SlideShare a Scribd company logo
Video Experience Operational
Insights in Real Time.
Aditya Vaidya - Sr Software Engineer
2
3
VDMS powers Oath Brands
4
VDMS enables partner experiences
Uplynk : 400 channels 35,000 live events | Edgecast: 45 Tbps total capacity
5
Devices
Global Scale Live Event
6
7
Video Player Event Lifecycle
8
Video Operational Insights Platform - 2015 v/s 2017
9
Redis
● In-memory db - High throughput & Low latencies
● Advanced data structures - SortedSet, HyperLogLog (probabilistic)
Operational Insights - Quality of Experience (QoE)
10
● Rebuffer Ratio - % of viewers time spent watching stalled playback
○ Metrics
● Rebuffering duration
● Playback duration
○ Dimensions
● Content Delivery Networks (Multi CDN environment)
Operational Insights - Audience Engagement
11
● Concurrent Views - Number of unique Concurrent Video Sessions
○ Metrics
● Unique Video Sessions
○ Dimensions
● Brands (Oath or Partner) e.g. yahoo sports, aol etc
● Devices e.g. Mobile, Desktop etc
12
● As close as possible to Real Time
● Near Real Time aggregations over millions of events
Near Real Time Challenges
13
Real Time Window
14
Dimensions & Metrics
15
Architecture
1616
Partitioning
● Local Redis Cluster
○ video_session_id
● Global Redis Cluster
○ key -> DIMS:MEASURE
17
HyperLogLog - Unique Counting
● Approximate data sketch
● Count upto 2^64 with std. error of .81% in 12KB
18
Metrics - Concurrent Views
● Local Redis
○ PFADD key video_session_id (streaming)
○ DUMP key (once per interval)
● Remote Redis Cluster
○ RESTORE (once per interval)
○ PFMERGE keys_from_all_servers (once per interval)
19
Metrics - Concurrent Views
20
Metrics - Rebuff, Starts, Bitrate etc
● Local Redis
○ INCRBY key (streaming)
○ GET key (once per key per interval)
● Remote Redis Cluster
○ INCRBY key (once per interval)
○ GET key (once per interval)
21
Master Redis Redundancy
22
Cluster Redundancy
23
Before & After
24
Real Time Dashboard
25
Results
● End-to-end latency < 20 secs
● Multi CDN failure detection during a global scale live event
Thank You

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