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Scaling hotstar.com for 10 million concurrent viewers
The document discusses the challenges and strategies for scaling hotstar.com to handle over 10 million peak concurrent users, particularly during events like the Vivo IPL final. Key statistics include 5.7 Tbps peak bandwidth, 1 million requests per second, and extensive resource allocation with 36,000 CPUs and 72 TB of RAM. The strategies employed involve load generation, chaos engineering, and future plans for machine learning-assisted auto-scaling to optimize performance during high-traffic events.
Scaling hotstar.com for 10 million concurrent viewers
- 1. Scaling Hotstar.com for 10Mnconcurrency CHALLENGES & LEARNINGS Gaurav Kamboj Cloud Architect at Hotstar
- 2. Let’s talk aboutScale! 10Mn+ PEAK CONCURRENCY DURING VIVO IPL FINAL 5.7 Tbps PEAK BANDWIDTH CONSUMPTION 1Mn PEAK REQUESTS PER SECOND 10Bn+ CLICKSTREAM MESSAGES 100+ HOURS OF LIVE TRANSCODING EVERYDAY
- 4. Game Day FACE THEREAL GAME BEFORE THE ACTUAL GAME 36,000 CPUs 80 Gbps NETWORK OUT 72 TB RAM 8 REGIONS GEO DISTRIBUTED Project HULK ● Load Generation ● Performance & Tsunami Tests ● Chaos Engineering ● Traffic Pattern using ML
- 5. Race against time! +500K GROWTH RATE PER MINUTE (CONCURRENCY) FULLY BAKED AMIs 4 mins APPLICATION BOOT-UP TIME 90 SECONDS REACTION TIME PUSH NOTIFICATIONS
- 6. Why we don’tuse autoscaling INSUFFICIENT CAPACITY ERRORS GAME OF (AVAILABILITY) ZONES STEP SIZE AUTOSCALING GROUPS
- 7. Others challenges.. SINGLE INSTANCE TYPE PERAUTO SCALING GROUP API THROTTLING RETRIES & EXPONENTIAL BACKOFF
- 8. PREWARM INFRA BEFORE MATCHTIME PROACTIVE SCALE UP WITH BUFFER FOR SPIKES SECONDARY AUTO SCALING GROUP SPOT FLEET DIVERSIFIED INSTANCE TYPES Battle tested scaling strategy!
- 9. MACHINE LEARNING BASED AUTOSCALING Future.. IPL 2019 onwards INTELLIGENT SCALE UP DECISIONS RUN IPL & WORLD CUP 2019 ON AUTO PILOT MODE
- 10.