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Ingesting clicks data for analytics
Francesco Furiani, CTO @
$ whoami
Francesco Furiani (@ilfurio):
 Backend Engineer
 Roamed these halls not too long ago
Ingesting clicks data for analytics
Loves:
 Studying new CS stuff
 PlayStation / Bike / Traveling / Soccer
 O RLY? books
How do i make a living:
 CTO @ ClickMeter
 Backend Engineer @ ClickMeter
 Enum.take_random(IT_ROLES,1) @ ClickMeter
Ingesting clicks data for analytics
ClickMeter
 100k+ customers
 Getting events for customers from 10 to 3000 req/sec
Ingesting clicks data for analytics
ClickMeter
We receive data anytime someone:
 Clicks our links
 Views our pixels
 Calls our postbacks
Our customers use us:
 Inside a famous app the day of the big release ✔
 Advertising on an extremely big video portal ✔
 A tiny travel blog ✔
 A physical device for advertising ✔
Ingesting clicks data for analytics
Getting the data
We need to:
 Try not lose the events we receive (duh)
 Show to customers data for better insight on their campaigns
 Scale up/down according to the incoming fluxes
 Improve the product by using the data we get
 Do it as fast as possible (wasn’t this ready a week ago?)
 Do it as cheap as possible
Ingesting clicks data for analytics
The challenge
Find the size of the problem you’re trying to solve
 How much data do you expect? Rate?
 What do you have to do with it?
 Do I have to do something with ALL of it?
 How fast do I have to do it?
Answers to these questions are a starting point.
Ingesting clicks data for analytics
Size
Once we know how big and bad the beast is, we
need to design the ranch that will keep it in check.
Iterative process and prone to a lot of failures, but
the world is out there to help us.
Think, write and draw a lot.
Ingesting clicks data for analytics
Design
… drawn too much ...
Ingesting clicks data for analytics
Design
Most of us will never have the joy (and the horror) of
creating a new stack novel in theory and practice.
Still we need to understand the theory behind every
brick.
Read the info, read the opinions, try little proof of
concepts of the moving parts, it helps a lot!
Ingesting clicks data for analytics
Which bricks should I use
A very important brick.
Elasticity of computation power, many *aaS, managed solutions are
really a great help in terms of saved manpower and fast iterations.
It comes at a great cost to consider:
• $$$ (ymmv)
• Possible lock-ins
Ingesting clicks data for analytics
The cloud is a brick too
… well it’s never definitive ...
Ingesting clicks data for analytics
Design with bricks
Obviously we haven’t followed those guidelines.
One becomes savvy after crashing and burning
many times.
But still thanks to those errors we got there and
built, at every iteration, a better infrastructure.
Ingesting clicks data for analytics
How we did it
ClickMeter was already live and growing
It needed an overhaul in its infrastructure/backend.
The growth fueled the need to be ready for more power to handle more data.
Obviously this had to be a tablecloth trick migration 
Ingesting clicks data for analytics
How we did it
Already on the cloud (AWS), we thought of having an hybrid approach but it
didn’t make sense.
Review of old components already in production to see what to kill, keep or
update.
Kept good stuff and designed some new layers to make them work flawlessly in
the new infrastructure.
Ingesting clicks data for analytics
How we did it
Ingesting clicks data for analytics
Pretty important, they need to:
• Stay up
• Scale up/down depending on the income traffic
• Never lose anything
• Be as fast as possible in processing
They’re a custom web app application that undergoes a lot of testing.
We used stuff like Beanstalk, Scaling groups, Load Balancers and Health routing
offered by our cloud provider to manage the webapp scaling/availability
Ingesting clicks data for analytics
Redirect engine
aka events collector
Pipeline
Most of this part uses our cloud provider
technology.
This simplify maintenance and provisioning,
keeping the focus on the value of our product.
Some moving parts are custom made by us to
interact with the cloud technology (might be
proprietary or just repackaged known one).
Ingesting clicks data for analytics
Tracking engine
and friends
SQS Pipeline
Kinesis
• Events • Preprocessing
• Postprocessing
• DynamoDB
Ingesting clicks data for analytics
Tracking engine
and friends
Combination of real-time and batch
technologies.
One of the scaling parts that actually provides
value to the customers.
Computes analysis on events data from a
simple count to some predictions.
Check the data produced by your processing
system to improve step by step the pipeline!
Ingesting clicks data for analytics
Pipeline
Ingesting clicks data for analytics
Pipeline
We employ different storage based on speed of delivery and data type.
All the data is accessible via a REST API.
This permits to develop a frontend layer with pretty much ease and allows
customers to take control of the data and use them in way we might haven’t
thought.
Ingesting clicks data for analytics
Storage and data delivery
Managed services on the cloud help us a lot!
Most of the team can focus on improvements
and shipping (users are happy, so is the CEO).
Some of us (me) still have to be the
CloudOp/DevOp.
p.s.: prepare always a plan b for when you’ll
break things!
Ingesting clicks data for analytics
Operations
Cloud is typically more expensive of your own metal.
This extra money you’ve to spend is anyway well spent:
• Flexibility
• Easier provisioning
• Easier management
• Easier operations
There are different types of clouds choose wisely.
Ingesting clicks data for analytics
Cloud co$t$
Creating and managing a “big data” ready infrastructure is no easy task,
but it can be done step by step also by startups.
The cloud is a cool starting ground providing you with many of the toys
you need, so you can focus on what part of “big data” gives you value!
Use the wisdom shared by the big/medium players that already have
been there(and built most of the stuff you’re using).
Ingesting clicks data for analytics
Conclusions
Thank You
Any questions?
@il_furio
francesco@clickmeter.com

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Ingesting click events for analytics

  • 1. Ingesting clicks data for analytics Francesco Furiani, CTO @
  • 2. $ whoami Francesco Furiani (@ilfurio):  Backend Engineer  Roamed these halls not too long ago Ingesting clicks data for analytics Loves:  Studying new CS stuff  PlayStation / Bike / Traveling / Soccer  O RLY? books How do i make a living:  CTO @ ClickMeter  Backend Engineer @ ClickMeter  Enum.take_random(IT_ROLES,1) @ ClickMeter
  • 3. Ingesting clicks data for analytics ClickMeter
  • 4.  100k+ customers  Getting events for customers from 10 to 3000 req/sec Ingesting clicks data for analytics ClickMeter
  • 5. We receive data anytime someone:  Clicks our links  Views our pixels  Calls our postbacks Our customers use us:  Inside a famous app the day of the big release ✔  Advertising on an extremely big video portal ✔  A tiny travel blog ✔  A physical device for advertising ✔ Ingesting clicks data for analytics Getting the data
  • 6. We need to:  Try not lose the events we receive (duh)  Show to customers data for better insight on their campaigns  Scale up/down according to the incoming fluxes  Improve the product by using the data we get  Do it as fast as possible (wasn’t this ready a week ago?)  Do it as cheap as possible Ingesting clicks data for analytics The challenge
  • 7. Find the size of the problem you’re trying to solve  How much data do you expect? Rate?  What do you have to do with it?  Do I have to do something with ALL of it?  How fast do I have to do it? Answers to these questions are a starting point. Ingesting clicks data for analytics Size
  • 8. Once we know how big and bad the beast is, we need to design the ranch that will keep it in check. Iterative process and prone to a lot of failures, but the world is out there to help us. Think, write and draw a lot. Ingesting clicks data for analytics Design
  • 9. … drawn too much ... Ingesting clicks data for analytics Design
  • 10. Most of us will never have the joy (and the horror) of creating a new stack novel in theory and practice. Still we need to understand the theory behind every brick. Read the info, read the opinions, try little proof of concepts of the moving parts, it helps a lot! Ingesting clicks data for analytics Which bricks should I use
  • 11. A very important brick. Elasticity of computation power, many *aaS, managed solutions are really a great help in terms of saved manpower and fast iterations. It comes at a great cost to consider: • $$$ (ymmv) • Possible lock-ins Ingesting clicks data for analytics The cloud is a brick too
  • 12. … well it’s never definitive ... Ingesting clicks data for analytics Design with bricks
  • 13. Obviously we haven’t followed those guidelines. One becomes savvy after crashing and burning many times. But still thanks to those errors we got there and built, at every iteration, a better infrastructure. Ingesting clicks data for analytics How we did it
  • 14. ClickMeter was already live and growing It needed an overhaul in its infrastructure/backend. The growth fueled the need to be ready for more power to handle more data. Obviously this had to be a tablecloth trick migration  Ingesting clicks data for analytics How we did it
  • 15. Already on the cloud (AWS), we thought of having an hybrid approach but it didn’t make sense. Review of old components already in production to see what to kill, keep or update. Kept good stuff and designed some new layers to make them work flawlessly in the new infrastructure. Ingesting clicks data for analytics How we did it
  • 16. Ingesting clicks data for analytics
  • 17. Pretty important, they need to: • Stay up • Scale up/down depending on the income traffic • Never lose anything • Be as fast as possible in processing They’re a custom web app application that undergoes a lot of testing. We used stuff like Beanstalk, Scaling groups, Load Balancers and Health routing offered by our cloud provider to manage the webapp scaling/availability Ingesting clicks data for analytics Redirect engine aka events collector
  • 18. Pipeline Most of this part uses our cloud provider technology. This simplify maintenance and provisioning, keeping the focus on the value of our product. Some moving parts are custom made by us to interact with the cloud technology (might be proprietary or just repackaged known one). Ingesting clicks data for analytics Tracking engine and friends
  • 19. SQS Pipeline Kinesis • Events • Preprocessing • Postprocessing • DynamoDB Ingesting clicks data for analytics Tracking engine and friends
  • 20. Combination of real-time and batch technologies. One of the scaling parts that actually provides value to the customers. Computes analysis on events data from a simple count to some predictions. Check the data produced by your processing system to improve step by step the pipeline! Ingesting clicks data for analytics Pipeline
  • 21. Ingesting clicks data for analytics Pipeline
  • 22. We employ different storage based on speed of delivery and data type. All the data is accessible via a REST API. This permits to develop a frontend layer with pretty much ease and allows customers to take control of the data and use them in way we might haven’t thought. Ingesting clicks data for analytics Storage and data delivery
  • 23. Managed services on the cloud help us a lot! Most of the team can focus on improvements and shipping (users are happy, so is the CEO). Some of us (me) still have to be the CloudOp/DevOp. p.s.: prepare always a plan b for when you’ll break things! Ingesting clicks data for analytics Operations
  • 24. Cloud is typically more expensive of your own metal. This extra money you’ve to spend is anyway well spent: • Flexibility • Easier provisioning • Easier management • Easier operations There are different types of clouds choose wisely. Ingesting clicks data for analytics Cloud co$t$
  • 25. Creating and managing a “big data” ready infrastructure is no easy task, but it can be done step by step also by startups. The cloud is a cool starting ground providing you with many of the toys you need, so you can focus on what part of “big data” gives you value! Use the wisdom shared by the big/medium players that already have been there(and built most of the stuff you’re using). Ingesting clicks data for analytics Conclusions