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AWS Finland March meetup – hosted by Cybercom
Selecting Enterprise IoT Platform
1
About the Presenter
Rolf Koski
Chief Technologist
Managed Cloud Services
rolf.koski@cybercom.com
https://fi.linkedin.com/in/rolle
https://twitter.com/therolle
https://therolle.com
• Cybercom has been helping customers to select IoT
platforms suitable for their needs and business
• Sometimes the end result has been AWS and
sometimes not – our role is to be impartial, but offer
guidance
• We have internal white paper about the topic – this
presentation is an overview of it’s contents
Background
3
IoT platform is not strictly defined term.
Some define it as full end-to-end solution offering
everything in the solution, but more commonly it
offers the key components and maybe framework to
build rest of the features.
Definition of IoT Platform
4
• Devices and sensors – the hardware where data originates.
• Gateways – devices to make first data crunching and to open
connection to IoT central system
• Connectivity – the data connection between gateway and
central system
• IoT endpoint – the entry points for central system.
• Real time analytics and triggers
• Offline analytics (Big Data)
• Application and user interface
Common functions of IoT solution
5
Anatomy of an IoT solution
6
• Security
• Solution development cost and time to market
• Maintenance, licensing and infrastructure cost
• Availability and quality factors
• Continuity
• Involved risks and commitment
Platform Selection Criteria
7
• Same paradigm as with cloud-agnostic approach in IaaS world
• Run it yourself?
– You will be solely responsible for: maintenance, security, scalability, ….
– Probably more expensive to develop and run
– But also gives ”complete” freedom – at least theoretically
• Use hyper-cloud IoT?
– Focus on the actual implementation
– Faster time to market, probably cheaper development cost
– What about security? No source code for services?
• Not necessarily absolute right or wrong answer
“To Buy” or “To Build”
8
IoT solution production costs mainly consist of following
factors. Platform selections has impact on these values so they
should be understood.
• Software development
• Platform operations and maintenance
• Platform and infrastructure costs
• Licences
• Hardware and gateway development costs
• Gateway monitoring and maintenance
Cost Structures
9
10
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8
Example cloud based scenario
Software development backend Operations and maintenance
Platform and infrastructure costs Licenses
Hardware and gateway development costs gateway monitoring and maintenance
Platform options (non-exhaustive)
11
• THE END-TO-END SOFTWARE SOLUTION
• FASTEST TO DEVELOP SIMPLE IOT APPLICATIONS
• OFFERS ADDITIONAL LICENSED SOFTWARE OPTIONS ANALYTICS
• CLOSED SYSTEM WITH NO SIMPLE WAY OF EXPANSION OR MIGRATION
• PLATFORM AS A SERVICE
• STRONG FOCUS ON COGNITIVE CLOUD AND ANALYTIS
• NEWCOMER WITH FRESH IDEAS AND RESOURCES TO DELIVER
• GOOD DEVOPS TOOLS AND TEMPLATES MAKE STARTING DEVELOMENT FAST
• AVAILABLE ON-PREMISE OPTION
• INFRASTRUCTURE AS A SERVICE WITH SOME PLATFORM AS A SERVICE OFFERINGS
• THE IAAS MARKET LEADER AND BIGGEST CLOUD PLATFORM
• MASSIVE SCALE ALLOWS USUALLY LOWEST COSTS WITH GOOD SERVICE LEVELS
• CONVENTIONAL DEVELOPMENT METHODS, BUILD WITH SMALL BLOCKS
• CAN BE EXPENSIVE TO MANGE EFFICIENTLY
• STRONG BRAND NAME AND ECOSYSTEM BY MICROSOFT
• PAAS AND IAAS OFFERING
• STRONGEST COMPETITION FOR AWS
• CLOSED SYSTEM TECHNICALLY
DIY Open Source • COMPLETE FREEDOM
• COMPLETE RESPONSIBLITY
Trends and market shares
12
█ AWS
█ Azure
█ IBM
█ ThingWorks
Just basic google trending…
• Some in absolute scale
– Measurable attributes (market share, trends)
• Some attributes in relative scale
– Average, good, very good, best…
• Some subjective attributes as well
– ”Risk”, ”great if done right”
• Mostly to put solutions in relative order per scoring category
• End result is in any case business case related – not the
absolute truth
Scoring the Platforms
13
• Matching to organizational competence – not just purely what
would be ”absolutely best”
– Ability to execute
– Technological competence in place
• Commercial software stacks can be inflexible, if
implementations have more exotic requirements
• Vendor lock can occur in different forms
– Do informed decisions. Technical commitment is also a lock-in.
• Build MVP first fast and build final later?
– You know what they say about temporary solutions…
Considerations
14
All the big public cloud players are valid options for IoT.
It is about finding balance between current and near future
requirements. Direct comparison is very difficult as all
platforms try to differentiate in features and pricing.
Good enterprise architecture is at least as important as good
platform selection. Good architecture can provide almost all
the benefits of single licensed end-to-end platform with more
flexibility, options and without committing fully to single
provider.
Summary
15
16

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AWS Finland March meetup 2017 - selecting enterprise IoT platform

  • 1. AWS Finland March meetup – hosted by Cybercom Selecting Enterprise IoT Platform 1
  • 2. About the Presenter Rolf Koski Chief Technologist Managed Cloud Services rolf.koski@cybercom.com https://fi.linkedin.com/in/rolle https://twitter.com/therolle https://therolle.com
  • 3. • Cybercom has been helping customers to select IoT platforms suitable for their needs and business • Sometimes the end result has been AWS and sometimes not – our role is to be impartial, but offer guidance • We have internal white paper about the topic – this presentation is an overview of it’s contents Background 3
  • 4. IoT platform is not strictly defined term. Some define it as full end-to-end solution offering everything in the solution, but more commonly it offers the key components and maybe framework to build rest of the features. Definition of IoT Platform 4
  • 5. • Devices and sensors – the hardware where data originates. • Gateways – devices to make first data crunching and to open connection to IoT central system • Connectivity – the data connection between gateway and central system • IoT endpoint – the entry points for central system. • Real time analytics and triggers • Offline analytics (Big Data) • Application and user interface Common functions of IoT solution 5
  • 6. Anatomy of an IoT solution 6
  • 7. • Security • Solution development cost and time to market • Maintenance, licensing and infrastructure cost • Availability and quality factors • Continuity • Involved risks and commitment Platform Selection Criteria 7
  • 8. • Same paradigm as with cloud-agnostic approach in IaaS world • Run it yourself? – You will be solely responsible for: maintenance, security, scalability, …. – Probably more expensive to develop and run – But also gives ”complete” freedom – at least theoretically • Use hyper-cloud IoT? – Focus on the actual implementation – Faster time to market, probably cheaper development cost – What about security? No source code for services? • Not necessarily absolute right or wrong answer “To Buy” or “To Build” 8
  • 9. IoT solution production costs mainly consist of following factors. Platform selections has impact on these values so they should be understood. • Software development • Platform operations and maintenance • Platform and infrastructure costs • Licences • Hardware and gateway development costs • Gateway monitoring and maintenance Cost Structures 9
  • 10. 10 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Example cloud based scenario Software development backend Operations and maintenance Platform and infrastructure costs Licenses Hardware and gateway development costs gateway monitoring and maintenance
  • 11. Platform options (non-exhaustive) 11 • THE END-TO-END SOFTWARE SOLUTION • FASTEST TO DEVELOP SIMPLE IOT APPLICATIONS • OFFERS ADDITIONAL LICENSED SOFTWARE OPTIONS ANALYTICS • CLOSED SYSTEM WITH NO SIMPLE WAY OF EXPANSION OR MIGRATION • PLATFORM AS A SERVICE • STRONG FOCUS ON COGNITIVE CLOUD AND ANALYTIS • NEWCOMER WITH FRESH IDEAS AND RESOURCES TO DELIVER • GOOD DEVOPS TOOLS AND TEMPLATES MAKE STARTING DEVELOMENT FAST • AVAILABLE ON-PREMISE OPTION • INFRASTRUCTURE AS A SERVICE WITH SOME PLATFORM AS A SERVICE OFFERINGS • THE IAAS MARKET LEADER AND BIGGEST CLOUD PLATFORM • MASSIVE SCALE ALLOWS USUALLY LOWEST COSTS WITH GOOD SERVICE LEVELS • CONVENTIONAL DEVELOPMENT METHODS, BUILD WITH SMALL BLOCKS • CAN BE EXPENSIVE TO MANGE EFFICIENTLY • STRONG BRAND NAME AND ECOSYSTEM BY MICROSOFT • PAAS AND IAAS OFFERING • STRONGEST COMPETITION FOR AWS • CLOSED SYSTEM TECHNICALLY DIY Open Source • COMPLETE FREEDOM • COMPLETE RESPONSIBLITY
  • 12. Trends and market shares 12 █ AWS █ Azure █ IBM █ ThingWorks Just basic google trending…
  • 13. • Some in absolute scale – Measurable attributes (market share, trends) • Some attributes in relative scale – Average, good, very good, best… • Some subjective attributes as well – ”Risk”, ”great if done right” • Mostly to put solutions in relative order per scoring category • End result is in any case business case related – not the absolute truth Scoring the Platforms 13
  • 14. • Matching to organizational competence – not just purely what would be ”absolutely best” – Ability to execute – Technological competence in place • Commercial software stacks can be inflexible, if implementations have more exotic requirements • Vendor lock can occur in different forms – Do informed decisions. Technical commitment is also a lock-in. • Build MVP first fast and build final later? – You know what they say about temporary solutions… Considerations 14
  • 15. All the big public cloud players are valid options for IoT. It is about finding balance between current and near future requirements. Direct comparison is very difficult as all platforms try to differentiate in features and pricing. Good enterprise architecture is at least as important as good platform selection. Good architecture can provide almost all the benefits of single licensed end-to-end platform with more flexibility, options and without committing fully to single provider. Summary 15
  • 16. 16

Editor's Notes

  1. Devices and sensors – the hardware where data originates. Gateways – devices to make first data crunching and to open connection to IoT central system Data filtering and packaging sensor normalizing and calibration data connection finding endpoint authentication encryption connectivity – the data connection between gateway and central system data connection, usually 3G or Ethernet data protocol, commonly MQTT IoT endpoint – the entry points for central system. device register authentication and encryption Real time analytics and triggers create simple thresholds and business logic triggers further functions as saving to database offline analytics (Big Data) Make reports and insights from history data supports visualizing the data Application and user interface the end user application communicating the finding, visualizing data and giving tools for end user interaction with devices.