Lorenzo Alberton, profile picture
Uploaded byLorenzo Alberton
87,721 views

The Art of Scalability - Managing growth

The document discusses scalability in systems, highlighting its importance in managing growth through effective people, processes, and technology. It emphasizes the need for role clarity, leadership, and measurable goals to ensure efficient scalability and outlines critical processes for managing and testing system performance. Additionally, it covers architectural principles and strategies for fault isolation, data management, and effective monitoring to enhance scalability.

Embed presentation

1 / 123
2 / 123
3 / 123
4 / 123
5 / 123
6 / 123
7 / 123
8 / 123
9 / 123
10 / 123
11 / 123
12 / 123
13 / 123
14 / 123
15 / 123
16 / 123
17 / 123
18 / 123
19 / 123
20 / 123
21 / 123
22 / 123
23 / 123
24 / 123
25 / 123
26 / 123
27 / 123
28 / 123
29 / 123
30 / 123
31 / 123
32 / 123
33 / 123
34 / 123
35 / 123
36 / 123
37 / 123
38 / 123
39 / 123
40 / 123
41 / 123
42 / 123
43 / 123
44 / 123
45 / 123
46 / 123
47 / 123
48 / 123
49 / 123
50 / 123
51 / 123
52 / 123
53 / 123
54 / 123
55 / 123
56 / 123
57 / 123
58 / 123
59 / 123
60 / 123
61 / 123
62 / 123
63 / 123
64 / 123
65 / 123
66 / 123
67 / 123
68 / 123
69 / 123
70 / 123
71 / 123
72 / 123
73 / 123
74 / 123
75 / 123
76 / 123
77 / 123
78 / 123
79 / 123
80 / 123
81 / 123
82 / 123
83 / 123
84 / 123
85 / 123
86 / 123
87 / 123
88 / 123
89 / 123
90 / 123
91 / 123
92 / 123
93 / 123
94 / 123
95 / 123
96 / 123
97 / 123
98 / 123
99 / 123
100 / 123
101 / 123
102 / 123
103 / 123
104 / 123
105 / 123
106 / 123
107 / 123
108 / 123
109 / 123
110 / 123
111 / 123
112 / 123
113 / 123
114 / 123
115 / 123
116 / 123
117 / 123
118 / 123
119 / 123
120 / 123
121 / 123
122 / 123
123 / 123
The Art of Scalabiliity Managing Growth Lorenzo Alberton Amsterdam, 11th June 2010
Scalability Scalability is a desirable property of a system, a network, a business or a process, which indicates its ability to handle growing amounts of work http://en.wikipedia.org/wiki/Scalability 2
Scalable ≠ Fast A service is said to be scalable if when we increase the resources in a system, it results in increased performance in a manner proportional to resources added. http://www.julianbrowne.com/article/viewer/scalability Increasing performance in general means serving more units of work, but it can also be to handle larger units of work, such as when data sets grow. http://highscalability.com/amazon-architecture 3
Scalability Is About... People Processes Technology 4
People Staffing, Roles, Leadership, Management 5
Roles And Responsibilities Role-clarity 6
Roles And Responsibilities Role-clarity overlapping areas missing wasted effort, responsibilities responsibilities value-destroying conflicts, failed scale initiatives 6
Roles And Responsibilities Role-clarity overlapping areas missing wasted effort, responsibilities responsibilities value-destroying conflicts, failed scale initiatives Key scale-related responsibilities Set measurable goals Staff the team with the appropriate skills Define and implement a scalable architecture Test, monitor, develop future demand projections Define future changes based on the analysis 6
Leadership Inspire people Set the right vision and goals Create the right culture Create the right tools 7
Leadership } Inspire people Set the right vision and goals Accelerator for growth Create the right culture Create the right tools 7
Leadership } Inspire people Set the right vision and goals Accelerator for growth Create the right culture Create the right tools vision = where we are going mission = general direction on how to get there goals = milestones along the path 7
Leadership } Inspire people Set the right vision and goals Accelerator for growth Create the right culture Create the right tools vision = where we are going mission = general direction on how to get there goals = milestones along the path S Specific M Measurable A Achievable (but Aggressive) R Realistic T Time-bound 7
Leadership } Inspire people Set the right vision and goals Accelerator for growth Create the right culture Create the right tools vision = where we are going mission = general direction on how to get there goals = milestones along the path S Specific Chip & Dan Heat, “Switch: How To Change Things When Change Is Hard” M Measurable A Achievable (but Aggressive) People R Realistic - Direct the rider T Time-bound - Motivate the elephant - Shape the path 7
Management Project Management Goals Projects Tasks Individuals Measurement Communication Resolution 8
Management Project Management Goals Projects Tasks Individuals Measurement Communication Resolution People Management Hiring Firing Growth 8
Organisational Structure And Team size Too small Too big Micromanaging Poor communication managers Low morale Overworked team Low productivity members 9
Team Structure functional CTO PM PM PM Designer Developer Tester Designer Developer Tester Designer Developer Tester Designer Developer Tester Designers Developers Testers 10
Team Structure functional matrix CTO PM PM PM Proj 1 PM Designer Developer Tester Proj 2 PM Designer Developer Tester Proj 3 PM Designer Developer Tester Proj 4 PM Designer Developer Tester Designers Developers Testers 10
Building Processes For Scale 11
Why Are Processes Critical? Augment management of teams and employees Standardise actions in repetitive tasks Reduce mundane decisions to focus on grander ideas Allow the team to react quickly to crisis Determine system capacity and scalability needs 12
Why Are Processes Critical? Augment management of teams and employees Standardise actions in repetitive tasks Reduce mundane decisions to focus on grander ideas Allow the team to react quickly to crisis Determine system capacity and scalability needs Challenge 12
Why Are Processes Critical? Augment management of teams and employees Standardise actions in repetitive tasks Reduce mundane decisions to focus on grander ideas Allow the team to react quickly to crisis Determine system capacity and scalability needs Challenge right amount 12
Why Are Processes Critical? Augment management of teams and employees Standardise actions in repetitive tasks Reduce mundane decisions to focus on grander ideas Allow the team to react quickly to crisis Determine system capacity and scalability needs Challenge right amount right process 12
Why Are Processes Critical? Augment management of teams and employees Standardise actions in repetitive tasks Reduce mundane decisions to focus on grander ideas Allow the team to react quickly to crisis Determine system capacity and scalability needs Challenge right amount right process right time 12
Determining Headroom For Apps Capacity Current Load 13
Determining Headroom For Apps Capacity Current Load 13
Determining Headroom For Apps Capacity Current Load 13
Determining Headroom For Apps Why? Capacity Planning annual budget Hiring plan Current Load Prioritisation 13
Headroom Process 1. Identify major components 14
Headroom Process 1. Identify major components 2. Identify responsible team 14
Headroom Process 1. Identify major components 2. Identify responsible team 315 queries/sec 20MB/min 3. Determine usage and capacity 14
Headroom Process 1. Identify major components 2. Identify responsible team 315 queries/sec 20MB/min 3. Determine usage and capacity 4. Determine growth rate 14
Headroom Process (ideal usage percentage) x (max capacity) - (current usage) - 1. Identify major components 12 2. Identify responsible team ∑ (growth(t) - (optimisation projects(t))) = ____________________________________ t=1 Headroom 315 queries/sec 20MB/min L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley M. 3. Determine usage and capacity 4. Determine growth rate 14
Joint Architecture Design + Review Board Engineering Architecture Operations M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 15
Joint Architecture Design + Review Board Engineering Architecture Operations M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 15
Joint Architecture Design + Review Board Engineering Architecture Architecture Review Board Operations M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 15
Joint Architecture Design + Review Board Meeting Engineering State goal Review alternative designs Architecture Q&A session Deliberation Architecture Review Board Vote Conclusion Operations M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 15
Joint Architecture Design + Review Board Meeting Engineering State goal Review alternative designs Architecture Q&A session Deliberation Architecture Review Board Vote Conclusion Operations M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 15
Controlling Change in Production Environment 16
Controlling Change in Production Environment Change Management Process Proposal Approval Scheduling Logging Review 16
Controlling Change in Production Environment Change Management Process Proposal Approval Scheduling Logging Review Change Identification Process Date & time System undergoing Expected of the change the change results Contact information Rollback procedure 16
Determining Risk #1: Gut Feeling http://dilbert.com/strips/comic/2008-05-08/ 17
Determining Risk #2: Traffic Lights Feature 1 Feature 2 Feature 3 18
Determining Risk #2: Traffic Lights Feature 1 Feature 2 = Overall Release Feature 3 18
Determining Risk #3: FMEA Failure Mode and Effect Analysis Likelihood Severity Ability Total Remed- Revised Failure Feature Effect of If Failure to Risk iation Risk Mode Failure Occurs Detect Score Actions Score User User not - do this data not registered 3 3 3 27 3 - do that saved Sign Up Users Users can given access 1 9 3 27 - do sth 9 wrong other’s privileges data CC Credit number CC theft not 1 9 1 9 N/A 9 Card risk encrypted 19
Managing Risk Rules Risk Level New Feature Release < 150 pts * Bug Fix Release < 50 pts * Peak-usage-time release < 10 pts * Off-peak release < 200 pts * * Numbers are just indicative figures 20
Managing Risk (Human Factor) Rules Risk Tolerance Level 6-hour period < 150 pts * 12-hour period < 250 pts * 24-hour period < 350 pts * 72-hour period < 500 pts * * Numbers are just indicative figures 21
Managing Incidents And Problems Detect, Report, Investigate, Escalate, Resolve approach M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley Restore services in a timely and cost-effective manner Contain chaos: each person has a place Determine root cause and correct problems Review issues regularly 22
Managing Incidents And Problems Detect, Report, Investigate, Escalate, Resolve approach M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley Restore services in a timely and cost-effective manner Contain chaos: each person has a place Determine root cause and correct problems Review issues regularly Post-mortem Process Cross-functional brainstorming meeting 22
Performance (Load) Testing 23
Performance (Load) Testing ✓1.5k users/sec 1. Establish success criteria ✓RT < 150ms 23
Performance (Load) Testing ✓1.5k users/sec 1. Establish success criteria ✓RT < 150ms 2. Establish the test environment TEST ≅ LIVE 23
Performance (Load) Testing ✓1.5k users/sec 1. Establish success criteria ✓RT < 150ms 2. Establish the test environment TEST ≅ LIVE Pareto rule 3. Define the tests (for different things) 20% - 80% 23
Performance (Load) Testing ✓1.5k users/sec 1. Establish success criteria ✓RT < 150ms 2. Establish the test environment TEST ≅ LIVE Pareto rule 3. Define the tests (for different things) 20% - 80% 4. Identify what needs to be monitored CPU - Memory What data needs to be collected TTL, RT, Services 23
Performance (Load) Testing ✓1.5k users/sec 1. Establish success criteria ✓RT < 150ms 2. Establish the test environment TEST ≅ LIVE Pareto rule 3. Define the tests (for different things) 20% - 80% 4. Identify what needs to be monitored CPU - Memory What data needs to be collected TTL, RT, Services CPU: 90% 5. Run, analyse, report to engineers RT: 180ms 2K SimUsers/sec 23
Performance (Load) Testing ✓1.5k users/sec 1. Establish success criteria ✓RT < 150ms 2. Establish the test environment TEST ≅ LIVE Pareto rule 3. Define the tests (for different things) 20% - 80% 4. Identify what needs to be monitored CPU - Memory What data needs to be collected TTL, RT, Services CPU: 90% 5. Run, analyse, report to engineers RT: 180ms 2K SimUsers/sec 6. Repeat tests and analysis Rinse and repeat 23
Stress Testing 24
Stress Testing 24
Stress Testing 24
Stress Testing JMeter Load Runner The Grinder Avalanche http://www.opensourcetesting.org/performance.php 24
Barrier Conditions Architecture review board Code reviews Manual and automated QA processes Performance testing Dev, Test, Stage and Live environments Production monitoring and measurement 25
Technology Architecting scalable solutions 26
Designing For Any Technology Dell WatchGuard Cisco CSS 11501 HP ProLiant DL HP Media Cache Server Appliance 27
Designing For Any Technology Dell WatchGuard Cisco CSS 11501 HP ProLiant DL HP Media Cache Server Appliance 27
Designing For Any Technology Dell WatchGuard Firewall Load Balancer Cisco CSS 11501 HP ProLiant DL Application Servers HP Media Cache Server Appliance DB Server Media / Cache 27
Architectural Principles 28
Architectural Principles +1 N + 1 design 28
Architectural Principles +1 N + 1 design for rollback 28
Architectural Principles +1 N + 1 design for rollback to be disabled 28
Architectural Principles +1 N + 1 design for rollback to be disabled to be monitored 28
Architectural Principles +1 N + 1 design for rollback to be disabled to be for multiple monitored live sites 28
Architectural Principles +1 N + 1 design for rollback to be disabled to be for multiple use mature monitored live sites technology 28
Architectural Principles +1 N + 1 design for rollback to be disabled to be for multiple use mature monitored live sites technology asynchronous design 28
Architectural Principles +1 N + 1 design for rollback to be disabled to be for multiple use mature monitored live sites technology asynchronous stateless design systems 28
Architectural Principles +1 N + 1 design for rollback to be disabled to be for multiple use mature monitored live sites technology asynchronous stateless buy when design systems non core 28
Focus On Core Competencies vs. Build Buy 29
Asynchronous Design 30
Asynchronous Design 30
Stateless Systems State is often useful, but has a significant cost (replication between data centres, synchronous calls...) 31
Stateless Systems State is often useful, but has a significant cost (replication between data centres, synchronous calls...) A B ? Avoidance No sessions / Sticky sessions 31
Stateless Systems State is often useful, but has a significant cost (replication between data centres, synchronous calls...) A B ? Avoidance Decentralisation No sessions / Data in the cookie / Sticky sessions Cookie with hash 31
Stateless Systems State is often useful, but has a significant cost (replication between data centres, synchronous calls...) A B ? Avoidance Decentralisation Centralisation No sessions / Data in the cookie / Store cookies in the Sticky sessions Cookie with hash db or in memcached 31
Creating Fault Isolative Structures 32
Creating Fault Isolative Structures Increase availability Limit impact of failures Easier debugging 32
Creating Fault Isolative Structures Increase availability Limit impact of failures Easier debugging First 32
Creating Fault Isolative Structures Increase availability Limit impact of failures Easier debugging Functions causing repetitive problems First 32
Creating Fault Isolative Structures Increase availability Limit impact of failures Easier debugging Functions Natural layout causing or topology repetitive of the site problems First 32
Scale Directions M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 33
Scale Directions cloning of entities or data - unbiased distribution of work x M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 33
Scale Directions cloning of entities or data - unbiased distribution of work x y separation of work by activity or data M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 33
Scale Directions cloning of entities or data - unbiased distribution of work x y z separation of work separation of work by person by activity or data for whom the work is done M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 33
Splitting Applications For Scale 34
Splitting Applications For Scale mirroring x + scale transactions - scale data 34
Splitting Applications For Scale mirroring x + scale transactions - scale data + fault isolation + scale function data - scale customer data y split by service 34
Splitting Applications For Scale mirroring x + scale transactions - scale data + fault isolation + fault isolation + scale function data + scale customer data - scale customer data - scale function data y z split by need / split by service location / value 34
Splitting Databases For Scale 35
Splitting Databases For Scale data cloning (replication / clustering) x + easy to implement + scale transaction volume - scale data size and growth 35
Splitting Databases For Scale data cloning (replication / clustering) x + easy to implement + scale transaction volume - scale data size and growth + fault isolation + reduce query time - more difficult - data migration y split by service / resource / data affinity 35
Splitting Databases For Scale data cloning (replication / clustering) x + easy to implement + scale transaction volume - scale data size and growth + balanced demand + fault isolation + fault isolation + reduce query time + scale data and trans. - more difficult - more costly - data migration y z split by service / split by modulus / resource / data affinity hash-based lookups 35
Caching For Performance & Scale 36
Caching For Performance & Scale Object Caches Usually serialized (marshalling / unmarshalling) get() / set() / replace() APC, Memcached 36
Caching For Performance & Scale Object Caches Application Caches Usually serialized Proxy caches (marshalling / Reverse proxy unmarshalling) caches get() / set() / HTTP headers replace() ISP/Uni proxies APC, Memcached Squid, Varnish, mod_cache 36
Caching For Performance & Scale Object Caches Application Caches CDNs Usually serialized Proxy caches Multiple locations (marshalling / / backbones Reverse proxy unmarshalling) caches get() / set() / HTTP headers CNAME entries replace() ISP/Uni proxies Akamai, Coral, APC, Memcached Squid, Varnish, Limelight... mod_cache 36
Solving Other Issues ...and challenges 37
Too Much Data 38
Too Much Data The more storage ...the more storage management 38
Too Much Data The more storage ...the more storage management storage costs people and software power and space processing power backup time and costs 38
Too Much Data The more storage ...the more storage management storage costs people and software power and space processing power backup time and costs Evaluate data retention policy Consider multi-tiered storage Distribute work (MapReduce) 38
Clouds And Grids Cheap, on-demand storage and compute capacity Cost (pay for what you use) High computation rates Speed (procurement, Shared infrastructure (with provisioning, deployment) proper scheduling Flexibility (change / Unused capacity (SETI@H) reconfigure environment) Security, portability, control Not shared simultaneously Limitations of virtualisation Monolithic applications Performance Complexity (debugging, OS) 39
Monitoring 40
Monitoring 1. Is there a problem? User experience / Business metrics monitors 2. Where is the problem? System monitors (threshold - variance) 3. What is the problem? Application monitors 40
Monitoring 1. Is there a problem? User experience / Business metrics monitors 2. Where is the problem? System monitors (threshold - variance) 3. What is the problem? Application monitors Keep Signal vs. Noise ratio high 40
Monitoring 1. Is there a problem? User experience / Business metrics monitors 2. Where is the problem? System monitors (threshold - variance) 3. What is the problem? Application monitors Keep Signal vs. Noise ratio high 40
Questions ? 41
Links & sources http://www.slideshare.net/postwait/scalable- internet-architecture http://highscalability.com/blog/2009/4/2/art- of-scalability-1-scalability-principles.html http://agile.dzone.com/news/approaches- organizational M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley http://theartofscalability.com/ 42
Links & sources 43
Image Credits http://www.sxc.hu/photo/1217386 http://michaelscomments.files.wordpress.com/2009/10/onion- centurion.jpg http://www.travelsd.com/_images/gallery/hires/000189.jpg http://www.socketmanufacturers.com/miniature-circuit-breaker/ DZ47-63-3P-Miniature-Circuit-Breaker.jpg http://blogs.microsoft.co.il/blogs/shair/archive/2008/06/19/load- testing-features-of-visual-studio-team-system.aspx http://www.alibaba.com/member/de100430205.html/viewimg/ photo/103590047/Boxing_Ring_Competition_AIBA_Ring.jpg.html http://brandonsmarathon.com/wp-content/uploads/2009/08/ Olympics+Day+3+Swimming+43rPmSVmwHql.jpg http://en.wikipedia.org/wiki/File:Synchronized_swimming_- _Russian_team.jpg http://www.flickr.com/photos/bugeaters/3025911233/ http://www.flickr.com/photos/cote/2763677698/ http://www.iconfinder.com 44
Thank you! Contact details: Lorenzo Alberton lorenzo@ibuildings.com http://www.alberton.info/talks http://joind.in/talk/view/1539
The Art of Scalability - Managing growth
The Art of Scalability - Managing growth
The Art of Scalability - Managing growth
The Art of Scalability - Managing growth
The Art of Scalability - Managing growth

More Related Content

PPTX
Scalability
byfelho
 
PPT
ERP and related technology
byUsman Tariq
 
PPTX
Supply chain management unit 5
bySaravanan Murugan
 
PPTX
PPT -Lean Supply Chain Presentation
byIke. M Nwamuo, MSQA
 
PPT
Change management
byMahwish Sana
 
PPTX
Coordination in a supply chain
byChaitrali Gijare
 
PPTX
Supply Chain Management module 4
byRavishankar ulle
 
PPTX
Supply chain drivers
byAnupam Basu
 
Scalability
byfelho
 
ERP and related technology
byUsman Tariq
 
Supply chain management unit 5
bySaravanan Murugan
 
PPT -Lean Supply Chain Presentation
byIke. M Nwamuo, MSQA
 
Change management
byMahwish Sana
 
Coordination in a supply chain
byChaitrali Gijare
 
Supply Chain Management module 4
byRavishankar ulle
 
Supply chain drivers
byAnupam Basu
 

What's hot

PPTX
Design thinking
byVlad Posea
 
PPTX
Change Management PPT Slides
byYodhia Antariksa
 
PPTX
System Analysis and Design
byAamir Abbas
 
PDF
Strategy Execution
byTeaching Excellence
 
PDF
Design Thinking & Innovation
byEnvisioning Labs
 
PDF
Design Thinking
byShimon Shmueli
 
PDF
Business Process Reengineering And Change Management PowerPoint Presentation ...
bySlideTeam
 
PPTX
Logistics Technology
byPatrick Montague
 
PPTX
A Guide to the SCAMPER Technique
byOlivier Serrat, PhD
 
PDF
ADKAR Change Management Model PowerPoint Presentation Slides
bySlideTeam
 
PDF
8 steps to innovation: An introduction
byvpdabholkar
 
PDF
Creativity & innovation
byLedarskapscentrum
 
PPTX
Role of IT in supply chain management
byNeelam Yadav
 
PDF
Developing Supply Chain Roadmap
bysinghmk74
 
PPTX
Big data and Hadoop
byRahul Agarwal
 
PPTX
Supply Chain Management module 3
byRavishankar ulle
 
PDF
The Process of Innovation
byJoel Wenger
 
DOCX
SCM - Framework of Structuring Drivers
byZaka Ul Hassan
 
PPTX
The role of e business in supply chain management
byJohns Joseph
 
DOCX
Sub systems of information system - MIS
bySanaRiaz789
 
Design thinking
byVlad Posea
 
Change Management PPT Slides
byYodhia Antariksa
 
System Analysis and Design
byAamir Abbas
 
Strategy Execution
byTeaching Excellence
 
Design Thinking & Innovation
byEnvisioning Labs
 
Design Thinking
byShimon Shmueli
 
Business Process Reengineering And Change Management PowerPoint Presentation ...
bySlideTeam
 
Logistics Technology
byPatrick Montague
 
A Guide to the SCAMPER Technique
byOlivier Serrat, PhD
 
ADKAR Change Management Model PowerPoint Presentation Slides
bySlideTeam
 
8 steps to innovation: An introduction
byvpdabholkar
 
Creativity & innovation
byLedarskapscentrum
 
Role of IT in supply chain management
byNeelam Yadav
 
Developing Supply Chain Roadmap
bysinghmk74
 
Big data and Hadoop
byRahul Agarwal
 
Supply Chain Management module 3
byRavishankar ulle
 
The Process of Innovation
byJoel Wenger
 
SCM - Framework of Structuring Drivers
byZaka Ul Hassan
 
The role of e business in supply chain management
byJohns Joseph
 
Sub systems of information system - MIS
bySanaRiaz789
 

Viewers also liked

KEY
Scaling Teams, Processes and Architectures
byLorenzo Alberton
 
KEY
Scalable Architectures - Taming the Twitter Firehose
byLorenzo Alberton
 
KEY
NoSQL Databases: Why, what and when
byLorenzo Alberton
 
KEY
Modern Algorithms and Data Structures - 1. Bloom Filters, Merkle Trees
byLorenzo Alberton
 
PDF
Monitoring at scale - Intuitive dashboard design
byLorenzo Alberton
 
KEY
Graphs in the Database: Rdbms In The Social Networks Age
byLorenzo Alberton
 
KEY
Trees In The Database - Advanced data structures
byLorenzo Alberton
 
Scaling Teams, Processes and Architectures
byLorenzo Alberton
 
Scalable Architectures - Taming the Twitter Firehose
byLorenzo Alberton
 
NoSQL Databases: Why, what and when
byLorenzo Alberton
 
Modern Algorithms and Data Structures - 1. Bloom Filters, Merkle Trees
byLorenzo Alberton
 
Monitoring at scale - Intuitive dashboard design
byLorenzo Alberton
 
Graphs in the Database: Rdbms In The Social Networks Age
byLorenzo Alberton
 
Trees In The Database - Advanced data structures
byLorenzo Alberton
 

Similar to The Art of Scalability - Managing growth

PPT
2012 Velocity London: DevOps Patterns Distilled
byGene Kim
 
PDF
Introduction to Lean, Agile, Scrum, & XP
bySi Alhir (Sinan Si Alhir)
 
PDF
Bigvisible journeytoagilitymilehighagile2012-120403183305-phpapp02
byInnovation Excellence
 
KEY
Leading agile product development
byArto Saari
 
PDF
How to Adopt Agile at Your Organization
byRaimonds Simanovskis
 
PPSX
Acto It Consulting Presentation
byArthurScheffer
 
PPSX
Acto It Consulting Presentation
byguest6c269db
 
PDF
The Art of Scaling People (English)
byendymi0n
 
PDF
Path to agility, Ken Schwaber
byXavier Warzee
 
PPT
7 strategic hrm performance management
byKapil Chhabra
 
PPT
4 ps
byJerry Linnins
 
PPTX
The agile vision
byIonel Condor
 
PDF
Managing Large Scale Agile Transformation
byDr. Tathagat Varma
 
PDF
Agile Transformations, the Good, the Bad and the Ugly
byRally Software
 
PPTX
Moving your organization into the fast lane metro
byMike Vincent
 
PPTX
Scrum: Enterprise Adoption
bySilvana Wasitova, Scrum & Agile Coach
 
PPTX
Always start with the "why"
byAgileSparks
 
PDF
Change Management
byBetclic Everest Group Tech Team
 
PPT
Presentation implementation challenge Twynstra Gudde Business Improvers
byMichiel Beijer
 
PPT
7 strategic hrm performance management
byKapil Chhabra
 
2012 Velocity London: DevOps Patterns Distilled
byGene Kim
 
Introduction to Lean, Agile, Scrum, & XP
bySi Alhir (Sinan Si Alhir)
 
Bigvisible journeytoagilitymilehighagile2012-120403183305-phpapp02
byInnovation Excellence
 
Leading agile product development
byArto Saari
 
How to Adopt Agile at Your Organization
byRaimonds Simanovskis
 
Acto It Consulting Presentation
byArthurScheffer
 
Acto It Consulting Presentation
byguest6c269db
 
The Art of Scaling People (English)
byendymi0n
 
Path to agility, Ken Schwaber
byXavier Warzee
 
7 strategic hrm performance management
byKapil Chhabra
 
4 ps
byJerry Linnins
 
The agile vision
byIonel Condor
 
Managing Large Scale Agile Transformation
byDr. Tathagat Varma
 
Agile Transformations, the Good, the Bad and the Ugly
byRally Software
 
Moving your organization into the fast lane metro
byMike Vincent
 
Scrum: Enterprise Adoption
bySilvana Wasitova, Scrum & Agile Coach
 
Always start with the "why"
byAgileSparks
 
Change Management
byBetclic Everest Group Tech Team
 
Presentation implementation challenge Twynstra Gudde Business Improvers
byMichiel Beijer
 
7 strategic hrm performance management
byKapil Chhabra
 

Recently uploaded

PDF
Digit Expo 2025 - EICC Edinburgh 27th November
byRay Bugg
 
PDF
Recursive Self Improvement vs Continuous Learning
byBob Marcus
 
PPTX
The Landscape of Computer Software Development Companies
byYash Singh
 
PPTX
Combining Induction and Transduction for Abstract Reasoning.pptx
byallen578468
 
PDF
TrustArc Webinar - Assessing AI Risk with Confidence
byTrustArc
 
PDF
Generative AI in UiPath: Mastering the Generative Extractor for Intelligent D...
byDianaGray10
 
PDF
ElyriaSoftware — Powering the Future with Blockchain Innovation
byElyria Software
 
PDF
Unlocking the Power of Salesforce Architecture: Frameworks for Effective Solu...
byvarsha30tiwari
 
PPTX
Basics of Identity Access Management In mordern Infrastructure
byPrinceXavier18
 
PDF
Making Sense of Raster: From Bit Depth to Better Workflows
bySafe Software
 
PDF
Top 7 Manufacturing Software for Small Businesses Boosting Growth in 2025
byEnvertis Software Solutions
 
PDF
Unser Jahresrückblick – MarvelClient in 2025
bypanagenda
 
PDF
Incident Response Planning with a Foundation Model
byKim Hammar
 
PDF
Safeguarding AI-Based Financial Infrastructure
byYasir Naveed Riaz
 
PDF
December Patch Tuesday
byIvanti
 
PPTX
The Future of IT Service Management AI Automation & Beyond.pptx
byChetu
 
PDF
Security Technologys: Access Control, Firewall, VPN
byShielaLasala
 
PDF
AI and Computer Architecture: 200 Years Together
byDmitry Zinoviev
 
DOCX
Introduction to the World of Computers (Hardware & Software)
byALIABBAS ABASOV
 
PDF
8 LLM Surveys https://tinyurl.com/bdz8e6fp
byBob Marcus
 
Digit Expo 2025 - EICC Edinburgh 27th November
byRay Bugg
 
Recursive Self Improvement vs Continuous Learning
byBob Marcus
 
The Landscape of Computer Software Development Companies
byYash Singh
 
Combining Induction and Transduction for Abstract Reasoning.pptx
byallen578468
 
TrustArc Webinar - Assessing AI Risk with Confidence
byTrustArc
 
Generative AI in UiPath: Mastering the Generative Extractor for Intelligent D...
byDianaGray10
 
ElyriaSoftware — Powering the Future with Blockchain Innovation
byElyria Software
 
Unlocking the Power of Salesforce Architecture: Frameworks for Effective Solu...
byvarsha30tiwari
 
Basics of Identity Access Management In mordern Infrastructure
byPrinceXavier18
 
Making Sense of Raster: From Bit Depth to Better Workflows
bySafe Software
 
Top 7 Manufacturing Software for Small Businesses Boosting Growth in 2025
byEnvertis Software Solutions
 
Unser Jahresrückblick – MarvelClient in 2025
bypanagenda
 
Incident Response Planning with a Foundation Model
byKim Hammar
 
Safeguarding AI-Based Financial Infrastructure
byYasir Naveed Riaz
 
December Patch Tuesday
byIvanti
 
The Future of IT Service Management AI Automation & Beyond.pptx
byChetu
 
Security Technologys: Access Control, Firewall, VPN
byShielaLasala
 
AI and Computer Architecture: 200 Years Together
byDmitry Zinoviev
 
Introduction to the World of Computers (Hardware & Software)
byALIABBAS ABASOV
 
8 LLM Surveys https://tinyurl.com/bdz8e6fp
byBob Marcus
 

The Art of Scalability - Managing growth

  • 1.
    The Art ofScalabiliity Managing Growth Lorenzo Alberton Amsterdam, 11th June 2010
  • 2.
    Scalability Scalability is a desirable property of a system, a network, a business or a process, which indicates its ability to handle growing amounts of work http://en.wikipedia.org/wiki/Scalability 2
  • 3.
    Scalable ≠ Fast A service is said to be scalable if when we increase the resources in a system, it results in increased performance in a manner proportional to resources added. http://www.julianbrowne.com/article/viewer/scalability Increasing performance in general means serving more units of work, but it can also be to handle larger units of work, such as when data sets grow. http://highscalability.com/amazon-architecture 3
  • 4.
    Scalability Is About... People Processes Technology 4
  • 5.
  • 6.
  • 7.
    Roles And Responsibilities Role-clarity overlapping areas missing wasted effort, responsibilities responsibilities value-destroying conflicts, failed scale initiatives 6
  • 8.
    Roles And Responsibilities Role-clarity overlapping areas missing wasted effort, responsibilities responsibilities value-destroying conflicts, failed scale initiatives Key scale-related responsibilities Set measurable goals Staff the team with the appropriate skills Define and implement a scalable architecture Test, monitor, develop future demand projections Define future changes based on the analysis 6
  • 9.
    Leadership Inspire people Set the right vision and goals Create the right culture Create the right tools 7
  • 10.
    Leadership } Inspire people Set the right vision and goals Accelerator for growth Create the right culture Create the right tools 7
  • 11.
    Leadership } Inspire people Set the right vision and goals Accelerator for growth Create the right culture Create the right tools vision = where we are going mission = general direction on how to get there goals = milestones along the path 7
  • 12.
    Leadership } Inspire people Set the right vision and goals Accelerator for growth Create the right culture Create the right tools vision = where we are going mission = general direction on how to get there goals = milestones along the path S Specific M Measurable A Achievable (but Aggressive) R Realistic T Time-bound 7
  • 13.
    Leadership } Inspire people Set the right vision and goals Accelerator for growth Create the right culture Create the right tools vision = where we are going mission = general direction on how to get there goals = milestones along the path S Specific Chip & Dan Heat, “Switch: How To Change Things When Change Is Hard” M Measurable A Achievable (but Aggressive) People R Realistic - Direct the rider T Time-bound - Motivate the elephant - Shape the path 7
  • 14.
    Management Project Management Goals Projects Tasks Individuals Measurement Communication Resolution 8
  • 15.
    Management Project Management Goals Projects Tasks Individuals Measurement Communication Resolution People Management Hiring Firing Growth 8
  • 16.
    Organisational Structure AndTeam size Too small Too big Micromanaging Poor communication managers Low morale Overworked team Low productivity members 9
  • 17.
    Team Structure functional CTO PM PM PM Designer Developer Tester Designer Developer Tester Designer Developer Tester Designer Developer Tester Designers Developers Testers 10
  • 18.
    Team Structure functional matrix CTO PM PM PM Proj 1 PM Designer Developer Tester Proj 2 PM Designer Developer Tester Proj 3 PM Designer Developer Tester Proj 4 PM Designer Developer Tester Designers Developers Testers 10
  • 19.
  • 20.
    Why Are ProcessesCritical? Augment management of teams and employees Standardise actions in repetitive tasks Reduce mundane decisions to focus on grander ideas Allow the team to react quickly to crisis Determine system capacity and scalability needs 12
  • 21.
    Why Are ProcessesCritical? Augment management of teams and employees Standardise actions in repetitive tasks Reduce mundane decisions to focus on grander ideas Allow the team to react quickly to crisis Determine system capacity and scalability needs Challenge 12
  • 22.
    Why Are ProcessesCritical? Augment management of teams and employees Standardise actions in repetitive tasks Reduce mundane decisions to focus on grander ideas Allow the team to react quickly to crisis Determine system capacity and scalability needs Challenge right amount 12
  • 23.
    Why Are ProcessesCritical? Augment management of teams and employees Standardise actions in repetitive tasks Reduce mundane decisions to focus on grander ideas Allow the team to react quickly to crisis Determine system capacity and scalability needs Challenge right amount right process 12
  • 24.
    Why Are ProcessesCritical? Augment management of teams and employees Standardise actions in repetitive tasks Reduce mundane decisions to focus on grander ideas Allow the team to react quickly to crisis Determine system capacity and scalability needs Challenge right amount right process right time 12
  • 25.
    Determining Headroom ForApps Capacity Current Load 13
  • 26.
    Determining Headroom ForApps Capacity Current Load 13
  • 27.
    Determining Headroom ForApps Capacity Current Load 13
  • 28.
    Determining Headroom ForApps Why? Capacity Planning annual budget Hiring plan Current Load Prioritisation 13
  • 29.
    Headroom Process 1. Identifymajor components 14
  • 30.
    Headroom Process 1. Identifymajor components 2. Identify responsible team 14
  • 31.
    Headroom Process 1. Identifymajor components 2. Identify responsible team 315 queries/sec 20MB/min 3. Determine usage and capacity 14
  • 32.
    Headroom Process 1. Identifymajor components 2. Identify responsible team 315 queries/sec 20MB/min 3. Determine usage and capacity 4. Determine growth rate 14
  • 33.
    Headroom Process (ideal usage percentage) x (max capacity) - (current usage) - 1. Identify major components 12 2. Identify responsible team ∑ (growth(t) - (optimisation projects(t))) = ____________________________________ t=1 Headroom 315 queries/sec 20MB/min L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley M. 3. Determine usage and capacity 4. Determine growth rate 14
  • 34.
    Joint Architecture Design+ Review Board Engineering Architecture Operations M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 15
  • 35.
    Joint Architecture Design+ Review Board Engineering Architecture Operations M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 15
  • 36.
    Joint Architecture Design+ Review Board Engineering Architecture Architecture Review Board Operations M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 15
  • 37.
    Joint Architecture Design+ Review Board Meeting Engineering State goal Review alternative designs Architecture Q&A session Deliberation Architecture Review Board Vote Conclusion Operations M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 15
  • 38.
    Joint Architecture Design+ Review Board Meeting Engineering State goal Review alternative designs Architecture Q&A session Deliberation Architecture Review Board Vote Conclusion Operations M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 15
  • 39.
    Controlling Change inProduction Environment 16
  • 40.
    Controlling Change inProduction Environment Change Management Process Proposal Approval Scheduling Logging Review 16
  • 41.
    Controlling Change inProduction Environment Change Management Process Proposal Approval Scheduling Logging Review Change Identification Process Date & time System undergoing Expected of the change the change results Contact information Rollback procedure 16
  • 42.
    Determining Risk #1:Gut Feeling http://dilbert.com/strips/comic/2008-05-08/ 17
  • 43.
    Determining Risk #2:Traffic Lights Feature 1 Feature 2 Feature 3 18
  • 44.
    Determining Risk #2:Traffic Lights Feature 1 Feature 2 = Overall Release Feature 3 18
  • 45.
    Determining Risk #3:FMEA Failure Mode and Effect Analysis Likelihood Severity Ability Total Remed- Revised Failure Feature Effect of If Failure to Risk iation Risk Mode Failure Occurs Detect Score Actions Score User User not - do this data not registered 3 3 3 27 3 - do that saved Sign Up Users Users can given access 1 9 3 27 - do sth 9 wrong other’s privileges data CC Credit number CC theft not 1 9 1 9 N/A 9 Card risk encrypted 19
  • 46.
    Managing Risk Rules Risk Level New Feature Release < 150 pts * Bug Fix Release < 50 pts * Peak-usage-time release < 10 pts * Off-peak release < 200 pts * * Numbers are just indicative figures 20
  • 47.
    Managing Risk (HumanFactor) Rules Risk Tolerance Level 6-hour period < 150 pts * 12-hour period < 250 pts * 24-hour period < 350 pts * 72-hour period < 500 pts * * Numbers are just indicative figures 21
  • 48.
    Managing Incidents AndProblems Detect, Report, Investigate, Escalate, Resolve approach M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley Restore services in a timely and cost-effective manner Contain chaos: each person has a place Determine root cause and correct problems Review issues regularly 22
  • 49.
    Managing Incidents AndProblems Detect, Report, Investigate, Escalate, Resolve approach M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley Restore services in a timely and cost-effective manner Contain chaos: each person has a place Determine root cause and correct problems Review issues regularly Post-mortem Process Cross-functional brainstorming meeting 22
  • 50.
  • 51.
    Performance (Load) Testing ✓1.5k users/sec 1. Establish success criteria ✓RT < 150ms 23
  • 52.
    Performance (Load) Testing ✓1.5k users/sec 1. Establish success criteria ✓RT < 150ms 2. Establish the test environment TEST ≅ LIVE 23
  • 53.
    Performance (Load) Testing ✓1.5k users/sec 1. Establish success criteria ✓RT < 150ms 2. Establish the test environment TEST ≅ LIVE Pareto rule 3. Define the tests (for different things) 20% - 80% 23
  • 54.
    Performance (Load) Testing ✓1.5k users/sec 1. Establish success criteria ✓RT < 150ms 2. Establish the test environment TEST ≅ LIVE Pareto rule 3. Define the tests (for different things) 20% - 80% 4. Identify what needs to be monitored CPU - Memory What data needs to be collected TTL, RT, Services 23
  • 55.
    Performance (Load) Testing ✓1.5k users/sec 1. Establish success criteria ✓RT < 150ms 2. Establish the test environment TEST ≅ LIVE Pareto rule 3. Define the tests (for different things) 20% - 80% 4. Identify what needs to be monitored CPU - Memory What data needs to be collected TTL, RT, Services CPU: 90% 5. Run, analyse, report to engineers RT: 180ms 2K SimUsers/sec 23
  • 56.
    Performance (Load) Testing ✓1.5k users/sec 1. Establish success criteria ✓RT < 150ms 2. Establish the test environment TEST ≅ LIVE Pareto rule 3. Define the tests (for different things) 20% - 80% 4. Identify what needs to be monitored CPU - Memory What data needs to be collected TTL, RT, Services CPU: 90% 5. Run, analyse, report to engineers RT: 180ms 2K SimUsers/sec 6. Repeat tests and analysis Rinse and repeat 23
  • 57.
  • 58.
  • 59.
  • 60.
    Stress Testing JMeter Load Runner The Grinder Avalanche http://www.opensourcetesting.org/performance.php 24
  • 61.
    Barrier Conditions Architecture review board Code reviews Manual and automated QA processes Performance testing Dev, Test, Stage and Live environments Production monitoring and measurement 25
  • 62.
  • 63.
    Designing For AnyTechnology Dell WatchGuard Cisco CSS 11501 HP ProLiant DL HP Media Cache Server Appliance 27
  • 64.
    Designing For AnyTechnology Dell WatchGuard Cisco CSS 11501 HP ProLiant DL HP Media Cache Server Appliance 27
  • 65.
    Designing For AnyTechnology Dell WatchGuard Firewall Load Balancer Cisco CSS 11501 HP ProLiant DL Application Servers HP Media Cache Server Appliance DB Server Media / Cache 27
  • 66.
  • 67.
    Architectural Principles +1 N + 1 design 28
  • 68.
    Architectural Principles +1 N + 1 design for rollback 28
  • 69.
    Architectural Principles +1 N + 1 design for rollback to be disabled 28
  • 70.
    Architectural Principles +1 N + 1 design for rollback to be disabled to be monitored 28
  • 71.
    Architectural Principles +1 N + 1 design for rollback to be disabled to be for multiple monitored live sites 28
  • 72.
    Architectural Principles +1 N + 1 design for rollback to be disabled to be for multiple use mature monitored live sites technology 28
  • 73.
    Architectural Principles +1 N + 1 design for rollback to be disabled to be for multiple use mature monitored live sites technology asynchronous design 28
  • 74.
    Architectural Principles +1 N + 1 design for rollback to be disabled to be for multiple use mature monitored live sites technology asynchronous stateless design systems 28
  • 75.
    Architectural Principles +1 N + 1 design for rollback to be disabled to be for multiple use mature monitored live sites technology asynchronous stateless buy when design systems non core 28
  • 76.
    Focus On CoreCompetencies vs. Build Buy 29
  • 77.
  • 78.
  • 79.
    Stateless Systems State isoften useful, but has a significant cost (replication between data centres, synchronous calls...) 31
  • 80.
    Stateless Systems State isoften useful, but has a significant cost (replication between data centres, synchronous calls...) A B ? Avoidance No sessions / Sticky sessions 31
  • 81.
    Stateless Systems State isoften useful, but has a significant cost (replication between data centres, synchronous calls...) A B ? Avoidance Decentralisation No sessions / Data in the cookie / Sticky sessions Cookie with hash 31
  • 82.
    Stateless Systems State isoften useful, but has a significant cost (replication between data centres, synchronous calls...) A B ? Avoidance Decentralisation Centralisation No sessions / Data in the cookie / Store cookies in the Sticky sessions Cookie with hash db or in memcached 31
  • 83.
  • 84.
    Creating Fault IsolativeStructures Increase availability Limit impact of failures Easier debugging 32
  • 85.
    Creating Fault IsolativeStructures Increase availability Limit impact of failures Easier debugging First 32
  • 86.
    Creating Fault IsolativeStructures Increase availability Limit impact of failures Easier debugging Functions causing repetitive problems First 32
  • 87.
    Creating Fault IsolativeStructures Increase availability Limit impact of failures Easier debugging Functions Natural layout causing or topology repetitive of the site problems First 32
  • 88.
    Scale Directions M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 33
  • 89.
    Scale Directions cloningof entities or data - unbiased distribution of work x M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 33
  • 90.
    Scale Directions cloningof entities or data - unbiased distribution of work x y separation of work by activity or data M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 33
  • 91.
    Scale Directions cloningof entities or data - unbiased distribution of work x y z separation of work separation of work by person by activity or data for whom the work is done M. L. Abbot, M. T. Fisher, “The Art Of Scalability”, Addison Wesley 33
  • 92.
  • 93.
    Splitting Applications ForScale mirroring x + scale transactions - scale data 34
  • 94.
    Splitting Applications ForScale mirroring x + scale transactions - scale data + fault isolation + scale function data - scale customer data y split by service 34
  • 95.
    Splitting Applications ForScale mirroring x + scale transactions - scale data + fault isolation + fault isolation + scale function data + scale customer data - scale customer data - scale function data y z split by need / split by service location / value 34
  • 96.
  • 97.
    Splitting Databases ForScale data cloning (replication / clustering) x + easy to implement + scale transaction volume - scale data size and growth 35
  • 98.
    Splitting Databases ForScale data cloning (replication / clustering) x + easy to implement + scale transaction volume - scale data size and growth + fault isolation + reduce query time - more difficult - data migration y split by service / resource / data affinity 35
  • 99.
    Splitting Databases ForScale data cloning (replication / clustering) x + easy to implement + scale transaction volume - scale data size and growth + balanced demand + fault isolation + fault isolation + reduce query time + scale data and trans. - more difficult - more costly - data migration y z split by service / split by modulus / resource / data affinity hash-based lookups 35
  • 100.
  • 101.
    Caching For Performance& Scale Object Caches Usually serialized (marshalling / unmarshalling) get() / set() / replace() APC, Memcached 36
  • 102.
    Caching For Performance& Scale Object Caches Application Caches Usually serialized Proxy caches (marshalling / Reverse proxy unmarshalling) caches get() / set() / HTTP headers replace() ISP/Uni proxies APC, Memcached Squid, Varnish, mod_cache 36
  • 103.
    Caching For Performance& Scale Object Caches Application Caches CDNs Usually serialized Proxy caches Multiple locations (marshalling / / backbones Reverse proxy unmarshalling) caches get() / set() / HTTP headers CNAME entries replace() ISP/Uni proxies Akamai, Coral, APC, Memcached Squid, Varnish, Limelight... mod_cache 36
  • 104.
  • 105.
  • 106.
    Too Much Data The more storage ...the more storage management 38
  • 107.
    Too Much Data The more storage ...the more storage management storage costs people and software power and space processing power backup time and costs 38
  • 108.
    Too Much Data The more storage ...the more storage management storage costs people and software power and space processing power backup time and costs Evaluate data retention policy Consider multi-tiered storage Distribute work (MapReduce) 38
  • 109.
    Clouds And Grids Cheap, on-demand storage and compute capacity Cost (pay for what you use) High computation rates Speed (procurement, Shared infrastructure (with provisioning, deployment) proper scheduling Flexibility (change / Unused capacity (SETI@H) reconfigure environment) Security, portability, control Not shared simultaneously Limitations of virtualisation Monolithic applications Performance Complexity (debugging, OS) 39
  • 110.
  • 111.
    Monitoring 1. Is therea problem? User experience / Business metrics monitors 2. Where is the problem? System monitors (threshold - variance) 3. What is the problem? Application monitors 40
  • 112.
    Monitoring 1. Is therea problem? User experience / Business metrics monitors 2. Where is the problem? System monitors (threshold - variance) 3. What is the problem? Application monitors Keep Signal vs. Noise ratio high 40
  • 113.
    Monitoring 1. Is therea problem? User experience / Business metrics monitors 2. Where is the problem? System monitors (threshold - variance) 3. What is the problem? Application monitors Keep Signal vs. Noise ratio high 40
  • 114.
  • 115.
  • 116.
  • 117.
    Image Credits http://www.sxc.hu/photo/1217386 http://michaelscomments.files.wordpress.com/2009/10/onion- centurion.jpg http://www.travelsd.com/_images/gallery/hires/000189.jpg http://www.socketmanufacturers.com/miniature-circuit-breaker/ DZ47-63-3P-Miniature-Circuit-Breaker.jpg http://blogs.microsoft.co.il/blogs/shair/archive/2008/06/19/load- testing-features-of-visual-studio-team-system.aspx http://www.alibaba.com/member/de100430205.html/viewimg/ photo/103590047/Boxing_Ring_Competition_AIBA_Ring.jpg.html http://brandonsmarathon.com/wp-content/uploads/2009/08/ Olympics+Day+3+Swimming+43rPmSVmwHql.jpg http://en.wikipedia.org/wiki/File:Synchronized_swimming_- _Russian_team.jpg http://www.flickr.com/photos/bugeaters/3025911233/ http://www.flickr.com/photos/cote/2763677698/ http://www.iconfinder.com 44
  • 118.
    Thank you! Contact details: Lorenzo Alberton lorenzo@ibuildings.com http://www.alberton.info/talks http://joind.in/talk/view/1539