SlideShare uma empresa Scribd logo
1 de 68
Back to the future

Understand and Optimize your IBM Notes/Domino infrastructure
Daniel Reimann
Introduction
• The goal: Thinking about going to the cloud, implementing Connections,
migrating, consolidating or growing your environment?

– Crucial data lives in various places in your IT infrastructure
– Doing any of the above projects requires you to look at this data in a “big picture”
view

• The challenge: How do you connect the various information silos?

– Knowledge is spread out in the environment in numerous repositories on several
servers
– In many situations, companies aren't even aware of the information available to them

• How we can help: Going to back to the future to move forward

– Find out how your environment looks today and get surprising results
– Use these gathered results to solve existing issues and be well prepared for
implementing or connecting new services and optimizing or extending your
infrastructure
Session content:
(Some) results of a Domino Network Analysis Health Check
About DNA®
• Service Offering
• Unique multi dimensional Insight in Utilisation &
Configuration of IBM Notes/Domino
• Overall Health Check / SWOT of Customer Environment
• Data Collection -> Analysis -> Reporting
• IBM & Business Partners reselling DNA World Wide
• Executed remotely by panagenda/Trust Factory
Zero Impact: means:
ZERO Impact
Impact
means:
Nothing to Install
No Installation

Leaves No Footprint
Leave No Footprint
No Dependancy

Deliver in a Few Days
No Footprint
DNA Service Modules
®

DNA ® Health Check

Starting Point for
all DNA Services

Server Consolidation Support
Optional Service

Root Cause & Performance

See slides at the end of
this presentation

Optional Service

See slides at the end of
this presentation

Source Code Analysis
Optional Service

See slides at the end of
this presentation
What Results will it Provide?
• Reveales Realistic Ambitions for:
•
•
•
•

Cleanup & Optimization Opportunities
Server Consolidation & Network (Optional Module)
Application Migration (Optional Module)
Performance Optimization (Optional Module)

• Interactive Slide Deck
• Linked to Common Spreadsheets & Check Lists
• Recommendations

• Presented Live
• Along with Explanation & Interpretation of Analysis Results by Subject Matter
Expert
What can you do with the results?
• IT Director / CIO:
•
•
•
•

Executive Decision-Making Support
Validation of Business Case
Define Innovation & Cloud Strategy
Current State of Affairs

Each DNA

®

delivers:

Quick Wins
Project Wins
Strategic Wins

• Project Manager & Teams:

• DNA Facts & Findings Help Focus & Prioritize
• Detailed Helicopter View replaces Micro View
• Prepare any Scenario with DNA Data Points

• For Administration & Support:

• Cleanup & Optimize by Means of Actionable Check Lists
• Improve Service Levels
Scope
• Activity by Rich Clients
• Web users not included

• 7 days
• 26 Servers in Scope
Management Summary
• Today:
26 Domino Servers
4 Different Releases
22544, GB Storage
Databases:
102, Integrity Issues
1020, Open to Anonymous
Directories:
110, Conflicts/Duplicates
18 Weak Passwords

• Tomorrow:
6 Domino Servers *
1 Single 9.0 Release
8316, GB Storage

Issues solved

* Based on observed session concurrency of 2.167
(clustered, excl. special functions )
Domino Environment Overview
1 Domino Directory

2,806 Users Registered
2,064 Users Active

3,345 Databases Touched

2,055 Users sending email
46 Servers Registered

149,515 Views Indexed
26 Servers Analyzed

15,572 Databases Deployed

1,177,671 Views Defined

4 Domino Releases

176 View Storage (GB)

4 Operating Systems
144,164 ACL Entries
589 Groups Registered

22,594 Db Storage (GB)
23,605 Group Members
DNA Benchmark
Active versus Registered Users
100 %

2,064 active users
80 %

60 %

40 %

20 %

0%
Demo Inc

Lowest Customer

Unused Licenses, Web Users, Regular Absense

DNA Average

Highest Customer
DNA Bechmark
Time Online
60

25

50

20

40

15

30

10

20

5

10

o
i
t
a
r
u
D
n
s
e
S
)
n
o
i
r
e
p
s
m
(

)
e
p
s
r
u
o
h
(

m
T
e
i
l
n
O

30

-

Demo Inc.

Lowest Customer

DNA Average

Highest Customer

Session Duration

3

1

4

28

Online Time

37

5

17

44

-
DNA Bechmark
Document Reads/Writes
1.000

3.000

750

2.000

500

1.000

250

s
d
a
R
t
n
e
m
u
c
o
D

s
i
r
W
t
n
e
m
u
c
o
D

4.000

-

Demo Inc.

Lowest Customer

DNA Average

Highest Customer

Document Reads

1.983

304

2.093

3.652

Document Writes

301

152

385

906

-
DNA Bechmark
Network Bandwidth Consumption

8

30

6

20

4

10

2

0

Demo Inc.

Lowest Customer

DNA Average

Highest Customer

server to clients

8,7

1,9

10,3

38,2

clients to server

1,6

0,5

2,1

8,1

0

v
r
o
s
t
n
e
i
l
c
)
c
r
e
p
s
t
b
o
l
i
k
(

10

40

n
i
l
c
o
t
v
r
e
s
)
c
r
e
p
s
t
b
o
l
i
k
(

50
User Demand Profiling
(Demo Company, 2064, active accounts)

20%

Remote Users <

> Of f ice Workers

System Accounts

15%

10%

5%

0%
2

4

6

8

10

12

14

Distinct Hours Online per Day

16

18

20

22

24
End User Demand Characteristics
Demo Company
100%

75%

50%

25%

0%

Notes Sessions

Document Reads

Document Writes

Db Transactions

Network Traffic

Session Duration

19%
6%

0%

0%

4%

0%

3%

5%

47%

8%

1%

1%

mail files

52%

69%

47%

62%

87%

89%

directories

17%

22%

2%

23%

6%

3%

applications

6%

4%

4%

3%

5%

4%

check new mail
system dbs
User Demand on 3341, Databases
Demo Company
100.000.000

y
B
o
l
i
K
v
r
n
S
s
e
t

10.000.000

1.000.000

100.000

10.000

1.000

100

10

1

0
1

10

100

1.000

10.000

100.000

1.000.000

10.000.000

100.000.000

Kilo Bytes Read from Server
Application

Domino Directory

Mailfile

Mailin database

Server Mail Box

System database
End User Demand at Demo Company
Classified by Demand Level
Document
Writes

Document
Reads

Database
Transactions

Network Traffic
(client to server)

Network Traffic
(server to client)

User Sessions

0%

25%
Extreme (,0)

50%
Intensive (2,0)

75%
Moderate (62,0)

100%
Light (2000,0)
User Activity by Top 10 Accounts
(Document Reads)
25.000

20.000
user_810
user_864
user_1831

15.000

user_1364
user_894
user_1950
user_2652

10.000

user_996
user_2243
user_657

8
1

2
1

6
D -O -Y
t 0
k Y

8
1

2
1

6
D -O -Y
t 0
k Y

8
1

2
1

6
D -O -Y
t 0
k Y

8
1

2
1

6
D -O -Y
t 0
k Y

8
1

2
1

6
D -O -Y
t 0
k Y

8
1

2
1

6

2
1

8
1
D -O -Y
t 0
k Y

D -O -Y
t 0
k Y

0

6

5.000
Domino Servers at Demo Company
Classified by Maximum Session Concurrency
20
Redistributing the load can reduce nr. of
servers with up to 18,

15

10

5

0
Level
Servers

Very Low
< 50

Low
50 - 249

Average
250 - 749

Normal
750 - 1499

High
> 1500

18

6

0

2

0
20

16

12

08

04

2010-10-27 00

20

16

12

08

04

2010-10-26 00

20

16

12

08

04

2010-10-25 00

20

16

12

08

04

2010-10-24 00

20

16

12

08

04

2010-10-23 00

20

16

12

08

04

2010-10-22 00

20

16

12

08

04

2010-10-21 00

Concurrent User Sessions

End User Demand
Session Concurrency

2,500
Max Observed Maximum : 2,167

2,000

1,500

1,000

500

0
20

16

12

08

04

2010-10-27 00

20

16

12

08

04

2010-10-26 00

20

16

12

08

04

2010-10-25 00

20

16

12

08

04

2010-10-24 00

20

16

12

08

04

2010-10-23 00

20

16

12

08

04

2010-10-22 00

20

16

12

08

04

2010-10-21 00

Avg per Hour

End User Demand
Document Reads

2,500
Max Observed Average: 1,911

2,000

1,500

1,000

500

0
20

16

12

08

04

2010-10-27 00

20

16

12

08

04

2010-10-26 00

20

16

12

08

04

2010-10-25 00

20

16

12

08

04

2010-10-24 00

20

16

12

08

04

2010-10-23 00

20

16

12

08

04

2010-10-22 00

20

16

12

08

04

2010-10-21 00

Avg per Hour

End User Demand
Document Writes

800
Max Observed Average: 678

700

600

500

400

300

200

100

0
20

16

12

08

04

2010-10-27 00

20

16

12

08

04

2010-10-26 00

20

16

12

08

04

2010-10-25 00

20

16

12

08

04

2010-10-24 00

20

16

12

08

04

2010-10-23 00

20

16

12

08

04

2010-10-22 00

20

16

12

08

04

2010-10-21 00

Avg per Hour

End User Demand
Database Transactions

16,000
Max Observed Average: 13,498

14,000

12,000

10,000

8,000

6,000

4,000

2,000

0
20

16

12

08

04

2010-10-27 00

20

16

12

08

04

2010-10-26 00

20

16

12

08

04

2010-10-25 00

20

16

12

08

04

2010-10-24 00

20

16

12

08

04

2010-10-23 00

20

16

12

08

04

2010-10-22 00

20

16

12

08

04

2010-10-21 00

Avg per Hour (kbps, to clients)

End User Demand
Network Bandwidth Consumption

25,000
Max Observed Average: 23,616

20,000

15,000

10,000

5,000

0
Network Compression
How Much is Notes Network Compression Used?

Includes Traffic
from Users and
Servers

# Users making use of
Notes Network Compression

Disabled
99%

100%
Enabled
Disabled

75%

% Active Users

Enabled
1%

50%

25%

0%
Persons

Servers
Deployment Integrity
Entries appearing in multiple documents
Integrity check
Duplicate Replica On Same Server
Duplicate Template on same Server

# Databases
80
0

Document Type

Full Names

Name Variations

Group

0

2

Mailin / Resource

4

6

Replicas Acting As Different Template

22

Person

0

95

Same Replica but Different Inheritance

0

Other

3

0

Grand Total

7

103

Grand Total

102

86 Group Cycles Detected
DB Storage Profile for Demo Company
Distributed by Size
25%
Dbs > 1 GB: 1,323
Dbs > 10 GB: 431

20%

System database

15%

Mailin database
Mailfile

Application

10%

.
0
1

.
0
1

0
.
1

Size (megabytes)

0
1

0%

0
1

5%

1

e
g
r
S
l
a
t
T
f
o
%

Domino Directory
Database Storage Consolidation Potential
Number of
Database Type
Domino Directory

Total

Unique

Consolidated

Storage

Databases

Storage

Replicas

Storage

Savings

79

3

30

7,832

20,723

2,768

7,517

64%

Mailin database

261

107

144

53

50%

Server Mail Box

54

8

54

8

0%

QuickPlace

165

1

147

1

0%

BlackBerry

1,425

11

718

6

45%

Application

2,904

1,691

1,200

731

57%

12,720

22,544

5,061

8,316

63%

Mailfile

Grand Total

-

100%

Top 10 databases ranked by size
Database Title

Db Type

Storage (GB)

061cc52a3244e8bad944519170c3ff06

Mailfile

42.2

96140ee5ec036ec69136a74647729a2a

Mailfile

32.2

cad93d0aa156514e70237f1b370cc9c5

Mailfile

31.9

cfef8f68b2847cdd2eea9dda44d94acc

Mailfile

30.5

861455d1d12b1b2d990fc9e7c41ceea7

Mailfile

28.9

5128de940e6d560d37723b6448d48e00

Mailfile

28.7

d6de2ffe48a037e2e93ff13c688df77c

Mailfile

28.3

490eeb54ce626d24d63d1038be4de073

Mailfile

28.0

928c35784596e9487a0db1304573a310

Mailfile

27.8

1ab2006c3ef8fe4ba6e7daca15ee29d6

Application

27.3
View Size Distribution for Demo Company

12%

Views > 100 MB: 234,
Views > 1 GB: 8,

Showing 148355, views

10%

System database

8%

Mailin database
Mailfile
Domino Directory
Application

4%

2%

B
G
0
1

B
G
1
B
M
0
1

B
M
0
1

B
K
0
1

B
M
1

0%

B
K
0
1

g
r
S
w
e
i
V
l
a
t
T
f
o
%

6%
View Size Distribution for Demo Company
End User Mail Files

25%

Views > 100 MB: 13,0
Views > 1 GB: ,0

Showing 7104, views

20%

($Meetings)

15%

($ThreadsEmbed)
($All)
($Sent)
($Inbox)

g
r
S
w
e
i
V
l
a
t
T
f
o
%

10%

5%

B
M
0
1

B
M
0
1

B
M
1
B
K
0
1

B
K
0
1

0%
Basic Security Checks
Internet Password Strength
Databases with Anonymous Access

Variations found

Accounts

Company Name

1

First Name

1

Last Name

1

Depositor

Short Name

7

'password'

8
18

Databases

Templates

0

28

Reader

262

80

Author

35

82

Editor
Grand Total

Access Level

2

0

Manager

0

21

Grand Total

299

211

Grand Total

598

422
Applications Touched by Users
Server Health Checks
The following Slides show several higlights of the
platform checks that were performed
Namelookup Cache Utilization
on server server_17
Set this cache higher to
prevent 100% utilization

2 other server(s) have similar issues

100

%
75

50

25

18

12

6

27-Oct-10 0

18

12

6

26-Oct-10 0

18

12

6

25-Oct-10 0

18

12

6

24-Oct-10 0

18

12

6

23-Oct-10 0

18

12

6

22-Oct-10 0

18

12

6

21-Oct-10 0

0
NSF Events & Monitor Pool Size Utilization
on server server_17
Cache Size is Sufficient

No issues detected on other servers

100

%
75

50

25

18

12

6

27-Oct-10 0

18

12

6

26-Oct-10 0

18

12

6

25-Oct-10 0

18

12

6

24-Oct-10 0

18

12

6

23-Oct-10 0

18

12

6

22-Oct-10 0

18

12

6

21-Oct-10 0

0
Miss Rate on Database BufferPool
on server server_24

Longer periods of High
Miss Rate may indicate
Performance Constraint

%
25

5 other server(s) m ay have sim ilar issues

20

15

10

5

18

12

6

27-Oct-10 0

18

12

6

26-Oct-10 0

18

12

6

25-Oct-10 0

18

12

6

24-Oct-10 0

18

12

6

23-Oct-10 0

18

12

6

22-Oct-10 0

18

12

6

21-Oct-10 0

0
Database File IO in KBytes per Second
Read activity on server server_16
Show ing busiest server

3,500

3,000

2,500

2,000

1,500

1,000

500

18

12

6

27-Oct-10 0

18

12

6

26-Oct-10 0

18

12

6

25-Oct-10 0

18

12

6

24-Oct-10 0

18

12

6

23-Oct-10 0

18

12

6

22-Oct-10 0

18

12

6

21-Oct-10 0

0
Database File IO in KBytes per Second
Write activity on server server_26
Show ing busiest server

1,000
900
800
700
600
500
400
300
200
100

18

12

6

27-Oct-10 0

18

12

6

26-Oct-10 0

18

12

6

25-Oct-10 0

18

12

6

24-Oct-10 0

18

12

6

23-Oct-10 0

18

12

6

22-Oct-10 0

18

12

6

21-Oct-10 0

0
Full Text Index Utilization
Search activity on server server_17
Show ing busiest server

0:00:22

0:00:13

0:00:09

0:00:04

18

12

6

27-Oct-10 0

18

12

6

26-Oct-10 0

18

12

6

25-Oct-10 0

18

12

6

24-Oct-10 0

18

12

6

23-Oct-10 0

18

12

6

22-Oct-10 0

18

12

6

0:00:00
21-Oct-10 0

Hours:Minutes

0:00:17
Mail Delivery Rates
Categorized by Msg Size
Msgs per Hour, Show ing all servers

30,000

25,000

20,000

15,000

10,000

5,000

under_1kb

1kb_to_10kb

10kb_to_100kb

100kb_to_1mb

1mb_to_10mb

10mb_to_100mb

18

12

6

27-Oct-10 0

18

12

6

26-Oct-10 0

18

12

6

25-Oct-10 0

18

12

6

24-Oct-10 0

18

12

6

23-Oct-10 0

18

12

6

22-Oct-10 0

18

12

6

21-Oct-10 0

0

over_100mb
Mail Transfer Rates
Categorized by Msg Size
7,000

Msgs per Hour, Show ing all servers

6,000

5,000

4,000

3,000

2,000

1,000

under_1kb

1kb_to_10kb

10kb_to_100kb

100kb_to_1mb

1mb_to_10mb

10mb_to_100mb

18

12

6

27-Oct-10 0

18

12

6

26-Oct-10 0

18

12

6

25-Oct-10 0

18

12

6

24-Oct-10 0

18

12

6

23-Oct-10 0

18

12

6

22-Oct-10 0

18

12

6

21-Oct-10 0

0

over_100mb
DNA for Root Cause & Performance:
• Service Offering
• Assist Customers with Root Cause Analysis
» Application & Server Performance
» Server Stability and Complex Support Topics
» Network Latency Impact

• Data Collection -> Analysis -> Reporting
• Executed Remotely by panagenda/Trust Factory
Zero Impact: means:
ZERO Impact
Impact
means:

• Prerequisite
• DNA Health Check Performed

Nothing to Install
No Installation

Leaves No Footprint
Leave No Footprint
No Dependancy

Deliver in a Few Days
No Footprint
What Results will it Provide?
• Root Cause Analysis Report:
•
•
•

Server & OS Configuration and Settings
Application Performance
Impact of Network Delay on Applications

• Interactive Slide Deck

• Linked to Common Spreadsheets & Check Lists
• Recommendations

• Presented Live

• Along with Explanation & Interpretation of Analysis Results
by Subject Matter Expert
What can you do with the results?
• Application Owners:
• Improve User Satisfaction

• Developers:
• Improve Source Code of Applications

• Adminstrators:
• Improve Server Performance
DNA Server Consolidation:
• Service Offering
• Multi Dimensional Insight into Network Demand,
Consolidation Potential & Data Center Scenarios
• Detailed Roadmap to Plan & Execute Server Consolidations
• Data Collection -> Analysis -> Reporting
• Executed Remotely by BP Trust Factory
ZEROImpactmeans:
Zero Impact:
Impact means:
No Installation
Nothing to Install

• Prerequisite

Leave No Footprint
Leaves No Footprint
No Dependancy

• DNA Health Check Performed
Deliver in a Few Days
No Footprint
What Results will it Provide?
•
•
•
•
•

Calculates Network Bandwidth Requirements
Consolidation Potential & Placement Scenarios
System & User Traffic Reduction & Optimization
Sizing Parameters for Servers, Storage & Network
Data Points for Cloud / Lotus Live

• Interactive Slide Deck

• Linked to Common Spreadsheets & Check Lists
• Recommendations

• Presented Live

• Along with Explanation & Interpretation of Analysis Results by Subject Matter Expert
What can you do with the results?
• IT Director / CIO:
• Executive Decision-Making Support
• Validation of Business Cases & Vendor Proposals
• Effective Realization of Cost Reduction

• Project Manager & Teams:
•
•
•
•

Input for Business Case & Project Proposal
DNA Facts & Findings Help Focus & Prioritize
Define Service Levels
Use Sizing Parameters for RFP’s
DNA Source Code Analysis:
• Service Offering

• Multi Dimensional Insight into Entire Application Landscape
» All Design Elements
» Source Code

• Real Impact of Application Landscape on Platform Migration
» Factual Quantification of Migration Effort for Redevelopment
» Identify Applications that Depend on Notes Mail

• Data Collection -> Analysis -> Reporting
• Executed Remotely by Trust Factory

ZEROImpactmeans:
Zero Impact:
Impact means:

No Installation
Nothing to Install

Leave No Footprint
Leaves No Footprint
No Dependancy

• Prerequisite

• DNA Health Check Performed

Deliver in a Few Days
No Footprint
What Results will it Provide?
• Complete Inventory of De-Duplicated Design & Source Code
• List of Applications that will Break after Migrating Notes Mail away
from Domino
• True Migration Effort based on Cocomo II
• Interactive Slide Deck
• Linked to Common Spreadsheets & Check Lists
• Recommendations

• Presented Live
• Along with Explanation & Interpretation of Analysis Results by Subject Matter
Expert
What can you do with the results?
• IT Director / CIO:
• Executive Decision-Making Support
• Validation of Business Cases & Vendor Proposals
• Develop Innovation Strategy

• Project Manager & Teams:
•
•
•
•

Input for Business Case & Project Proposal
Remediate Apps & Code Interacting with Notes Mail
DNA Facts & Findings Help Focus & Prioritize
Consolidate Source Code
Upcoming: panagenda iDNA
The In-house Version of Trust Factory‘s DNA Service

http://www.panagenda.com/en_uk/idna
Instant and Ongoing Analytics for Servers, Clients, Apps & More

• Unique Insights and Instant Value
• Executive Decision-Making Support
• Validation of Business Cases & Vendor Proposals
• Develop Innovation Strategy

• Turn Data into Knowledge
•
•
•
•

Hassle-free data collection from many different data sources
Instantly turns your data into meaningful reports
Move from reactive to proactive operations
Helps to fix, foresee and prevent problems with root cause
identification
• Gain answers to questions you never knew you could ask
Instant and Ongoing Analytics for Servers, Clients, Apps & More

• Facts and Architecture
• Up and running in half an hour - turnkey virtual softwareappliance
(Linux/VMWare)
• Non-intrusive, agent-less software - no installations required on
analyzed systems
• Data ware house access possible for data use with existing
reporting solutions
• HTML5 and PDF export for offline reports
Thank you!!!
How to Engage
• Master Agreement is in Place with IBM since 2003:
• Global Master Agreement Number:
• Trust Factory Supplier Number:

• panagenda:
•
•
•
•

4902NL0239
1000216663

Schreyvogelgasse 3/10 :: 1010 Vienna :: Austria
Web: http://www.panagenda.com
Email: office@panagenda.com
Fax: +43 1 89 012 89 – 15

• Our business partners in Italy:
Grazie agli sponsor per aver reso possibile i
Dominopoint Days 2013!
Main Sponsor

Vad sponsor
Platinum sponsor
Gold sponsor

Mais conteúdo relacionado

Mais procurados

cloud session uklug
cloud session uklugcloud session uklug
cloud session uklug
dominion
 
Citrix XenDesktop and XenApp 7.5 Architecture Deployment
Citrix XenDesktop and XenApp 7.5 Architecture DeploymentCitrix XenDesktop and XenApp 7.5 Architecture Deployment
Citrix XenDesktop and XenApp 7.5 Architecture Deployment
Huy Pham
 

Mais procurados (20)

Presentation basic administration for citrix xen app 6
Presentation   basic administration for citrix xen app 6Presentation   basic administration for citrix xen app 6
Presentation basic administration for citrix xen app 6
 
Co je nového v XenDesktop 7.6 a XenApp 7.6
Co je nového v XenDesktop 7.6 a XenApp 7.6 Co je nového v XenDesktop 7.6 a XenApp 7.6
Co je nového v XenDesktop 7.6 a XenApp 7.6
 
Citrix xenapp training
Citrix xenapp training Citrix xenapp training
Citrix xenapp training
 
Citrix Day 2014: XenApp / XenDesktop 7.6
Citrix Day 2014: XenApp / XenDesktop 7.6Citrix Day 2014: XenApp / XenDesktop 7.6
Citrix Day 2014: XenApp / XenDesktop 7.6
 
You don't want to do it like that
You don't want to do it like thatYou don't want to do it like that
You don't want to do it like that
 
Citrix Desktop Master Class – What’s New in XenApp/XenDesktop 7.11 - Sept 2016
Citrix Desktop Master Class – What’s New in XenApp/XenDesktop 7.11 - Sept 2016Citrix Desktop Master Class – What’s New in XenApp/XenDesktop 7.11 - Sept 2016
Citrix Desktop Master Class – What’s New in XenApp/XenDesktop 7.11 - Sept 2016
 
cloud session uklug
cloud session uklugcloud session uklug
cloud session uklug
 
What's new in XenDesktop and XenApp
What's new in XenDesktop and XenAppWhat's new in XenDesktop and XenApp
What's new in XenDesktop and XenApp
 
What We Wish We Had Known: Becoming an IBM Connections Administrator
What We Wish We Had Known: Becoming an IBM Connections AdministratorWhat We Wish We Had Known: Becoming an IBM Connections Administrator
What We Wish We Had Known: Becoming an IBM Connections Administrator
 
Citrix XenDesktop and XenApp 7.5 Architecture Deployment
Citrix XenDesktop and XenApp 7.5 Architecture DeploymentCitrix XenDesktop and XenApp 7.5 Architecture Deployment
Citrix XenDesktop and XenApp 7.5 Architecture Deployment
 
AAI-2075 Evolving an IBM WebSphere Topology to Manage a Changing Workloa
AAI-2075 Evolving an IBM WebSphere Topology to Manage a Changing WorkloaAAI-2075 Evolving an IBM WebSphere Topology to Manage a Changing Workloa
AAI-2075 Evolving an IBM WebSphere Topology to Manage a Changing Workloa
 
The Sametime Mobile Experience
The Sametime Mobile ExperienceThe Sametime Mobile Experience
The Sametime Mobile Experience
 
VMware@night - Was ist neu in VMware Horizon View 5.3 und Mirage 4.3
VMware@night - Was ist neu in VMware Horizon View 5.3 und Mirage 4.3VMware@night - Was ist neu in VMware Horizon View 5.3 und Mirage 4.3
VMware@night - Was ist neu in VMware Horizon View 5.3 und Mirage 4.3
 
Synergy 2015 Session Slides: SYN408 XenDesktop 7.6 Architecture - Dealing Wit...
Synergy 2015 Session Slides: SYN408 XenDesktop 7.6 Architecture - Dealing Wit...Synergy 2015 Session Slides: SYN408 XenDesktop 7.6 Architecture - Dealing Wit...
Synergy 2015 Session Slides: SYN408 XenDesktop 7.6 Architecture - Dealing Wit...
 
Presentation v mware horizon vision
Presentation   v mware horizon visionPresentation   v mware horizon vision
Presentation v mware horizon vision
 
XenDesktop and XenApp - 2015 summary & bit of future
XenDesktop and XenApp - 2015 summary & bit of futureXenDesktop and XenApp - 2015 summary & bit of future
XenDesktop and XenApp - 2015 summary & bit of future
 
Quickr
QuickrQuickr
Quickr
 
AAI-3281 Smarter Production with WebSphere Application Server ND Intelligent ...
AAI-3281 Smarter Production with WebSphere Application Server ND Intelligent ...AAI-3281 Smarter Production with WebSphere Application Server ND Intelligent ...
AAI-3281 Smarter Production with WebSphere Application Server ND Intelligent ...
 
IBM Lotus Notes / Domino upgrades
IBM Lotus Notes / Domino upgradesIBM Lotus Notes / Domino upgrades
IBM Lotus Notes / Domino upgrades
 
Keynote talk on Windows 8 - Jeff Stokes
Keynote talk on Windows 8 - Jeff StokesKeynote talk on Windows 8 - Jeff Stokes
Keynote talk on Windows 8 - Jeff Stokes
 

Semelhante a Back to the Future: Understand and Optimize your IBM Notes and Domino Infrastructure, #dd13

Idge dell qp_robo2014_04222014[1]
Idge dell qp_robo2014_04222014[1]Idge dell qp_robo2014_04222014[1]
Idge dell qp_robo2014_04222014[1]
jmariani14
 
SharePoint Online vs. On-Premise
SharePoint Online vs. On-PremiseSharePoint Online vs. On-Premise
SharePoint Online vs. On-Premise
Evan Hodges
 

Semelhante a Back to the Future: Understand and Optimize your IBM Notes and Domino Infrastructure, #dd13 (20)

Back to the Future - Understand and Optimize your IBM Notes/Domino Infrastruc...
Back to the Future - Understand and Optimize your IBM Notes/Domino Infrastruc...Back to the Future - Understand and Optimize your IBM Notes/Domino Infrastruc...
Back to the Future - Understand and Optimize your IBM Notes/Domino Infrastruc...
 
Data center insights summit 2015 disruptive force of clouds
Data center insights summit 2015   disruptive force of cloudsData center insights summit 2015   disruptive force of clouds
Data center insights summit 2015 disruptive force of clouds
 
Great Lakes Oracle Conference (GLOC) Benefits of migrating to the Cloud- Me...
Great Lakes Oracle Conference (GLOC)  Benefits of migrating to the Cloud-  Me...Great Lakes Oracle Conference (GLOC)  Benefits of migrating to the Cloud-  Me...
Great Lakes Oracle Conference (GLOC) Benefits of migrating to the Cloud- Me...
 
Co01_panagenda_NotesDomino-Licensing-Understand-and-Optimize-DLAU-results-wit...
Co01_panagenda_NotesDomino-Licensing-Understand-and-Optimize-DLAU-results-wit...Co01_panagenda_NotesDomino-Licensing-Understand-and-Optimize-DLAU-results-wit...
Co01_panagenda_NotesDomino-Licensing-Understand-and-Optimize-DLAU-results-wit...
 
Ojoconsulting Oy Nimbus Monitoring Service description v1.2 public
Ojoconsulting Oy Nimbus Monitoring Service description v1.2 publicOjoconsulting Oy Nimbus Monitoring Service description v1.2 public
Ojoconsulting Oy Nimbus Monitoring Service description v1.2 public
 
2010/09 - Database Architechs - Performance & Tuning Tool
2010/09 - Database Architechs - Performance & Tuning Tool2010/09 - Database Architechs - Performance & Tuning Tool
2010/09 - Database Architechs - Performance & Tuning Tool
 
Scoping for BMC Discovery (ADDM) Deployment by Traversys Limited
Scoping for BMC Discovery (ADDM) Deployment by Traversys LimitedScoping for BMC Discovery (ADDM) Deployment by Traversys Limited
Scoping for BMC Discovery (ADDM) Deployment by Traversys Limited
 
Idge dell qp_robo2014_04222014[1]
Idge dell qp_robo2014_04222014[1]Idge dell qp_robo2014_04222014[1]
Idge dell qp_robo2014_04222014[1]
 
SharePoint 2016 Beta 2 What's new (End users and IT Pros) Microsoft Innovat...
SharePoint 2016   Beta 2 What's new (End users and IT Pros) Microsoft Innovat...SharePoint 2016   Beta 2 What's new (End users and IT Pros) Microsoft Innovat...
SharePoint 2016 Beta 2 What's new (End users and IT Pros) Microsoft Innovat...
 
SharePoint Online vs. On-Premise
SharePoint Online vs. On-PremiseSharePoint Online vs. On-Premise
SharePoint Online vs. On-Premise
 
Office 365 deployment
Office 365 deploymentOffice 365 deployment
Office 365 deployment
 
SharePoint 2010 Global Deployment
SharePoint 2010 Global DeploymentSharePoint 2010 Global Deployment
SharePoint 2010 Global Deployment
 
Building the Case for System z Linux
Building the Case for System z LinuxBuilding the Case for System z Linux
Building the Case for System z Linux
 
O365 quick with fast user experience
O365 quick with fast user experienceO365 quick with fast user experience
O365 quick with fast user experience
 
Give ‘Em What They Want! Self-Service Middleware Monitoring in a Shared Servi...
Give ‘Em What They Want! Self-Service Middleware Monitoring in a Shared Servi...Give ‘Em What They Want! Self-Service Middleware Monitoring in a Shared Servi...
Give ‘Em What They Want! Self-Service Middleware Monitoring in a Shared Servi...
 
Datapolis Guest Expert Presentation: Top 15 SharePoint Server Configuration M...
Datapolis Guest Expert Presentation: Top 15 SharePoint Server Configuration M...Datapolis Guest Expert Presentation: Top 15 SharePoint Server Configuration M...
Datapolis Guest Expert Presentation: Top 15 SharePoint Server Configuration M...
 
Data Virtualization Journey: How to Grow from Single Project and to Enterpris...
Data Virtualization Journey: How to Grow from Single Project and to Enterpris...Data Virtualization Journey: How to Grow from Single Project and to Enterpris...
Data Virtualization Journey: How to Grow from Single Project and to Enterpris...
 
Atlassian User Group NYC 092718 Event
Atlassian User Group NYC 092718 EventAtlassian User Group NYC 092718 Event
Atlassian User Group NYC 092718 Event
 
Top reasons o365 deployments fail v1
Top reasons o365 deployments fail v1Top reasons o365 deployments fail v1
Top reasons o365 deployments fail v1
 
Top reasons o365 deployments fail
Top reasons o365 deployments failTop reasons o365 deployments fail
Top reasons o365 deployments fail
 

Mais de Dominopoint - Italian Lotus User Group

Mais de Dominopoint - Italian Lotus User Group (20)

TOTP - Time-Based One Time password in Domino
TOTP - Time-Based One Time password in DominoTOTP - Time-Based One Time password in Domino
TOTP - Time-Based One Time password in Domino
 
Domino Backup V12 - Un nuovo Task
Domino Backup V12 - Un nuovo TaskDomino Backup V12 - Un nuovo Task
Domino Backup V12 - Un nuovo Task
 
Mail Client from Traveler to Verse On-Premises
Mail Client from Traveler to Verse On-PremisesMail Client from Traveler to Verse On-Premises
Mail Client from Traveler to Verse On-Premises
 
IBM Worspace: Towards a culture of conversations
IBM Worspace: Towards a culture of conversationsIBM Worspace: Towards a culture of conversations
IBM Worspace: Towards a culture of conversations
 
Microsoft Outlook for Domino (IMSMO)
Microsoft Outlook for Domino (IMSMO)Microsoft Outlook for Domino (IMSMO)
Microsoft Outlook for Domino (IMSMO)
 
Riding the Enterprise Integration train
Riding the Enterprise Integration trainRiding the Enterprise Integration train
Riding the Enterprise Integration train
 
Ortocloud l'applicazione per fare orto su Bluemix
Ortocloud l'applicazione per fare orto su BluemixOrtocloud l'applicazione per fare orto su Bluemix
Ortocloud l'applicazione per fare orto su Bluemix
 
Meetit16 KeyNote di Apertura
Meetit16 KeyNote di AperturaMeetit16 KeyNote di Apertura
Meetit16 KeyNote di Apertura
 
IBM Domino Modernizing apps with Angularjs
IBM Domino Modernizing apps with AngularjsIBM Domino Modernizing apps with Angularjs
IBM Domino Modernizing apps with Angularjs
 
IBM Connections How to use existing data to increase adoption success with IB...
IBM Connections How to use existing data to increase adoption success with IB...IBM Connections How to use existing data to increase adoption success with IB...
IBM Connections How to use existing data to increase adoption success with IB...
 
Cloudant e XPages
Cloudant e XPagesCloudant e XPages
Cloudant e XPages
 
IBM Bluemix
IBM BluemixIBM Bluemix
IBM Bluemix
 
IBM Connections 10 things every user should know
IBM Connections 10 things every user should knowIBM Connections 10 things every user should know
IBM Connections 10 things every user should know
 
IBM Verse New Way To Work
IBM Verse New Way To WorkIBM Verse New Way To Work
IBM Verse New Way To Work
 
Crossware MailSignature
Crossware MailSignatureCrossware MailSignature
Crossware MailSignature
 
Cooperteam soluzioni
Cooperteam soluzioniCooperteam soluzioni
Cooperteam soluzioni
 
Notes and Domino Roadmap
Notes and Domino RoadmapNotes and Domino Roadmap
Notes and Domino Roadmap
 
La Collaborazione Europea
La Collaborazione EuropeaLa Collaborazione Europea
La Collaborazione Europea
 
the future of work
the future of workthe future of work
the future of work
 
Dominopoint meet the experts 2015 - XPages
Dominopoint   meet the experts 2015 - XPagesDominopoint   meet the experts 2015 - XPages
Dominopoint meet the experts 2015 - XPages
 

Último

Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
vu2urc
 
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
Enterprise Knowledge
 

Último (20)

Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
Tech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdfTech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdf
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)
 
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
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 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
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 

Back to the Future: Understand and Optimize your IBM Notes and Domino Infrastructure, #dd13

  • 1. Back to the future Understand and Optimize your IBM Notes/Domino infrastructure Daniel Reimann
  • 2. Introduction • The goal: Thinking about going to the cloud, implementing Connections, migrating, consolidating or growing your environment? – Crucial data lives in various places in your IT infrastructure – Doing any of the above projects requires you to look at this data in a “big picture” view • The challenge: How do you connect the various information silos? – Knowledge is spread out in the environment in numerous repositories on several servers – In many situations, companies aren't even aware of the information available to them • How we can help: Going to back to the future to move forward – Find out how your environment looks today and get surprising results – Use these gathered results to solve existing issues and be well prepared for implementing or connecting new services and optimizing or extending your infrastructure
  • 3. Session content: (Some) results of a Domino Network Analysis Health Check
  • 4. About DNA® • Service Offering • Unique multi dimensional Insight in Utilisation & Configuration of IBM Notes/Domino • Overall Health Check / SWOT of Customer Environment • Data Collection -> Analysis -> Reporting • IBM & Business Partners reselling DNA World Wide • Executed remotely by panagenda/Trust Factory Zero Impact: means: ZERO Impact Impact means: Nothing to Install No Installation Leaves No Footprint Leave No Footprint No Dependancy Deliver in a Few Days No Footprint
  • 5. DNA Service Modules ® DNA ® Health Check Starting Point for all DNA Services Server Consolidation Support Optional Service Root Cause & Performance See slides at the end of this presentation Optional Service See slides at the end of this presentation Source Code Analysis Optional Service See slides at the end of this presentation
  • 6. What Results will it Provide? • Reveales Realistic Ambitions for: • • • • Cleanup & Optimization Opportunities Server Consolidation & Network (Optional Module) Application Migration (Optional Module) Performance Optimization (Optional Module) • Interactive Slide Deck • Linked to Common Spreadsheets & Check Lists • Recommendations • Presented Live • Along with Explanation & Interpretation of Analysis Results by Subject Matter Expert
  • 7. What can you do with the results? • IT Director / CIO: • • • • Executive Decision-Making Support Validation of Business Case Define Innovation & Cloud Strategy Current State of Affairs Each DNA ® delivers: Quick Wins Project Wins Strategic Wins • Project Manager & Teams: • DNA Facts & Findings Help Focus & Prioritize • Detailed Helicopter View replaces Micro View • Prepare any Scenario with DNA Data Points • For Administration & Support: • Cleanup & Optimize by Means of Actionable Check Lists • Improve Service Levels
  • 8. Scope • Activity by Rich Clients • Web users not included • 7 days • 26 Servers in Scope
  • 9. Management Summary • Today: 26 Domino Servers 4 Different Releases 22544, GB Storage Databases: 102, Integrity Issues 1020, Open to Anonymous Directories: 110, Conflicts/Duplicates 18 Weak Passwords • Tomorrow: 6 Domino Servers * 1 Single 9.0 Release 8316, GB Storage Issues solved * Based on observed session concurrency of 2.167 (clustered, excl. special functions )
  • 10. Domino Environment Overview 1 Domino Directory 2,806 Users Registered 2,064 Users Active 3,345 Databases Touched 2,055 Users sending email 46 Servers Registered 149,515 Views Indexed 26 Servers Analyzed 15,572 Databases Deployed 1,177,671 Views Defined 4 Domino Releases 176 View Storage (GB) 4 Operating Systems 144,164 ACL Entries 589 Groups Registered 22,594 Db Storage (GB) 23,605 Group Members
  • 11. DNA Benchmark Active versus Registered Users 100 % 2,064 active users 80 % 60 % 40 % 20 % 0% Demo Inc Lowest Customer Unused Licenses, Web Users, Regular Absense DNA Average Highest Customer
  • 12. DNA Bechmark Time Online 60 25 50 20 40 15 30 10 20 5 10 o i t a r u D n s e S ) n o i r e p s m ( ) e p s r u o h ( m T e i l n O 30 - Demo Inc. Lowest Customer DNA Average Highest Customer Session Duration 3 1 4 28 Online Time 37 5 17 44 -
  • 13. DNA Bechmark Document Reads/Writes 1.000 3.000 750 2.000 500 1.000 250 s d a R t n e m u c o D s i r W t n e m u c o D 4.000 - Demo Inc. Lowest Customer DNA Average Highest Customer Document Reads 1.983 304 2.093 3.652 Document Writes 301 152 385 906 -
  • 14. DNA Bechmark Network Bandwidth Consumption 8 30 6 20 4 10 2 0 Demo Inc. Lowest Customer DNA Average Highest Customer server to clients 8,7 1,9 10,3 38,2 clients to server 1,6 0,5 2,1 8,1 0 v r o s t n e i l c ) c r e p s t b o l i k ( 10 40 n i l c o t v r e s ) c r e p s t b o l i k ( 50
  • 15. User Demand Profiling (Demo Company, 2064, active accounts) 20% Remote Users < > Of f ice Workers System Accounts 15% 10% 5% 0% 2 4 6 8 10 12 14 Distinct Hours Online per Day 16 18 20 22 24
  • 16. End User Demand Characteristics Demo Company 100% 75% 50% 25% 0% Notes Sessions Document Reads Document Writes Db Transactions Network Traffic Session Duration 19% 6% 0% 0% 4% 0% 3% 5% 47% 8% 1% 1% mail files 52% 69% 47% 62% 87% 89% directories 17% 22% 2% 23% 6% 3% applications 6% 4% 4% 3% 5% 4% check new mail system dbs
  • 17. User Demand on 3341, Databases Demo Company 100.000.000 y B o l i K v r n S s e t 10.000.000 1.000.000 100.000 10.000 1.000 100 10 1 0 1 10 100 1.000 10.000 100.000 1.000.000 10.000.000 100.000.000 Kilo Bytes Read from Server Application Domino Directory Mailfile Mailin database Server Mail Box System database
  • 18. End User Demand at Demo Company Classified by Demand Level Document Writes Document Reads Database Transactions Network Traffic (client to server) Network Traffic (server to client) User Sessions 0% 25% Extreme (,0) 50% Intensive (2,0) 75% Moderate (62,0) 100% Light (2000,0)
  • 19. User Activity by Top 10 Accounts (Document Reads) 25.000 20.000 user_810 user_864 user_1831 15.000 user_1364 user_894 user_1950 user_2652 10.000 user_996 user_2243 user_657 8 1 2 1 6 D -O -Y t 0 k Y 8 1 2 1 6 D -O -Y t 0 k Y 8 1 2 1 6 D -O -Y t 0 k Y 8 1 2 1 6 D -O -Y t 0 k Y 8 1 2 1 6 D -O -Y t 0 k Y 8 1 2 1 6 2 1 8 1 D -O -Y t 0 k Y D -O -Y t 0 k Y 0 6 5.000
  • 20. Domino Servers at Demo Company Classified by Maximum Session Concurrency 20 Redistributing the load can reduce nr. of servers with up to 18, 15 10 5 0 Level Servers Very Low < 50 Low 50 - 249 Average 250 - 749 Normal 750 - 1499 High > 1500 18 6 0 2 0
  • 21. 20 16 12 08 04 2010-10-27 00 20 16 12 08 04 2010-10-26 00 20 16 12 08 04 2010-10-25 00 20 16 12 08 04 2010-10-24 00 20 16 12 08 04 2010-10-23 00 20 16 12 08 04 2010-10-22 00 20 16 12 08 04 2010-10-21 00 Concurrent User Sessions End User Demand Session Concurrency 2,500 Max Observed Maximum : 2,167 2,000 1,500 1,000 500 0
  • 22. 20 16 12 08 04 2010-10-27 00 20 16 12 08 04 2010-10-26 00 20 16 12 08 04 2010-10-25 00 20 16 12 08 04 2010-10-24 00 20 16 12 08 04 2010-10-23 00 20 16 12 08 04 2010-10-22 00 20 16 12 08 04 2010-10-21 00 Avg per Hour End User Demand Document Reads 2,500 Max Observed Average: 1,911 2,000 1,500 1,000 500 0
  • 23. 20 16 12 08 04 2010-10-27 00 20 16 12 08 04 2010-10-26 00 20 16 12 08 04 2010-10-25 00 20 16 12 08 04 2010-10-24 00 20 16 12 08 04 2010-10-23 00 20 16 12 08 04 2010-10-22 00 20 16 12 08 04 2010-10-21 00 Avg per Hour End User Demand Document Writes 800 Max Observed Average: 678 700 600 500 400 300 200 100 0
  • 24. 20 16 12 08 04 2010-10-27 00 20 16 12 08 04 2010-10-26 00 20 16 12 08 04 2010-10-25 00 20 16 12 08 04 2010-10-24 00 20 16 12 08 04 2010-10-23 00 20 16 12 08 04 2010-10-22 00 20 16 12 08 04 2010-10-21 00 Avg per Hour End User Demand Database Transactions 16,000 Max Observed Average: 13,498 14,000 12,000 10,000 8,000 6,000 4,000 2,000 0
  • 25. 20 16 12 08 04 2010-10-27 00 20 16 12 08 04 2010-10-26 00 20 16 12 08 04 2010-10-25 00 20 16 12 08 04 2010-10-24 00 20 16 12 08 04 2010-10-23 00 20 16 12 08 04 2010-10-22 00 20 16 12 08 04 2010-10-21 00 Avg per Hour (kbps, to clients) End User Demand Network Bandwidth Consumption 25,000 Max Observed Average: 23,616 20,000 15,000 10,000 5,000 0
  • 26. Network Compression How Much is Notes Network Compression Used? Includes Traffic from Users and Servers # Users making use of Notes Network Compression Disabled 99% 100% Enabled Disabled 75% % Active Users Enabled 1% 50% 25% 0% Persons Servers
  • 27. Deployment Integrity Entries appearing in multiple documents Integrity check Duplicate Replica On Same Server Duplicate Template on same Server # Databases 80 0 Document Type Full Names Name Variations Group 0 2 Mailin / Resource 4 6 Replicas Acting As Different Template 22 Person 0 95 Same Replica but Different Inheritance 0 Other 3 0 Grand Total 7 103 Grand Total 102 86 Group Cycles Detected
  • 28. DB Storage Profile for Demo Company Distributed by Size 25% Dbs > 1 GB: 1,323 Dbs > 10 GB: 431 20% System database 15% Mailin database Mailfile Application 10% . 0 1 . 0 1 0 . 1 Size (megabytes) 0 1 0% 0 1 5% 1 e g r S l a t T f o % Domino Directory
  • 29. Database Storage Consolidation Potential Number of Database Type Domino Directory Total Unique Consolidated Storage Databases Storage Replicas Storage Savings 79 3 30 7,832 20,723 2,768 7,517 64% Mailin database 261 107 144 53 50% Server Mail Box 54 8 54 8 0% QuickPlace 165 1 147 1 0% BlackBerry 1,425 11 718 6 45% Application 2,904 1,691 1,200 731 57% 12,720 22,544 5,061 8,316 63% Mailfile Grand Total - 100% Top 10 databases ranked by size Database Title Db Type Storage (GB) 061cc52a3244e8bad944519170c3ff06 Mailfile 42.2 96140ee5ec036ec69136a74647729a2a Mailfile 32.2 cad93d0aa156514e70237f1b370cc9c5 Mailfile 31.9 cfef8f68b2847cdd2eea9dda44d94acc Mailfile 30.5 861455d1d12b1b2d990fc9e7c41ceea7 Mailfile 28.9 5128de940e6d560d37723b6448d48e00 Mailfile 28.7 d6de2ffe48a037e2e93ff13c688df77c Mailfile 28.3 490eeb54ce626d24d63d1038be4de073 Mailfile 28.0 928c35784596e9487a0db1304573a310 Mailfile 27.8 1ab2006c3ef8fe4ba6e7daca15ee29d6 Application 27.3
  • 30. View Size Distribution for Demo Company 12% Views > 100 MB: 234, Views > 1 GB: 8, Showing 148355, views 10% System database 8% Mailin database Mailfile Domino Directory Application 4% 2% B G 0 1 B G 1 B M 0 1 B M 0 1 B K 0 1 B M 1 0% B K 0 1 g r S w e i V l a t T f o % 6%
  • 31. View Size Distribution for Demo Company End User Mail Files 25% Views > 100 MB: 13,0 Views > 1 GB: ,0 Showing 7104, views 20% ($Meetings) 15% ($ThreadsEmbed) ($All) ($Sent) ($Inbox) g r S w e i V l a t T f o % 10% 5% B M 0 1 B M 0 1 B M 1 B K 0 1 B K 0 1 0%
  • 32. Basic Security Checks Internet Password Strength Databases with Anonymous Access Variations found Accounts Company Name 1 First Name 1 Last Name 1 Depositor Short Name 7 'password' 8 18 Databases Templates 0 28 Reader 262 80 Author 35 82 Editor Grand Total Access Level 2 0 Manager 0 21 Grand Total 299 211 Grand Total 598 422
  • 34. Server Health Checks The following Slides show several higlights of the platform checks that were performed
  • 35. Namelookup Cache Utilization on server server_17 Set this cache higher to prevent 100% utilization 2 other server(s) have similar issues 100 % 75 50 25 18 12 6 27-Oct-10 0 18 12 6 26-Oct-10 0 18 12 6 25-Oct-10 0 18 12 6 24-Oct-10 0 18 12 6 23-Oct-10 0 18 12 6 22-Oct-10 0 18 12 6 21-Oct-10 0 0
  • 36. NSF Events & Monitor Pool Size Utilization on server server_17 Cache Size is Sufficient No issues detected on other servers 100 % 75 50 25 18 12 6 27-Oct-10 0 18 12 6 26-Oct-10 0 18 12 6 25-Oct-10 0 18 12 6 24-Oct-10 0 18 12 6 23-Oct-10 0 18 12 6 22-Oct-10 0 18 12 6 21-Oct-10 0 0
  • 37. Miss Rate on Database BufferPool on server server_24 Longer periods of High Miss Rate may indicate Performance Constraint % 25 5 other server(s) m ay have sim ilar issues 20 15 10 5 18 12 6 27-Oct-10 0 18 12 6 26-Oct-10 0 18 12 6 25-Oct-10 0 18 12 6 24-Oct-10 0 18 12 6 23-Oct-10 0 18 12 6 22-Oct-10 0 18 12 6 21-Oct-10 0 0
  • 38. Database File IO in KBytes per Second Read activity on server server_16 Show ing busiest server 3,500 3,000 2,500 2,000 1,500 1,000 500 18 12 6 27-Oct-10 0 18 12 6 26-Oct-10 0 18 12 6 25-Oct-10 0 18 12 6 24-Oct-10 0 18 12 6 23-Oct-10 0 18 12 6 22-Oct-10 0 18 12 6 21-Oct-10 0 0
  • 39. Database File IO in KBytes per Second Write activity on server server_26 Show ing busiest server 1,000 900 800 700 600 500 400 300 200 100 18 12 6 27-Oct-10 0 18 12 6 26-Oct-10 0 18 12 6 25-Oct-10 0 18 12 6 24-Oct-10 0 18 12 6 23-Oct-10 0 18 12 6 22-Oct-10 0 18 12 6 21-Oct-10 0 0
  • 40. Full Text Index Utilization Search activity on server server_17 Show ing busiest server 0:00:22 0:00:13 0:00:09 0:00:04 18 12 6 27-Oct-10 0 18 12 6 26-Oct-10 0 18 12 6 25-Oct-10 0 18 12 6 24-Oct-10 0 18 12 6 23-Oct-10 0 18 12 6 22-Oct-10 0 18 12 6 0:00:00 21-Oct-10 0 Hours:Minutes 0:00:17
  • 41. Mail Delivery Rates Categorized by Msg Size Msgs per Hour, Show ing all servers 30,000 25,000 20,000 15,000 10,000 5,000 under_1kb 1kb_to_10kb 10kb_to_100kb 100kb_to_1mb 1mb_to_10mb 10mb_to_100mb 18 12 6 27-Oct-10 0 18 12 6 26-Oct-10 0 18 12 6 25-Oct-10 0 18 12 6 24-Oct-10 0 18 12 6 23-Oct-10 0 18 12 6 22-Oct-10 0 18 12 6 21-Oct-10 0 0 over_100mb
  • 42. Mail Transfer Rates Categorized by Msg Size 7,000 Msgs per Hour, Show ing all servers 6,000 5,000 4,000 3,000 2,000 1,000 under_1kb 1kb_to_10kb 10kb_to_100kb 100kb_to_1mb 1mb_to_10mb 10mb_to_100mb 18 12 6 27-Oct-10 0 18 12 6 26-Oct-10 0 18 12 6 25-Oct-10 0 18 12 6 24-Oct-10 0 18 12 6 23-Oct-10 0 18 12 6 22-Oct-10 0 18 12 6 21-Oct-10 0 0 over_100mb
  • 43. DNA for Root Cause & Performance: • Service Offering • Assist Customers with Root Cause Analysis » Application & Server Performance » Server Stability and Complex Support Topics » Network Latency Impact • Data Collection -> Analysis -> Reporting • Executed Remotely by panagenda/Trust Factory Zero Impact: means: ZERO Impact Impact means: • Prerequisite • DNA Health Check Performed Nothing to Install No Installation Leaves No Footprint Leave No Footprint No Dependancy Deliver in a Few Days No Footprint
  • 44. What Results will it Provide? • Root Cause Analysis Report: • • • Server & OS Configuration and Settings Application Performance Impact of Network Delay on Applications • Interactive Slide Deck • Linked to Common Spreadsheets & Check Lists • Recommendations • Presented Live • Along with Explanation & Interpretation of Analysis Results by Subject Matter Expert
  • 45. What can you do with the results? • Application Owners: • Improve User Satisfaction • Developers: • Improve Source Code of Applications • Adminstrators: • Improve Server Performance
  • 46. DNA Server Consolidation: • Service Offering • Multi Dimensional Insight into Network Demand, Consolidation Potential & Data Center Scenarios • Detailed Roadmap to Plan & Execute Server Consolidations • Data Collection -> Analysis -> Reporting • Executed Remotely by BP Trust Factory ZEROImpactmeans: Zero Impact: Impact means: No Installation Nothing to Install • Prerequisite Leave No Footprint Leaves No Footprint No Dependancy • DNA Health Check Performed Deliver in a Few Days No Footprint
  • 47. What Results will it Provide? • • • • • Calculates Network Bandwidth Requirements Consolidation Potential & Placement Scenarios System & User Traffic Reduction & Optimization Sizing Parameters for Servers, Storage & Network Data Points for Cloud / Lotus Live • Interactive Slide Deck • Linked to Common Spreadsheets & Check Lists • Recommendations • Presented Live • Along with Explanation & Interpretation of Analysis Results by Subject Matter Expert
  • 48. What can you do with the results? • IT Director / CIO: • Executive Decision-Making Support • Validation of Business Cases & Vendor Proposals • Effective Realization of Cost Reduction • Project Manager & Teams: • • • • Input for Business Case & Project Proposal DNA Facts & Findings Help Focus & Prioritize Define Service Levels Use Sizing Parameters for RFP’s
  • 49. DNA Source Code Analysis: • Service Offering • Multi Dimensional Insight into Entire Application Landscape » All Design Elements » Source Code • Real Impact of Application Landscape on Platform Migration » Factual Quantification of Migration Effort for Redevelopment » Identify Applications that Depend on Notes Mail • Data Collection -> Analysis -> Reporting • Executed Remotely by Trust Factory ZEROImpactmeans: Zero Impact: Impact means: No Installation Nothing to Install Leave No Footprint Leaves No Footprint No Dependancy • Prerequisite • DNA Health Check Performed Deliver in a Few Days No Footprint
  • 50. What Results will it Provide? • Complete Inventory of De-Duplicated Design & Source Code • List of Applications that will Break after Migrating Notes Mail away from Domino • True Migration Effort based on Cocomo II • Interactive Slide Deck • Linked to Common Spreadsheets & Check Lists • Recommendations • Presented Live • Along with Explanation & Interpretation of Analysis Results by Subject Matter Expert
  • 51. What can you do with the results? • IT Director / CIO: • Executive Decision-Making Support • Validation of Business Cases & Vendor Proposals • Develop Innovation Strategy • Project Manager & Teams: • • • • Input for Business Case & Project Proposal Remediate Apps & Code Interacting with Notes Mail DNA Facts & Findings Help Focus & Prioritize Consolidate Source Code
  • 52. Upcoming: panagenda iDNA The In-house Version of Trust Factory‘s DNA Service http://www.panagenda.com/en_uk/idna
  • 53. Instant and Ongoing Analytics for Servers, Clients, Apps & More • Unique Insights and Instant Value • Executive Decision-Making Support • Validation of Business Cases & Vendor Proposals • Develop Innovation Strategy • Turn Data into Knowledge • • • • Hassle-free data collection from many different data sources Instantly turns your data into meaningful reports Move from reactive to proactive operations Helps to fix, foresee and prevent problems with root cause identification • Gain answers to questions you never knew you could ask
  • 54. Instant and Ongoing Analytics for Servers, Clients, Apps & More • Facts and Architecture • Up and running in half an hour - turnkey virtual softwareappliance (Linux/VMWare) • Non-intrusive, agent-less software - no installations required on analyzed systems • Data ware house access possible for data use with existing reporting solutions • HTML5 and PDF export for offline reports
  • 55.
  • 56.
  • 57.
  • 58.
  • 59.
  • 60.
  • 61.
  • 62.
  • 63.
  • 64.
  • 65.
  • 67. How to Engage • Master Agreement is in Place with IBM since 2003: • Global Master Agreement Number: • Trust Factory Supplier Number: • panagenda: • • • • 4902NL0239 1000216663 Schreyvogelgasse 3/10 :: 1010 Vienna :: Austria Web: http://www.panagenda.com Email: office@panagenda.com Fax: +43 1 89 012 89 – 15 • Our business partners in Italy:
  • 68. Grazie agli sponsor per aver reso possibile i Dominopoint Days 2013! Main Sponsor Vad sponsor Platinum sponsor Gold sponsor

Notas do Editor

  1. When performing the data collection, the DNA collector will populate itself by taking server documents from the Domino Directories. By default the directory is taken from the homeserver of the user-id that performs the collector, but the customer is free to add more server documents from additional directories. With a populated collector database, each server will be verified for connectivity and sufficient access to log files. In case the Notes client cannot reach certain servers, the customer may decide to place them out of scope. Another reason for placing servers out of scope may be to discard activity on servers in the development and test environment. DNA will always attempt to collect 7 days worth of log data from the servers in scope. In the event that a server log does not contain 7 days of data, or when the server log has been removed and recreated after e.g. a crash, the collector will be unable to collect data that is missing.
  2. This slide summarizes the optimization potential as it is observed within the customer environment today. Each topic described here, will be explained in more detail within the remaining slides of this presentation.
  3. In this benchmark, DNA calcules the number of active users as a percentage of the number of person documents registered in the Domino directories of the customer. User are considered active as soon as the user has had at least one user session towards one of the servers in scope, with a rich client, during the 7 days of analysis. Web users are not included in this DNA analysis. Purpose of this slide: If the result is low this could indicate that only a small number of servers have been placed in scope for this analysis. When all servers were included, a low score might indicate that the directories containt person documents that are no longer in use.
  4. This benchmark looks at the amount of time notes clients spent online with the Domino servers. The analysis is split up into two measures: 1. total time online during the 7 day period, expressed in hours; 2. average session duration expressed in minutes; Average session duration has a negative correlation with network bandwidth consumption. The longer an average session lasts, the lower the network consumption. High session duration may indicate performance issues in the network or at the servers. Notice that with the customer on the right, each user had sessions open to separate mail and application servers. This is why the customer scored a total online time of more than 40 hours. Usually, we see that customer who deploy local mail file replicas (where users do not work on server but on their local replica) score significantly lower in session duration, and at higher network bandwidth consumption.
  5. This benchmark shows the total number of documents read and written in the 7 day period that was analyzed. Note that user activity can be caused in several ways: user clicking on desktop icon and workin interactively on the server; user’s workstation starts replicating local databases with a server; workstation checks for new mail; Scheduled Notes agent on a desktop starts interacting with server(s). All these actions result in user sessions that are logged in the log.nsf. It is not easy to draw conclusions from this analysis, other than that the current customer under investigation is relatively heavier or lighter than the DNA average. Also, be aware that system-type accounts that are defined in a person document, are considered in this analysis. Especially fax workstations and rdbms connectors may impact the outcome of this analysis significantly.
  6. This benchmark compares the network bandwidth consumption. Two measures are shown for end users connecting to Domino servers. One measure shows the network traffic from desktops towards servers, the other shows the opposite direction. Bandwidth consumption is expressed in kilobits per second. Low scores may indicate performance issues either in the network, or at the servers. While high scores may prove high performance, it can also indicate excessive use patterns due to misconfiguration of the desktops. As an example, consider desktops that have a local mail file replica, while the end user keeps working online on the server. This results in double the amount of traffic and higher bandwidth levels. Lotus offers network compression that reduce the network traffic significantly. This is analyzed too by DNA.
  7. Another method to profile end user demand (user segmentation) is by taking a look at the distinct number of working hours per day that users show active on the server park. This analysis does not show the working hours of end users, but observes how many distinct hours the user showed activity, on average per day. As an example: remote non-office workers (e.g. salesmen visiting customers all day) typically replicate with their home server in the morning (1 hour observed), go on the road all day and replicate again in the evening (another hour observed). Many system accounts (monitoring workstations, fax machines operating with notes) show activity up to 24x7. This chart expresses the percentage of the total number of active users in each category.
  8. This analysis presents an overview of the overall user demand characteristics. Total demand is expressed in 6 columns, with each column representing 100% of that type of demand scored during the week of analysis. Each column is then split up into various types of demand: Checks for new mail shows Notes clients checking for new mail; System dbs represents access to system databases; Mail files: access to end user mail files; Directories: access to Domino Directories; Applications: access to application databases* Application databases are identified as follows: Of all databases inventoried, DNA substracts mail and mailin files, ‘known’ system databases and domino directories. What remains is a set of databases that are considered applications. Although this is not a 100% accurate method, it does provide a solid understanding of the types of user demand.
  9. This analysis is revealing how end users make use of Notes databases, in terms of network traffic. Every bubble on this chart represents a database. Databases have different colors, indicating the type of database. The size of each bubble is defined by the distinct number of end users that showed activity during the 7 day period that was analyzed. The horizontal and vertical distribution of bubbles reflect the amount of network traffic (bytes read and written towards each database, logarithmic scale). Databases in the lower left corner are the most light in terms of network consumption, while databases in the upper right hand are the most network intensive. While this analysis presents up to 10,000 most used databases, the underlaying factsheet does contain all databases that have been touched. Trust Factory is offering an optional cluster plotter component that enables customers to generate a wide variety of angles in analyzing database utilization.
  10. A significant optimization potential can be found by analyzing user accounts that show excessive demand patterns. Often, we see that very few user accounts consume one third or more of the total network and server capacity. DNA is able to classify user accounts by means of comparing their individual behavior with the organization average. While the underlaying algorhitm is rather complex, it basically comes down to the following classification: Light: below or on average with the overall average; Moderate: causing a load that is 10 - 100 times more than the average; Intensive: causing a load that is 100 – 1,000 times more heavy than average; Extreme: causing a load that is more than 1,000 times more heavy. For each class of user account, this chart shows their impact on the total user demand caused in the 7 days analyzed. This total demand is expressed in 6 measures. The numbers behind the legend indicate the number of users in that class. Details for the 10 most heavy accounts are given in the next slide.
  11. This analysis shows the demand caused by the 10 most heavy user accounts, during the 7 day period of analysis. The heaviest account is shown on top. With the DNA factsheet, the customer can identify in detail which servers and databases were touched by these heavy user accounts. This knowledge gives a solid indication if the traffic is really necessary or not. Mis-configured desktops or functional systems such as e.g. fax or archiving solutions often cause an extreme load on the network and servers.
  12. This slide gives an indication of over capacity in the server park. Each server is classified according to the maximum number of concurrent end user sessions it has served, over the 7 day analysis period. Load levels on servers in the yellow area are very low and can often be redistributed onto other servers. Functional servers (smtp, hubs, blackberry, sametime) often show very low session levels. Use the factsheet to verify which servers fall in each category. Customers with a highly centralized server park often show less over capacity than customers with a very decentralized server park.
  13. This analysis topic reveals the total session concurrency caused by end users working on Domino servers, in each of the 168 hours (7 days) that were analyzed. For time-series charts, the timezone reflected on the horizontal axis is equal to that of the workstation that was used for the data collection.
  14. Network compression is a feature that was introduced with Lotus Notes and Domino release 6. The compression ratio we see at customers is around 40%, so the benefits of this feature are significant. For network compression to function properly, a setting needs to be in place at both ends of the connection, so both on all servers as well as on every desktop. This is usually not the case. With this analysis, we show how much of the total network traffic was making use of compression (pie chart). In addition, DNA is presenting for all servers and users if compression has been enabled or not. Customers that make use of other compression solutions in their network, may want to reverse the purpose of this analysis. In these situations, customers may want to disable Notes network compression. The factsheet reveal which servers and users make use of compression.
  15. Description: This analysis produces insight into how capacity is being utilized in the database landscape. The left hand table shows how many databases have been deployed, and how many of these have been touched by end users during the analysis period. The right hand table does the analysis on the same databases, but then for storage that these databases occupy. Interpretation: This analysis gives a solid indication for the amount of over capacity that exists in the database landscape. Organizations with a highly decentralized server park often show higher levels of over capacity. Many organizations have seasonal applications that are used once per month, quarter or year. As this DNA analysis covers a 7 day period, these kind of applications may show as unused. Side note: Databases that are not recorded in the catalog.nsf are not included in this analysis, therefor the numbers presented in this analysis may slightly differ from those presented in other analysis topics
  16. When the Namelookupcachepool utilization is clipping this could be an indication that the amount of memory assigned to the namelookupcache is insufficient. Default value is 16MB. Namelookup requests that are not found in the cache, result in the server going to disk to read the data. This slows down server performance. See: http://www-10.lotus.com/ldd/stwiki.nsf/dx/Optimizing_Name_Lookup_Sametime_server