Manchester, March 2017Splunk
 
Taking Splunk to the Next Level – Architecture
Taking Splunk to the Next Level – ArchitectureTaking Splunk to the Next Level – Architecture
Taking Splunk to the Next Level – ArchitectureSplunk
 
Machine Learning + Analytics in Splunk
Machine Learning + Analytics in SplunkMachine Learning + Analytics in Splunk
Machine Learning + Analytics in SplunkSplunk
 
Splunk conf2014 - Getting Deeper Insights into your Virtualization and Storag...
Splunk conf2014 - Getting Deeper Insights into your Virtualization and Storag...Splunk conf2014 - Getting Deeper Insights into your Virtualization and Storag...
Splunk conf2014 - Getting Deeper Insights into your Virtualization and Storag...Splunk
 
Taking Splunk to the Next Level - Architecture
Taking Splunk to the Next Level - ArchitectureTaking Splunk to the Next Level - Architecture
Taking Splunk to the Next Level - ArchitectureSplunk
 
Taking Splunk to the Next Level - Architecture
Taking Splunk to the Next Level - ArchitectureTaking Splunk to the Next Level - Architecture
Taking Splunk to the Next Level - ArchitectureSplunk
 
Getting Started with Splunk Enterprise - Demo
Getting Started with Splunk Enterprise - DemoGetting Started with Splunk Enterprise - Demo
Getting Started with Splunk Enterprise - DemoSplunk
 
Got Big Data? Splunk on Nutanix
Got Big Data? Splunk on NutanixGot Big Data? Splunk on Nutanix
Got Big Data? Splunk on NutanixNEXTtour
 
SplunkSummit 2015 - Real World Big Data Architecture
SplunkSummit 2015 -  Real World Big Data ArchitectureSplunkSummit 2015 -  Real World Big Data Architecture
SplunkSummit 2015 - Real World Big Data ArchitectureSplunk
 
Best Practices for a CoE
Best Practices for a CoEBest Practices for a CoE
Best Practices for a CoESplunk
 
Webinar: Which Storage Architecture is Best for Splunk Analytics?
Webinar: Which Storage Architecture is Best for Splunk Analytics?Webinar: Which Storage Architecture is Best for Splunk Analytics?
Webinar: Which Storage Architecture is Best for Splunk Analytics?Storage Switzerland
 
Molina Healthcare Customer Presentation
Molina Healthcare Customer PresentationMolina Healthcare Customer Presentation
Molina Healthcare Customer PresentationSplunk
 
Getting Started with IT Service Intelligence
Getting Started with IT Service IntelligenceGetting Started with IT Service Intelligence
Getting Started with IT Service IntelligenceSplunk
 
Getting Started with Splunk Enterprise
Getting Started with Splunk EnterpriseGetting Started with Splunk Enterprise
Getting Started with Splunk EnterpriseSplunk
 
Ceph Introduction 2017
Ceph Introduction 2017  Ceph Introduction 2017
Ceph Introduction 2017 Karan Singh
 

Viewers also liked (20)

Taking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout SessionTaking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout Session
 
Taking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout SessionTaking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout Session
 
Taking Splunk to the Next Level - Technical
Taking Splunk to the Next Level - TechnicalTaking Splunk to the Next Level - Technical
Taking Splunk to the Next Level - Technical
 
Splunk Enterprise 6.3 - Splunk Tech Day
Splunk Enterprise 6.3 - Splunk Tech DaySplunk Enterprise 6.3 - Splunk Tech Day
Splunk Enterprise 6.3 - Splunk Tech Day
 
Taking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout SessionTaking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout Session
 
Softcat Splunk Discovery Day Manchester, March 2017
Softcat Splunk Discovery Day Manchester, March 2017Softcat Splunk Discovery Day Manchester, March 2017
Softcat Splunk Discovery Day Manchester, March 2017
 
Taking Splunk to the Next Level – Architecture
Taking Splunk to the Next Level – ArchitectureTaking Splunk to the Next Level – Architecture
Taking Splunk to the Next Level – Architecture
 
Machine Learning + Analytics in Splunk
Machine Learning + Analytics in SplunkMachine Learning + Analytics in Splunk
Machine Learning + Analytics in Splunk
 
Splunk conf2014 - Getting Deeper Insights into your Virtualization and Storag...
Splunk conf2014 - Getting Deeper Insights into your Virtualization and Storag...Splunk conf2014 - Getting Deeper Insights into your Virtualization and Storag...
Splunk conf2014 - Getting Deeper Insights into your Virtualization and Storag...
 
Taking Splunk to the Next Level - Architecture
Taking Splunk to the Next Level - ArchitectureTaking Splunk to the Next Level - Architecture
Taking Splunk to the Next Level - Architecture
 
Taking Splunk to the Next Level - Architecture
Taking Splunk to the Next Level - ArchitectureTaking Splunk to the Next Level - Architecture
Taking Splunk to the Next Level - Architecture
 
Getting Started with Splunk Enterprise - Demo
Getting Started with Splunk Enterprise - DemoGetting Started with Splunk Enterprise - Demo
Getting Started with Splunk Enterprise - Demo
 
Got Big Data? Splunk on Nutanix
Got Big Data? Splunk on NutanixGot Big Data? Splunk on Nutanix
Got Big Data? Splunk on Nutanix
 
SplunkSummit 2015 - Real World Big Data Architecture
SplunkSummit 2015 -  Real World Big Data ArchitectureSplunkSummit 2015 -  Real World Big Data Architecture
SplunkSummit 2015 - Real World Big Data Architecture
 
Best Practices for a CoE
Best Practices for a CoEBest Practices for a CoE
Best Practices for a CoE
 
Webinar: Which Storage Architecture is Best for Splunk Analytics?
Webinar: Which Storage Architecture is Best for Splunk Analytics?Webinar: Which Storage Architecture is Best for Splunk Analytics?
Webinar: Which Storage Architecture is Best for Splunk Analytics?
 
Molina Healthcare Customer Presentation
Molina Healthcare Customer PresentationMolina Healthcare Customer Presentation
Molina Healthcare Customer Presentation
 
Getting Started with IT Service Intelligence
Getting Started with IT Service IntelligenceGetting Started with IT Service Intelligence
Getting Started with IT Service Intelligence
 
Getting Started with Splunk Enterprise
Getting Started with Splunk EnterpriseGetting Started with Splunk Enterprise
Getting Started with Splunk Enterprise
 
Ceph Introduction 2017
Ceph Introduction 2017  Ceph Introduction 2017
Ceph Introduction 2017
 

Similar to Taking Splunk to the Next Level - Architecture Breakout Session

Taking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout SessionTaking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout SessionSplunk
 
Taking Splunk to the Next Level – Architecture
Taking Splunk to the Next Level – ArchitectureTaking Splunk to the Next Level – Architecture
Taking Splunk to the Next Level – ArchitectureSplunk
 
Taking Splunk to the Next Level - Architecture
Taking Splunk to the Next Level - ArchitectureTaking Splunk to the Next Level - Architecture
Taking Splunk to the Next Level - ArchitectureSplunk
 
Taking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout SessionTaking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout SessionSplunk
 
Benchmarking Solr Performance at Scale
Benchmarking Solr Performance at ScaleBenchmarking Solr Performance at Scale
Benchmarking Solr Performance at Scalethelabdude
 
Managing Security At 1M Events a Second using Elasticsearch
Managing Security At 1M Events a Second using ElasticsearchManaging Security At 1M Events a Second using Elasticsearch
Managing Security At 1M Events a Second using ElasticsearchJoe Alex
 
Scaling Hadoop at LinkedIn
Scaling Hadoop at LinkedInScaling Hadoop at LinkedIn
Scaling Hadoop at LinkedInDataWorks Summit
 
Revolutionary Storage for Modern Databases, Applications and Infrastrcture
Revolutionary Storage for Modern Databases, Applications and InfrastrctureRevolutionary Storage for Modern Databases, Applications and Infrastrcture
Revolutionary Storage for Modern Databases, Applications and Infrastrcturesabnees
 
Introducing Cloudian HyperStore 6.0
Introducing Cloudian HyperStore 6.0Introducing Cloudian HyperStore 6.0
Introducing Cloudian HyperStore 6.0Cloudian
 
Ceph Community Talk on High-Performance Solid Sate Ceph
Ceph Community Talk on High-Performance Solid Sate Ceph Ceph Community Talk on High-Performance Solid Sate Ceph
Ceph Community Talk on High-Performance Solid Sate Ceph Ceph Community
 
What's new in JBoss ON 3.2
What's new in JBoss ON 3.2What's new in JBoss ON 3.2
What's new in JBoss ON 3.2Thomas Segismont
 
Webinar: Faster Log Indexing with Fusion
Webinar: Faster Log Indexing with FusionWebinar: Faster Log Indexing with Fusion
Webinar: Faster Log Indexing with FusionLucidworks
 
Building a High Performance Analytics Platform
Building a High Performance Analytics PlatformBuilding a High Performance Analytics Platform
Building a High Performance Analytics PlatformSantanu Dey
 
InfluxEnterprise Architectural Patterns by Dean Sheehan, Senior Director, Pre...
InfluxEnterprise Architectural Patterns by Dean Sheehan, Senior Director, Pre...InfluxEnterprise Architectural Patterns by Dean Sheehan, Senior Director, Pre...
InfluxEnterprise Architectural Patterns by Dean Sheehan, Senior Director, Pre...InfluxData
 
Modeling, estimating, and predicting Ceph (Linux Foundation - Vault 2015)
Modeling, estimating, and predicting Ceph (Linux Foundation - Vault 2015)Modeling, estimating, and predicting Ceph (Linux Foundation - Vault 2015)
Modeling, estimating, and predicting Ceph (Linux Foundation - Vault 2015)Lars Marowsky-Brée
 
Hardware Provisioning
Hardware ProvisioningHardware Provisioning
Hardware ProvisioningMongoDB
 
HPC and cloud distributed computing, as a journey
HPC and cloud distributed computing, as a journeyHPC and cloud distributed computing, as a journey
HPC and cloud distributed computing, as a journeyPeter Clapham
 

Similar to Taking Splunk to the Next Level - Architecture Breakout Session (20)

Taking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout SessionTaking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout Session
 
Taking Splunk to the Next Level – Architecture
Taking Splunk to the Next Level – ArchitectureTaking Splunk to the Next Level – Architecture
Taking Splunk to the Next Level – Architecture
 
Taking Splunk to the Next Level - Architecture
Taking Splunk to the Next Level - ArchitectureTaking Splunk to the Next Level - Architecture
Taking Splunk to the Next Level - Architecture
 
Taking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout SessionTaking Splunk to the Next Level - Architecture Breakout Session
Taking Splunk to the Next Level - Architecture Breakout Session
 
Benchmarking Solr Performance at Scale
Benchmarking Solr Performance at ScaleBenchmarking Solr Performance at Scale
Benchmarking Solr Performance at Scale
 
Managing Security At 1M Events a Second using Elasticsearch
Managing Security At 1M Events a Second using ElasticsearchManaging Security At 1M Events a Second using Elasticsearch
Managing Security At 1M Events a Second using Elasticsearch
 
Scaling Hadoop at LinkedIn
Scaling Hadoop at LinkedInScaling Hadoop at LinkedIn
Scaling Hadoop at LinkedIn
 
Revolutionary Storage for Modern Databases, Applications and Infrastrcture
Revolutionary Storage for Modern Databases, Applications and InfrastrctureRevolutionary Storage for Modern Databases, Applications and Infrastrcture
Revolutionary Storage for Modern Databases, Applications and Infrastrcture
 
Introducing Cloudian HyperStore 6.0
Introducing Cloudian HyperStore 6.0Introducing Cloudian HyperStore 6.0
Introducing Cloudian HyperStore 6.0
 
Redshift overview
Redshift overviewRedshift overview
Redshift overview
 
Ceph Community Talk on High-Performance Solid Sate Ceph
Ceph Community Talk on High-Performance Solid Sate Ceph Ceph Community Talk on High-Performance Solid Sate Ceph
Ceph Community Talk on High-Performance Solid Sate Ceph
 
What's new in JBoss ON 3.2
What's new in JBoss ON 3.2What's new in JBoss ON 3.2
What's new in JBoss ON 3.2
 
BigData Developers MeetUp
BigData Developers MeetUpBigData Developers MeetUp
BigData Developers MeetUp
 
Webinar: Faster Log Indexing with Fusion
Webinar: Faster Log Indexing with FusionWebinar: Faster Log Indexing with Fusion
Webinar: Faster Log Indexing with Fusion
 
Building a High Performance Analytics Platform
Building a High Performance Analytics PlatformBuilding a High Performance Analytics Platform
Building a High Performance Analytics Platform
 
InfluxEnterprise Architectural Patterns by Dean Sheehan, Senior Director, Pre...
InfluxEnterprise Architectural Patterns by Dean Sheehan, Senior Director, Pre...InfluxEnterprise Architectural Patterns by Dean Sheehan, Senior Director, Pre...
InfluxEnterprise Architectural Patterns by Dean Sheehan, Senior Director, Pre...
 
Modeling, estimating, and predicting Ceph (Linux Foundation - Vault 2015)
Modeling, estimating, and predicting Ceph (Linux Foundation - Vault 2015)Modeling, estimating, and predicting Ceph (Linux Foundation - Vault 2015)
Modeling, estimating, and predicting Ceph (Linux Foundation - Vault 2015)
 
The state of SQL-on-Hadoop in the Cloud
The state of SQL-on-Hadoop in the CloudThe state of SQL-on-Hadoop in the Cloud
The state of SQL-on-Hadoop in the Cloud
 
Hardware Provisioning
Hardware ProvisioningHardware Provisioning
Hardware Provisioning
 
HPC and cloud distributed computing, as a journey
HPC and cloud distributed computing, as a journeyHPC and cloud distributed computing, as a journey
HPC and cloud distributed computing, as a journey
 

More from Splunk

.conf Go 2023 - Data analysis as a routine
.conf Go 2023 - Data analysis as a routine.conf Go 2023 - Data analysis as a routine
.conf Go 2023 - Data analysis as a routineSplunk
 
.conf Go 2023 - How KPN drives Customer Satisfaction on IPTV
.conf Go 2023 - How KPN drives Customer Satisfaction on IPTV.conf Go 2023 - How KPN drives Customer Satisfaction on IPTV
.conf Go 2023 - How KPN drives Customer Satisfaction on IPTVSplunk
 
.conf Go 2023 - Navegando la normativa SOX (Telefónica)
.conf Go 2023 - Navegando la normativa SOX (Telefónica).conf Go 2023 - Navegando la normativa SOX (Telefónica)
.conf Go 2023 - Navegando la normativa SOX (Telefónica)Splunk
 
.conf Go 2023 - Raiffeisen Bank International
.conf Go 2023 - Raiffeisen Bank International.conf Go 2023 - Raiffeisen Bank International
.conf Go 2023 - Raiffeisen Bank InternationalSplunk
 
.conf Go 2023 - På liv og død Om sikkerhetsarbeid i Norsk helsenett
.conf Go 2023 - På liv og død Om sikkerhetsarbeid i Norsk helsenett .conf Go 2023 - På liv og død Om sikkerhetsarbeid i Norsk helsenett
.conf Go 2023 - På liv og død Om sikkerhetsarbeid i Norsk helsenett Splunk
 
.conf Go 2023 - Many roads lead to Rome - this was our journey (Julius Bär)
.conf Go 2023 - Many roads lead to Rome - this was our journey (Julius Bär).conf Go 2023 - Many roads lead to Rome - this was our journey (Julius Bär)
.conf Go 2023 - Many roads lead to Rome - this was our journey (Julius Bär)Splunk
 
.conf Go 2023 - Das passende Rezept für die digitale (Security) Revolution zu...
.conf Go 2023 - Das passende Rezept für die digitale (Security) Revolution zu....conf Go 2023 - Das passende Rezept für die digitale (Security) Revolution zu...
.conf Go 2023 - Das passende Rezept für die digitale (Security) Revolution zu...Splunk
 
.conf go 2023 - Cyber Resilienz – Herausforderungen und Ansatz für Energiever...
.conf go 2023 - Cyber Resilienz – Herausforderungen und Ansatz für Energiever....conf go 2023 - Cyber Resilienz – Herausforderungen und Ansatz für Energiever...
.conf go 2023 - Cyber Resilienz – Herausforderungen und Ansatz für Energiever...Splunk
 
.conf go 2023 - De NOC a CSIRT (Cellnex)
.conf go 2023 - De NOC a CSIRT (Cellnex).conf go 2023 - De NOC a CSIRT (Cellnex)
.conf go 2023 - De NOC a CSIRT (Cellnex)Splunk
 
conf go 2023 - El camino hacia la ciberseguridad (ABANCA)
conf go 2023 - El camino hacia la ciberseguridad (ABANCA)conf go 2023 - El camino hacia la ciberseguridad (ABANCA)
conf go 2023 - El camino hacia la ciberseguridad (ABANCA)Splunk
 
Splunk - BMW connects business and IT with data driven operations SRE and O11y
Splunk - BMW connects business and IT with data driven operations SRE and O11ySplunk - BMW connects business and IT with data driven operations SRE and O11y
Splunk - BMW connects business and IT with data driven operations SRE and O11ySplunk
 
Splunk x Freenet - .conf Go Köln
Splunk x Freenet - .conf Go KölnSplunk x Freenet - .conf Go Köln
Splunk x Freenet - .conf Go KölnSplunk
 
Splunk Security Session - .conf Go Köln
Splunk Security Session - .conf Go KölnSplunk Security Session - .conf Go Köln
Splunk Security Session - .conf Go KölnSplunk
 
Data foundations building success, at city scale – Imperial College London
 Data foundations building success, at city scale – Imperial College London Data foundations building success, at city scale – Imperial College London
Data foundations building success, at city scale – Imperial College LondonSplunk
 
Splunk: How Vodafone established Operational Analytics in a Hybrid Environmen...
Splunk: How Vodafone established Operational Analytics in a Hybrid Environmen...Splunk: How Vodafone established Operational Analytics in a Hybrid Environmen...
Splunk: How Vodafone established Operational Analytics in a Hybrid Environmen...Splunk
 
SOC, Amore Mio! | Security Webinar
SOC, Amore Mio! | Security WebinarSOC, Amore Mio! | Security Webinar
SOC, Amore Mio! | Security WebinarSplunk
 
.conf Go 2022 - Observability Session
.conf Go 2022 - Observability Session.conf Go 2022 - Observability Session
.conf Go 2022 - Observability SessionSplunk
 
.conf Go Zurich 2022 - Keynote
.conf Go Zurich 2022 - Keynote.conf Go Zurich 2022 - Keynote
.conf Go Zurich 2022 - KeynoteSplunk
 
.conf Go Zurich 2022 - Platform Session
.conf Go Zurich 2022 - Platform Session.conf Go Zurich 2022 - Platform Session
.conf Go Zurich 2022 - Platform SessionSplunk
 
.conf Go Zurich 2022 - Security Session
.conf Go Zurich 2022 - Security Session.conf Go Zurich 2022 - Security Session
.conf Go Zurich 2022 - Security SessionSplunk
 

More from Splunk (20)

.conf Go 2023 - Data analysis as a routine
.conf Go 2023 - Data analysis as a routine.conf Go 2023 - Data analysis as a routine
.conf Go 2023 - Data analysis as a routine
 
.conf Go 2023 - How KPN drives Customer Satisfaction on IPTV
.conf Go 2023 - How KPN drives Customer Satisfaction on IPTV.conf Go 2023 - How KPN drives Customer Satisfaction on IPTV
.conf Go 2023 - How KPN drives Customer Satisfaction on IPTV
 
.conf Go 2023 - Navegando la normativa SOX (Telefónica)
.conf Go 2023 - Navegando la normativa SOX (Telefónica).conf Go 2023 - Navegando la normativa SOX (Telefónica)
.conf Go 2023 - Navegando la normativa SOX (Telefónica)
 
.conf Go 2023 - Raiffeisen Bank International
.conf Go 2023 - Raiffeisen Bank International.conf Go 2023 - Raiffeisen Bank International
.conf Go 2023 - Raiffeisen Bank International
 
.conf Go 2023 - På liv og død Om sikkerhetsarbeid i Norsk helsenett
.conf Go 2023 - På liv og død Om sikkerhetsarbeid i Norsk helsenett .conf Go 2023 - På liv og død Om sikkerhetsarbeid i Norsk helsenett
.conf Go 2023 - På liv og død Om sikkerhetsarbeid i Norsk helsenett
 
.conf Go 2023 - Many roads lead to Rome - this was our journey (Julius Bär)
.conf Go 2023 - Many roads lead to Rome - this was our journey (Julius Bär).conf Go 2023 - Many roads lead to Rome - this was our journey (Julius Bär)
.conf Go 2023 - Many roads lead to Rome - this was our journey (Julius Bär)
 
.conf Go 2023 - Das passende Rezept für die digitale (Security) Revolution zu...
.conf Go 2023 - Das passende Rezept für die digitale (Security) Revolution zu....conf Go 2023 - Das passende Rezept für die digitale (Security) Revolution zu...
.conf Go 2023 - Das passende Rezept für die digitale (Security) Revolution zu...
 
.conf go 2023 - Cyber Resilienz – Herausforderungen und Ansatz für Energiever...
.conf go 2023 - Cyber Resilienz – Herausforderungen und Ansatz für Energiever....conf go 2023 - Cyber Resilienz – Herausforderungen und Ansatz für Energiever...
.conf go 2023 - Cyber Resilienz – Herausforderungen und Ansatz für Energiever...
 
.conf go 2023 - De NOC a CSIRT (Cellnex)
.conf go 2023 - De NOC a CSIRT (Cellnex).conf go 2023 - De NOC a CSIRT (Cellnex)
.conf go 2023 - De NOC a CSIRT (Cellnex)
 
conf go 2023 - El camino hacia la ciberseguridad (ABANCA)
conf go 2023 - El camino hacia la ciberseguridad (ABANCA)conf go 2023 - El camino hacia la ciberseguridad (ABANCA)
conf go 2023 - El camino hacia la ciberseguridad (ABANCA)
 
Splunk - BMW connects business and IT with data driven operations SRE and O11y
Splunk - BMW connects business and IT with data driven operations SRE and O11ySplunk - BMW connects business and IT with data driven operations SRE and O11y
Splunk - BMW connects business and IT with data driven operations SRE and O11y
 
Splunk x Freenet - .conf Go Köln
Splunk x Freenet - .conf Go KölnSplunk x Freenet - .conf Go Köln
Splunk x Freenet - .conf Go Köln
 
Splunk Security Session - .conf Go Köln
Splunk Security Session - .conf Go KölnSplunk Security Session - .conf Go Köln
Splunk Security Session - .conf Go Köln
 
Data foundations building success, at city scale – Imperial College London
 Data foundations building success, at city scale – Imperial College London Data foundations building success, at city scale – Imperial College London
Data foundations building success, at city scale – Imperial College London
 
Splunk: How Vodafone established Operational Analytics in a Hybrid Environmen...
Splunk: How Vodafone established Operational Analytics in a Hybrid Environmen...Splunk: How Vodafone established Operational Analytics in a Hybrid Environmen...
Splunk: How Vodafone established Operational Analytics in a Hybrid Environmen...
 
SOC, Amore Mio! | Security Webinar
SOC, Amore Mio! | Security WebinarSOC, Amore Mio! | Security Webinar
SOC, Amore Mio! | Security Webinar
 
.conf Go 2022 - Observability Session
.conf Go 2022 - Observability Session.conf Go 2022 - Observability Session
.conf Go 2022 - Observability Session
 
.conf Go Zurich 2022 - Keynote
.conf Go Zurich 2022 - Keynote.conf Go Zurich 2022 - Keynote
.conf Go Zurich 2022 - Keynote
 
.conf Go Zurich 2022 - Platform Session
.conf Go Zurich 2022 - Platform Session.conf Go Zurich 2022 - Platform Session
.conf Go Zurich 2022 - Platform Session
 
.conf Go Zurich 2022 - Security Session
.conf Go Zurich 2022 - Security Session.conf Go Zurich 2022 - Security Session
.conf Go Zurich 2022 - Security Session
 

Recently uploaded

Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machinePadma Pradeep
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
Artificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraArtificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraDeakin University
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitecturePixlogix Infotech
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking MenDelhi Call girls
 
Maximizing Board Effectiveness 2024 Webinar.pptx
Maximizing Board Effectiveness 2024 Webinar.pptxMaximizing Board Effectiveness 2024 Webinar.pptx
Maximizing Board Effectiveness 2024 Webinar.pptxOnBoard
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | DelhiFULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhisoniya singh
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024Scott Keck-Warren
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your Budget
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your BudgetHyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your Budget
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your BudgetEnjoy Anytime
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Scott Keck-Warren
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesSinan KOZAK
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationSafe Software
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 3652toLead Limited
 

Recently uploaded (20)

Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machine
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
Artificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraArtificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning era
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC Architecture
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
Maximizing Board Effectiveness 2024 Webinar.pptx
Maximizing Board Effectiveness 2024 Webinar.pptxMaximizing Board Effectiveness 2024 Webinar.pptx
Maximizing Board Effectiveness 2024 Webinar.pptx
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | DelhiFULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your Budget
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your BudgetHyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your Budget
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your Budget
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen Frames
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 
The transition to renewables in India.pdf
The transition to renewables in India.pdfThe transition to renewables in India.pdf
The transition to renewables in India.pdf
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
 

Taking Splunk to the Next Level - Architecture Breakout Session

  • 1. Copyright © 2015 Splunk Inc. Splunk @ Level++ Steve Dvorak
  • 2. 2 Customer Discovery 2 • Activity brief in the box folder: – https://splunk.box.com/SLPhx • In the room: – Door2door’s Splunk Architect (Steve) – Splunk SE (Nate)
  • 3. 3 Splunk at the Next Level Time to move beyond initial Splunk environment • More use cases – how to tackle? • More data – how do we scale? • Splunk is mission critical == HA • Global deployments • Splunk user experience Screenshot here
  • 4. 4 Agenda Use cases  Business Cases Simple Scaling Indexer Clustering (+Cross-site Clustering, Search Affinity) Search Head Clustering Distributed Management Console Centralized Configuration Management Splunk Cloud & Hybrid Deployments Architecture workshop Q&A
  • 5. 5 Growing your Splunk Deployment Many customers start with a single use case… • Ex: Monitor the web servers • Help ensure up-time & response times • Track usage, errors • Provides business value
  • 6. 6 Growing your Splunk Deployment Value statement for each overall service Your services exist in a larger context than just one app, or one tier. What is the value of the service as a whole? What are CIO commitments for the service? • The company’s web store is one of the most critical parts of the business. • Performance of the overall environment must be maintained at all times. • Failures in any portion of the web store must be quickly identified, send notification to the appropriate parties. • Dependencies on external processes must be monitored as well.
  • 7. 7 Growing your Splunk Deployment The larger context • Failure in one system cascades • Map dependencies, estimate costs • Use Splunk to track all dependencies. • What happens when it is down? Dependencies often include: • Networking dependencies • Shared storage • Databases, middleware, custom apps • Virtualization layer Screenshot here
  • 8. 8 Scaling Multiple factors Indexer: IOPs, daily rate Storage: Usage & retention Search Head usage
  • 9. 9 Scaling - Indexers Sizing for index performance Indexers are usually storage-bound Indexers: 150 to 250 GB per day each. (With suitable storage) Ref HW: 12 cores (2 GHz+), 12 GB RAM, 800+ IOPs Optimal HW (normal disk): 16 CPU cores, 48 GB RAM Optimal HW (SSD): 24 CPU cores, 132 GB RAM Questions?
  • 10. 10 SSD Advantage http://blogs.splunk.com/2012/05/10/quantifying-the-benefits-of- splunk-with-ssds/ • Low cost random seeks • Writes are not that much faster – no great improvement with Indexing • Significant improvements with Sparse/needle-haystack searches • Dense searches become CPU bound • Searches run faster allowing for more completed searches/min
  • 11. 11 Scaling - Storage Simple storage to complex Raw data rate  net compression of ~ 50% on disk. Simple: rate * compression * retention 200 GB / day * 50% * 100 days = 10TB Consider cold storage on NAS – Changes storage story. – Retention on fast, retention on slow Clustering – Changes storage story
  • 12. 12 Scaling - Storage Sizing Calculator: http://splunk-sizing.appspot.com/
  • 13. 13 Scaling - Storage RAID + SSD deep dive • For spinning disks, Splunk recommends RAID 1+0 with 1k IOPs • SSDs provide extremely high IOPs (45,000 +) • RAID 5 SSD arrays give great Splunk performance in most scenarios. Additional details: Splunk Docs, Capacity Planning Manual
  • 14. 15 Indexer Clustering High-Availability, Out of the Box Splunk indexer clustering Active-Active= better performance Specific terms: – Master Node – Peer Node – Search Factor – Replication Factor Additional details: Splunk Docs, Distributed Deployment Manual
  • 15. 16 Cross-site Clustering Search Affinity by location “Search locally”, “Store Globally” DR scenarios
  • 16. 17 Scaling the Search Heads Splunk Search is critical, too! Splunk Search high availability needs Scale to handle # of concurrent queries
  • 17. 18 SHP vs SHC SHC • SHP • Available since v4.2 • Sharing configurations through NFS • Single point of failure • Performance issues • No NFS • Replication using local storage • Commodity hardware NFS
  • 19. 20 Search Head Clustering Use “Captain” for Master to avoid confusion with Index-Clustering Minimum 3 nodes required. Odd is always preferred. Cluster takes certain key decisions based on *majority* (consensus) In multi-site setup have more nodes in main datacenter
  • 20. 21 Distributed Management Console Manage Splunk 6.2 environments Replaces Deployment Monitor App Incorporates SOS app prior to 6.2
  • 21. 22 Deployment Server Central management of Splunk Forwarders Deployment Server manages Apps, Configs Select one or more classes for each host Class defines apps & configs Works by phone-home Notes: DS does not push forwarder binaries Use Cluster Master to manage indexers in cluster, not DS
  • 22. 23 Cloud & Hybrid Scale without waiting for hardware
  • 23. 24
  • 24. 25 Discovery 2 • 1Tb/day peak ingest • Up to 50 concurrent users • All data is being generated from a single data center • Fault tolerant design for high availability of Splunk • 90 days data retention • Standard hardware models in the Activity Brief
  • 26. 27 Forwarding Tier 2 Design Factors • Syslog Collectors (HA) • DBConnect Inputs – McAfee EPO data • TA Inputs – CheckPoint • Assorted Inputs – Microsoft AD logs – MicroSoft Exchange Server – Microsoft Sharepoint logs – Log4j, Linux, IIS
  • 27. 28 Syslog Collectors 2 • Best Practice to use dedicated syslog servers • Syslog-NG/rSyslog recommended • Syslog can write events to dedicated log files allowing for easy sourcetype classification on inputs
  • 28. 29 Syslog Collectors 2 • Using a Load Balancer/VIP with Linux Heartbeat to provide failover for the syslog listener • Syslog-NG PE Client-side failover High Availability
  • 29. 30 Forwarder for TA’s 3 • TA-McAfee requires DBConnect to pull endpoint events • TA-Checkpoint uses the LEA Client to retrieve Firewall log events • Not a HA design, but could be hosted on a VM to standby or failover
  • 30. 31 Deployment Server 3 ● Deployment Server to manage Linux and Windows forwarders ● Not a HA design, but could be hosted on a VM to standby or failover
  • 32. 33 Forwarding Tier BOM 3 Role Type Config # Syslog Server F 4vCPU/12Gb/200 Gb 2 HWF E 2vCPU/8Gb/20G b 1 Deployment Server F 4vCPU/12Gb/200 Gb 1 Load Balancer - - -
  • 33. 34 Forwarding Tier Design Best Practices 3 • Use a Syslog Server for Syslog data • Be careful with Intermediate forwarders – They can introduce bottlenecks – Reduce the distribution of events across Indexers • AutoLB will spread over all available indexers, but don’t assume evenly! – Enable forceTimebasedAutoLB • May need to increase UF thruput setting for high velocity sources – [thruput] – maxKBps
  • 35. 36 Indexing Tier 3 Design Factors • 1 Tb/day (1000Gb/day) peak ingest • High Availability – Indexer Replication (RF=3/SF=2) • 10% Disk Space Contingency • 90 days minimum data retention • • Cluster Sizing Calculator • o http://splunk- sizing.appspot.com
  • 36. 37 Storage Calculations 3 • RAID Configuration – Amount of raw disk – Fault tolerance – Available IOPS • Filesystem Overhead – inodes consume space • Wiggle room – Additional replicated buckets when a node fails – Unbalanced replicated buckets • Splunk internal logs, Summary Indexes, Report Acceleration, Accelerated Data Models
  • 38. 39 Storage Types 3 • Local vs Direct Attached vs SAN vs NAS • SSD/Flash vs Spinning Disk – SSDs offer much higher IOPS with no latency – Significant performance increases with Sparse Searches
  • 39. 40 Cluster Master Server 4 • Indexer Apps are deployed via CM • Not a HA design, but could be hosted on a VM to standby or failover
  • 41. 42 Indexing Tier BOM – Solution A 4 Role Type Config # Indexer A 16CPU/64Gb/12* 1Tb (RAID10) 20 Cluster Master F 4vCPU/12Gb/200 GB 1
  • 42. 43 Indexing Tier BOM – Solution B 4 Role Type Config # Indexer C 24CPU/96Gb/6*8 00Gb(RAID6)+6* 2Tb(RAID10) 13 Cluster Master F 4vCPU/12Gb/200 GB 1
  • 43. 44 Indexing Tier Design Best Practices 4 • Depending on Searchload 100-250Gb max/idx/day*** • Max # of Indexes (indices) when clustering is enabled
  • 44. 45 How Clustering Affects Sizing • Increased storage: – 15% of raw usage for every replica copy – 35% MORE to make that searchable • Increased processing – Incoming data to indexer is streamed to indexing peers to satisfy required number of copies • More hosts – Need “replication factor” + 2 (search head, cluster master) 4
  • 45. 46 Benefits of Clustering • Data redundancy • Data availability • Indexer resiliency • Simpler management of indexers • Simpler setup of distributed search • Multi-site clustering allows site-specific search to reduce WAN traffic 4
  • 46. 47 Downsides of Clustering • Increased Storage • Extra machine (cluster master) required • Increased bandwidth • Hard to manage with DS (read: don’t) 4
  • 48. 49 Search Tier 4 Design Factors • High Availability • Search Head Clustering • # users • # concurrent searches • Forward all data to indexers
  • 49. 50 SHC & Deployer 5 • Search Head Cluster Apps need to be installed by the Deployer • A minimum of 3 Search Heads are required for a SHC • No Exchange or VMware app with SHC – Anything leveraging tscollect based searches will need modification
  • 51. 52 Search Tier BOM 5 Role Type Config # Search Head B 16CPU/64Gb/2*8 00Gb 3 Deployer E 2vCPU/8Gb/20G b 1 License Server E 2vCPU/8Gb/20G b 1 Load Balancer - - -
  • 52. 53 Search Tier Design Best Practices 5 • ES will still require a Separate Search Head or dedicated SHC • Use LDAP/AD/SSO for user Authentication • Load Balancer configured for sticky sessions
  • 54. 55 Putting it all together 5
  • 56. 57 Hybrid Approach 5 • Add the existing Splunk instance as a search peer until the data retention period has expired • Disable scheduled searches on the old instance • Migrate any Summary Index data to new Indexers
  • 58. 59 Top 5 things to consider 5 • Indexer Storage requirements – Size and IOPS • Minimum buy-in for a SHC is 3 • Use VMs for CM/LS/DS/Deployer if possible • Consider a dedicated SH for a Distributed Management Console • When in doubt – add another Indexer
  • 59. 60 How Apps Affect Sizing • Enterprise Security – Requires a dedicated search head • Don’t share hosts with other services – Not co-located with Exchange, Active Directory, Hypervisors • Don’t let anti-virus run on the Splunk partition • Some data collection apps require a full instance (heavy forwarder) – VMWare – Checkpoint LEA 6
  • 60. 61 Sizing Considerations • http://docs.splunk.com/Documentation/Splunk/latest/Installation/Cap acityplanningforalargerSplunkdeployment – Amount of incoming data – Amount of indexed (stored) data – Number of concurrent users – Number of saved searches – Types of searches – Specific Splunk apps • http://docs.splunk.com/Documentation/Splunk/latest/Installation/Perf ormancechecklist
  • 61. 62 Required Reading • Distributed Deployment Manual – http://docs.splunk.com/Documentation/Splunk/latest/Deploy/Distributedoverv iew • Highlights – Reference hardware specs – How searches affect performance  Dense / Rare / Sparse – App considerations – Summary table 6
  • 62. 63 63 The 6th Annual Splunk Worldwide Users’ Conference • September 21-24, 2015 • The MGM Grand Hotel, Las Vegas • 4000 IT & Business Professionals • 2 Keynote Sessions • 3 days of technical content – 165+ sessions • 3 days of Splunk University – Sept 19-21, 2015 – Get Splunk Certified for FREE! – Get CPE credits for CISSP, CAP, SSCP, etc. – Save thousands on Splunk education! • 80 Customer Speakers • 80 Splunk Speakers • 35+ Apps in Splunk Apps Showcase • 65 Technology Partners • Ask The Experts and Security Experts, Birds of a Feather, Chalk Talks and a new & improved Partner Pavilion! • Register at conf.splunk.com
  • 63. 64 6 www.splunk.com/apptitude July 20th, 2015 Submission deadline
  • 64. 65 We Want to Hear your Feedback! After the Breakout Sessions conclude Text Splunk PHX to 878787 And be entered for a chance to win a $100 AMEX gift card!

Editor's Notes

  1. Default 3/2 cluster uses 3*.15 + 2*.35 = 115% of license usage for that redudancy Processing : a little more CPU and more network this is much better in current versions, the indexed data (tsidx, etc) is streamed to the replica peer, rather than forcing the peer to re-index.
  2. Availability – Cervelli famously smashed a laptop that was part of a distributed cluster, another host answered, search still available
  3. As discussed – default parameters require *more than* original log size
  4. Indexing volume per day (reference indexer = 250 GB / day = 3 MB/s .. ~ ¼ of a forwarder) Long-term storage (retention) Users = search activity Saved searches = search activity Dense (cpu, time spend unzipping data) / rare / sparse (1 in a million or one in 10 million – IOPS)
  5. 2 inspired Keynotes – General Session and Security Keynote 150+ Breakout sessions addressing all areas and levels of Operational Intelligence – IT, Business Analytics, Mobile, Cloud, IoT, Security…and MORE! Join the 50%+ of Fortune 100 companies who attended .conf2014 to get hands on with Splunk. You’ll be surrounded by thousands of other like-minded individuals who are ready to share exciting and cutting edge use cases and best practices. You can also deep dive on all things Splunk products together with your favorite Splunkers. Head back to your company with both practical and inspired new uses for Splunk, ready to unlock the unimaginable power of your data! Arrive in Vegas a Splunk user, leave Vegas a Splunk Ninja!
  6. ----- Meeting Notes (4/22/15 10:47) ----- Splunk Apptitude is live and open. You've got 90 days. To win more than $150,000 in cash and prizes. Last day to submit is July 20th, 2015. We'll announce the winners at Black Hat in August. Good luck!