Keystone - Leverage Big Data 2016

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Peter Bakas

The Netflix Way To Deal With Real-Time Data

Technology

What should I expect
Keystone Season 1 - Who, What, How and Why
Keystone Season 2 - Preview Trailer

hello!
I am Peter Bakas
I lead the Real-Time Data Infrastructure team @ Netflix
You can find me at @peter_bakas

1,000,000,000,000
Whoa! That’s a big number.
Events Processed Every Day

Daily Averages
700B unique events ingested
1T events processed
1.4 PB
By the numbers
Peak
1T unique events ingested/day
12.5M/sec
35 GB/sec

Trending on Netflix
80B/day
1/2014
300B/day
1/2015
1T/day
1/2016

Q4 2015 - Keystone
Internal
Routing
Service
EMR
Fronting
Kafka
Event
Producer
Consumer
Kafka
Control Plane
HTTP
PROXY
Stream
Consumers

Keystone Kafka Footprint
Fronting
Kafka
Consumer Kafka
Number of Clusters 24 8
Number of Instances 3000+ 900+
Retention Period 8 to 24 hrs 2 to 4 hrs

Keystone Internal Routing Service
+
Checkpointing
Cluster
+

Keystone Internal Routing Service Footprint
S3 ElasticSearch
Consumer
Kafka
Number of
containers
7000 1500 4500

Keystone avg end-to-end metrics
S3 ElasticSearch
Consumer
Kafka
1 sec 13 sec 800 ms

Netflix Culture
Freedom and Responsibility

“It may well be the most
important document to ever
come out of the Valley
Sheryl Sandberg, COO @ Facebook

A true story
Keystone went live 10/27/15
2 days later...

Place your screenshot here
80% “loss” over
6 hour period
A true story

Lessons learned
There are times when things can go wrong… and no turning back
Reduce complexity
Minimize blast radius
Find a way to start over fresh

Failover
Cold standby Kafka cluster with different instance type
Different ZooKeeper cluster with no state
Fully automated

Place your screenshot here
Time is of the essence
Failover as fast as
5 minutes
Fully
Automated
Failover

Best Practices
Full Automation
Self Healing
Kafka Kong

“We didn’t do anything wrong, but
somehow, we lost...
Stephen Elop, Nokia CEO

125,000,000 hrs/day
That’s a lot of hours!
37 %
of North America internet traffic @ peak!
81,000,000 members
and a lot of members

If you don’t change,
you will be eliminated from the
competition

Our philosophy
Create Duplo R
Blocks :
Let reusability drive new value

Evolution
Keystone
Management
Keystone
Messaging
Keystone
Stream
Processing

Keystone
Unified event publishing, collection,
routing for batch and stream
processing
85% of data volume
Keystone Messaging
Ad-hoc Messaging
15% of data volume

Consumers weary of
Complexity of self-managed
infrastructure
Multiple runtimes across different
platforms
Keystone Stream Processing
Consumers want
Simple unified model/API/UI/system

Simple and intuitive interface to
manage all Keystone services
Keystone Management

thanks!
Any questions?
You can find me at
@peter_bakas
pbakas@netflix.com

Credits
Special thanks to all the people who made and released
these awesome resources for free:
Presentation template by SlidesCarnival
Photographs by Unsplash

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Easier, Faster, and More Powerful – Alles Neu macht der Mai -Wir durchleuchte...

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I'm excited to share my latest predictions on how AI, robotics, and other technological advancements will reshape industries in the coming years. The slides explore the exponential growth of computational power, the future of AI and robotics, and their profound impact on various sectors. Why this matters: The success of new products and investments hinges on precise timing and foresight into emerging categories. This deck equips founders, VCs, and industry leaders with insights to align future products with upcoming tech developments. These insights enhance the ability to forecast industry trends, improve market timing, and predict competitor actions. Highlights: ▪ Exponential Growth in Compute: How $1000 will soon buy the computational power of a human brain ▪ Scaling of AI Models: The journey towards beyond human-scale models and intelligent edge computing ▪ Transformative Technologies: From advanced robotics and brain interfaces to automated healthcare and beyond ▪ Future of Work: How automation will redefine jobs and economic structures by 2040 With so many predictions presented here, some will inevitably be wrong or mistimed, especially with potential external disruptions. For instance, a conflict in Taiwan could severely impact global semiconductor production, affecting compute costs and related advancements. Nonetheless, these slides are intended to guide intuition on future technological trends.

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Join me in this session where I'll share our journey of building a fully serverless application that flawlessly managed check-ins for an event with a staggering 80 thousand registrations. We'll dive into three key strategies that made this possible. Firstly, by harnessing DynamoDB global tables, we ensured global service availability and data replication across regions, boosting performance and disaster recovery. Next, we'll explore how we seamlessly integrated real-time updates into the app using Appsync subscriptions, making the experience dynamic and engaging for users. Finally, I'll discuss how provisioned concurrency not only improved performance but also kept costs in check, highlighting the cost-effectiveness of serverless architectures. Through these strategies and the inherent scalability of serverless technology, our application effortlessly handled massive user loads without manual intervention. This session is a real world example to the power and efficiency of modern cloud-based solutions in enabling seamless scalability and robust performance with Serverless

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TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...

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Keystone - Leverage Big Data 2016

1. The Netflix way to deal with real-time data How we built a 1t/day stream processing cloud platform in a year

2. What should I expect Keystone Season 1 - Who, What, How and Why Keystone Season 2 - Preview Trailer

3. 1. The Who?

4. hello! I am Peter Bakas I lead the Real-Time Data Infrastructure team @ Netflix You can find me at @peter_bakas

5. 2. The What?

6. Publish + Collect + Process + Move Data

7. 1,000,000,000,000 Whoa! That’s a big number. Events Processed Every Day

8. Daily Averages 700B unique events ingested 1T events processed 1.4 PB By the numbers Peak 1T unique events ingested/day 12.5M/sec 35 GB/sec

10. Growth has its season

11. In the beginning - Chukwa

12. Q4 2014 - Chukwa/Suro

13. Q4 2015 - Keystone Internal Routing Service EMR Fronting Kafka Event Producer Consumer Kafka Control Plane HTTP PROXY Stream Consumers

14. Kafka

15. Q4 2015 - Keystone Internal Routing Service EMR Fronting Kafka Event Producer Consumer Kafka Control Plane HTTP PROXY Stream Consumers

16. Keystone Kafka Footprint Fronting Kafka Consumer Kafka Number of Clusters 24 8 Number of Instances 3000+ 900+ Retention Period 8 to 24 hrs 2 to 4 hrs

17. Q4 2015 - Keystone Internal Routing Service EMR Fronting Kafka Event Producer Consumer Kafka Control Plane HTTP PROXY Stream Consumers

18. Keystone Internal Routing Service + Checkpointing Cluster +

19. Keystone Internal Routing Service

20. Keystone Internal Routing Service Footprint S3 ElasticSearch Consumer Kafka Number of containers 7000 1500 4500

21. Keystone avg end-to-end metrics S3 ElasticSearch Consumer Kafka 1 sec 13 sec 800 ms

22. 3. The How?

23. Netflix Culture Freedom and Responsibility

24. “It may well be the most important document to ever come out of the Valley Sheryl Sandberg, COO @ Facebook

25. What does culture have to do with how?

26. Sounds easy Build Team Build Product

27. A true story Keystone went live 10/27/15 2 days later...

28. Place your screenshot here 80% “loss” over 6 hour period A true story

29. Lessons learned There are times when things can go wrong… and no turning back Reduce complexity Minimize blast radius Find a way to start over fresh

30. Failover Cold standby Kafka cluster with different instance type Different ZooKeeper cluster with no state Fully automated

31. Place your screenshot here Time is of the essence Failover as fast as 5 minutes Fully Automated Failover

32. Best Practices Full Automation Self Healing Kafka Kong

33. 4. The Why?

34. “We didn’t do anything wrong, but somehow, we lost... Stephen Elop, Nokia CEO

35. Global Launch 1/6/16

36. 125,000,000 hrs/day That’s a lot of hours! 37 % of North America internet traffic @ peak! 81,000,000 members and a lot of members

37. If you don’t change, you will be eliminated from the competition

38. 5. Coming Soon

39. Our philosophy Create Duplo R Blocks : Let reusability drive new value

40. Evolution Keystone Management Keystone Messaging Keystone Stream Processing

41. Keystone Unified event publishing, collection, routing for batch and stream processing 85% of data volume Keystone Messaging Ad-hoc Messaging 15% of data volume

42. Consumers weary of Complexity of self-managed infrastructure Multiple runtimes across different platforms Keystone Stream Processing Consumers want Simple unified model/API/UI/system

43. Simple and intuitive interface to manage all Keystone services Keystone Management

44. thanks! Any questions? You can find me at @peter_bakas pbakas@netflix.com

45. Credits Special thanks to all the people who made and released these awesome resources for free: Presentation template by SlidesCarnival Photographs by Unsplash

Keystone - Leverage Big Data 2016

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