Presented by Tom Maule, Software Solutions Architect, NowTV Experience level: Advanced NOW TV’s customer base has tripled year on year, and linear event streaming has become a greater and greater percentage of their viewing. This talk will take you through the lessons we learnt following one unfortunate event in 2014 which led NOW TV to catastrophic failure, and the improvements and scalability challenges we were faced with when preparing for the same event just 1 year later. Hear how we turned our entire failure case behaviour on its head; from always failing in favour of NOW TV, to failing in favour of the customer. Learn how we ensure that high availability of video assets on the CDN ensures continued playout irrespective of the state of our application servers. Take away some tips of how NOT to scale, as well as how we reversed our fortunes and delivered stability during the biggest event on NOW TV to date.

1. NOW TV and Linear Streaming:
Scaling MongoDB for High Load Events
Tom Maule – NOW TV Solution Architect

2. 2
• Tom Maule
– Solution Architect at NOW TV, Sky
– Previously Senior Java Developer on NOW TV Platform team (since project inception in early 2012)
I have also previously worked in the defence and telecoms industries
tom.maule@sky.uk
linkedin.com/in/tommaule
@tommaule
Who am I?

3. 3
Abstract
• NOW TV Introduction
• Linear streaming challenges
• 7th April 2014
• Fixes and improvements
• 13th April 2015
• Future work and next steps

4. 4
Introduction - Overview
• NOW TV is the online no-contract TV streaming service from Sky
• Available on over 60 devices including the award-winning NOW TV Box
• NOW TV offers movies and entertainment VOD and linear content, and for the first time in the UK,
pay-as-you-go Sports linear content

5. 5
Introduction - Customer Base
• Our customer base TRIPLED in the year up to April 2014
2013 2014

6. 6
Introduction – Streaming Features
VOD Streaming
VOD DRM
Linear Streaming
Linear DRM
Concurrency Limits

7. 7
Introduction - NOW TV Architecture
CDN
Content
MongoDB:
Content Metadata
MongoDB:
Account Data
VOD
Transcoding
Linear
Transcoding
CDN
Manifest and
video chunks
Live video stream
Stream
upload
Asset
upload
Content metadata,
User services
User
device
Video
Assets
NOW TV Platform
Load Balancer Load Balancer
Services
Logs
Splunk
Cloud
Manager
Icinga
Monitoring
& alerting:
New
Relic

8. 8
Video On Demand (VOD)
• Video content, available on demand, whenever users want it.
• Platform load is predictable, just ask any of Netflix, Amazon Instant Video, YouTube, etc

9. 9
Video On Demand (VOD)
• Even weekend load, though busier during the day, remains predictable

10. 10
Linear Streaming
• Unlike other OTT (Over-the-Top) Providers, NOW TV offers streaming of live channels
• This is typically NOT predictable
• Load is driven by live events, not by time of day
Linear VOD

11. 11
NOW TV and Linear Streaming: The unpredictable scalability challenge
Tom Maule – NOW TV Solution Architect

12. 12

13. 13
Commemorative Merchandise

14. 14

15. 15
Why did we not see this coming?

16. 16
What happened?
• High load stressed our MongoDB instance
• Retries only compounded the problem
• Observed issues:
– Customers couldn’t start new streams
– Existing streams were terminated
– Concurrency errors during and shortly after the outage
– Very high read and write queues in MongoDB
– Viewing History APIs performed very slowly
– High proportion of time was spent updating indexes in MongoDB

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Issues to Address
• Heartbeating resiliency
• Concurrency inaccuracies
• Products storage
• Viewing History
• Indexes in MongoDB
• MongoDB write lock
H
C
P
V
I
M
H C P V I M

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Heartbeating: Introduction
• After playout initiation, actual video chunks are served by CDN, and don't touch our platform
• Lightweight heartbeats call back to our platform to notify us of continued playout every 10 mins
• NOW TV use heartbeats to:
– Enforce concurrency rules
– Enforce entitlement
– Record bookmark positions (VOD only)
CDN
NOW TV
Video chunks
Heartbeats
(10 min interval)
H C P V I M

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Heartbeating: Previously
• Previously, a non-OK heartbeat response would terminate playout on the user’s device
• Fail in favour of NOW TV
– When NOW TV platform is unavailable, existing playouts are terminated on next heartbeat.
CDN
NOW TV
Video chunks
Heartbeat
non-OK response
P V I M
H C

20. 20
Heartbeating: Today
• Today, playout continues unless a specific STOP heartbeat response is received
• Fail in favour of the customer
– Existing streams will NOT be terminated if NOW TV becomes unavailable
CDN
NOW TV
Video chunks
Heartbeat
non-STOP response
P V I M
H C

21. 21
Heartbeating: Future
• Game of Thrones Linear customers produce ripple-effect heartbeating
– Due to heartbeats fixed to a 10 minute period
• In future, we will randomise the first heartbeat period in attempt to smooth out these ripples
P V I M
H C

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{
“playouts”: []
}
Concurrency: Introduction
• Concurrency of 2 streams is managed through the concept of Playout Slots
• A playout slot keeps track of a currently playing stream
• Slots are allocated on playout initiation
{
“playouts”: [
{
“id” : “ABC123”,
“heartbeat”: “<timestamp>”,
“content”: “<content_id>”
}
]
}
{
“playouts”: [
{
“id” : “ABC123”,
“heartbeat”: “<timestamp>”,
“content”: “<content_id>”
},
{
“id” : “DEF456”,
“heartbeat”: “<timestamp>”,
“content”: “<content_id>”
}
]
}
NOW TV
MongoDB
Play
Play
Play
C P V I MH

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{
“playouts”: [
{
“id” : “ABC123”,
“heartbeat”: “<timestamp>”,
“content”: “<content_id>”
},
{
“id” : “DEF456”,
“heartbeat”: “<timestamp>”,
“content”: “<content_id>”
}
]
}
Concurrency: Introduction
• Slots are updated on heartbeats to refresh the time stamp
• Expired slots are re-allocated on next playout request
• Slots are terminated on an END event
{
“playouts”: [
{
“id” : “DEF456”,
“heartbeat”: “<timestamp>”,
“content”: “<content_id>”
}
]
}
NOW TV
MongoDB
END
Play
{
“playouts”: [
{
“id” : “DEF456”,
“heartbeat”: “<timestamp>”,
“content”: “<content_id>”
},
{
“id” : “CBF789”,
“heartbeat”: “<timestamp>”,
“content”: “<content_id>”
}
]
}
P V I M
CH

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{
“playouts”: [
{
“id” : “ABC123”,
“heartbeat”: “<timestamp>”,
“content”: “<content_id>”
},
{
“id” : “DEF456”,
“heartbeat”: “<timestamp>”,
“content”: “<content_id>”
}
]
}
Concurrency: Previously
• Failure to receive an END event (due to app crash or connectivity loss), blocked a slot until timeout
• Previously, this blocked subsequent playouts for up to 10 minutes
• “Concurrency limit reached” errors were seen after our service had been restored on GoT night
NOW TV
MongoDB
Play
P V I M
CH

25. 25
{
“playouts”: [
{
“id” : “ABC123”,
“heartbeat”: “<timestamp>”,
“content”: “<content_id>”,
“deviceId” : “box1”
},
{
“id” : “DEF456”,
“heartbeat”: “<timestamp>”,
“content”: “<content_id>” ,
“deviceId” : “box2”
}
]
}
Concurrency: Today
• Now, slots allocated to the same Device ID can be ‘reclaimed’
• No more “Concurrency limit reached” errors following app crashes or service outages
NOW TV
MongoDB
Play
{
“playouts”: [
{
“id” : “FCE987”,
“heartbeat”: “<timestamp>”,
“content”: “<content_id>”,
“deviceId” : “box1”
},
{
“id” : “DEF456”,
“heartbeat”: “<timestamp>”,
“content”: “<content_id>” ,
“deviceId” : “box2”
}
]
}
box
1
box
2
P V I M
CH

26. 26
Product Storage: Previously
• Every purchase and renewal of any product resulted in a new Product entity in MongoDB
Entertainment – June 2015
Movies – August 2015
Sports – 20th July 2015
Entertainment – July 2015
Entertainment – August 2015
Movies – September 2015
Entertainment – September 2015
Sports – 12th September 2015
Movies – October 2015
Entertainment – October 2015
Entertainment – November 2015
P
V I MH C
From June 2015
20th July 2015
From Aug 2015
12th Sept 2015

27. 27
Product Storage: Today
• We store Entitlement entities instead of products, updating on renewals rather than duplicating
Entertainment – June 2015
Movies – August 2015
Sports – 20th July 2015
Entertainment – July 2015Entertainment – August 2015
Movies – September 2015
Entertainment – September 2015
Sports – 12th September 2015
Movies – October 2015
Entertainment – October 2015
Movies – November 2015
Entertainment – November 2015
P
V I M
From June 2015
20th July 2015
From Aug 2015
12th Sept 2015
H C

28. 28
Viewings & Bookmarks: Introduction
• Viewing a VOD asset => Viewing
• Heartbeating during a VOD asset => Bookmark
• Viewings and Bookmarks were stored separately
• No capping or archiving
V
I MPH C

29. 29
Viewings & Bookmarks: Previously
• Upon fetching a customer’s viewing history, multiple database queries were made:
- 1 query to the viewings collection to fetch n viewings for the customer
- n queries to the bookmarks collection to fetch the bookmark position for each viewing
- TOTAL: n + 1 MongoDB queries for a single request!
- Some customers had thousands of items in their viewing history!
{
“_id”: “abc123”,
“accountId”: “account1”,
“contentId”: “movie1”,
“timestamp”: “<timestamp>”
}
{
“_id”: “bcd345”,
“accountId”: “account1”,
“contentId”: “movie2”,
“timestamp”: “<timestamp>”
}
{
“_id”: “cde456”,
“accountId”: “account1”,
“contentId”: “episode1”,
“timestamp”: “<timestamp>”
}
Viewings
{
“_id”: “fed987”,
“accountId”: “account1”,
“contentId”: “movie1”,
“position”: 1187
}
{
“_id”: “edc765”,
“accountId”: “account1”,
“contentId”: “movie2”,
“position”: 2854
}
{
“_id”: “dcb543”,
“accountId”: “account1”,
“contentId”: “episode1”,
“position”: 3542
}
Bookmarks
}
V
I MPH C

30. 30
Viewings & Bookmarks: Today
• The original reason for keeping viewings and bookmarks separate was no longer apparent
• Now, viewings and bookmarks are merged
– Unnecessary document ID replaced with compound ID – improving indexing efficiency
– Shortened field names - reducing storage consumption and further improving indexing efficiency
{
“_id”: “abc123”,
“accountId”: “account1”,
“contentId”: “movie1”,
“timestamp”: “<timestamp>”
}
Viewing
{
“_id”: “fed987”,
“accountId”: “account1”,
“contentId”: “movie1”,
“position”: 1187
}
Bookmark
{
“_id”: {
“accountId”: “account1”,
“contentId”: “movie1”
},
“position”: 1187,
“timestamp”: “<timestamp>”
}
View History
{
“_id”: {
“aid”: “account1”,
“cid”: “movie1”
},
“pos”: 1187,
“ts”: “<timestamp>”
}
V
I MPH C

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MongoDB Indexes
{
“_id”: “abc123”,
“accountId”: “account1”,
“contentId”: “movie1”,
“timestamp”: “<timestamp>”
}
{
“_id”: “abc123”,
“accountId”: “account1”
}
{
“_id”: “abc123”,
“accountId”: “account1”,
“timestamp”: “<timestamp>”
}
{
“_id”: “abc123”,
“accountId”: “account1”,
“contentId”: “movie1”
}
{
“_id”: “fed987”,
“accountId”: “account1”,
“contentId”: “movie1”,
“position”: 1187
}
{
“_id”: “fed987”,
“accountId”: “account1”,
“contentId”: “movie1”
}
{
“_id”: {
“aid”: “account1”,
“cid”: “movie1”
},
“pos”: 1187,
“ts”: “<timestamp>”
}
{
“_id.aid”: “account1”,
“ts”: “<timestamp>”
}
{
“_id”: “abc123”
}
{
“_id”: “fed987”
}
{
“_id”: {
“aid”: “account1”,
“cid”: “movie1”
}
}
Viewing Bookmark View History
I
MP VH C

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MongoDB Instance
Database 1
Collection 1
MongoDB Write Locks: Previously
Document
Collection 2
Document
Document
Document
Document
Document
Document
Document
Database 2
Collection 3
Document
Document
Collection 4
Document
Document
Document
Document
M
P V IH C

33. 33
MongoDB Instance
Database 4Database 2Database 1
MongoDB Write Locks: Today
Collection 2
Document
Document
Document
Collection 1
Document
Document
Document
Document
Document
Database 3
Collection 3
Document
Document
Collection 4
Document
Document
Document
Document
M
P V IH C

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Performance Testing
Game of Thrones 2014 Load Capacity Tests March 2015

35. 35
NOW TV Customer Base 2014 - 2015
• Our customer base TRIPLED, again, in the year up to April 2015
2013 2014 2015

36. 36
NOW TV and Linear Streaming: The unpredictable scalability challenge
Tom Maule – NOW TV Solution Architect

37. 37
What happened?
• Good platform availability throughout
• 2.5x the load that affected us just one year earlier
• Twice the normal concurrency for a typical Monday night

38. 38
What did our customers say?

39. 39
Recognition
MongoDB Innovation Award 2015
recognises organisations that are
creating ground-breaking applications.
These projects represent the best and
most innovative work in the industry
over the last year.
DTG Innovation Award 2015
recognises organisations which
have driven innovation in a
particular technology or sector

40. 40
What’s Next For NOW TV?
• Our growth is expected to continue along the same trajectory
• Moving to active-active datacentre architecture for increased resiliency
• Cloud-based ‘overflow’ scaling for high-load events
• Microservices
• Sub-system resiliency

41. 41
Credits
• The entire NOW TV Technology team
are credited with our success
– Platform Software Engineers
– Platform Quality Assurance Engineers
– Dev-Ops Engineers
– App Developers & Testers
– Analysts, scrum masters and management
• MongoDB Consultants and Technical
Services Engineers
• Be a part of our future success, work for NOW TV at Sky
– Sky’s Social Job Site (http://rfer.us/BSKEti5rp)
– @workforsky

42. Thank you. Any questions?
@tommaule
tom.maule@sky.uk

43. The End
@tommaule
tom.maule@sky.uk