Keeping your Cloud Footprint in Check - GOTO...
Transcript of Keeping your Cloud Footprint in Check - GOTO...
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Keeping your Cloud Footprint in Check
Coburn Watson
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@coburnw
• Cloud Performance and Reliability @ Ne6lix – Reduce TTD and TTR – Build innova<ve performance analysis tooling – Op<mize usage of AWS Cloud – Steer global user traffic and support failover – Inject Chaos into produc<on environment – Drive opera<onal best prac<ce adop<on
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• 67M+ Subscribers • > 50 countries • > 3 billion hours of video streamed monthly • Huge cloud footprint • Homegrown CDN • Strong Originals slate
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• Strong focus on open source efforts • hTps://ne6lix.github.io/
Atlas
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Our Priori<es
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(me)
Innova<on
Reliability
Efficiency
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Cost of Innova<on and Reliability
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Maximize Innovation
• Capacity On-‐Demand • Commit-‐to-‐Cloud in minutes • Single Produc<on Account (~ 350 µservices) • Burst into on-‐demand, cover with reserva<on purchases
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Cost of Reliability
• Red-‐Black push model • Over-‐provision for redundancy in AWS Region • Global redundancy through failover • Purchase “Heavy” AWS EC2reserva<ons to secure capacity
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Efficiency
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Efficiency Goals
• Have them and track them!
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Monitoring Costs
• ICE: Open Source AWS Cost Monitoring U<lity • Internal Cost Repor<ng pushed to first-‐level managers
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Maximize Sharing
• Single Produc<on Account • Fewer/Larger Pools • Maximize Shared Capacity
> 75% in only 8 EC2 Instance Types
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Encourage Borrowing
• All accounts are linked at a billing level • Large troughs of unused capacity exist (Autoscaling) • Interrup<ble workloads for internal “Spot”
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Optimization
• Direct Consulta<on for “Big Fish” • Tooling for Everyone
1 • Develop
2 • Deploy • Scale
3 • Op<mize (if needed)
New Services or Features Ongoing Service Development
1 • Develop
2 • Canary
3 • Op<mize (if needed) • Deploy
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Improving Stack Observability
• Too big for commercial tools • Patch key middleware where necessary
Mixed-‐Mode JVM CPU Flame Graph Transac<on Tracing with Resource Demand
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Monitor Capacity Shortfalls
• Constrain On-‐Demand charges • Iden<fy/alert on significant capacity provisioning events
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Data Points
• Internal Borrowing • Encoding consumed 135k cross-‐account EC2 Instance hours June 2015 (> ~ $200k/monthly savings)
• Data Pla6orm (Hadoop, etc.) saves > $1MM/year
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Summary
• Target your Innova<on:Efficiency ra<o
• Push cost context to the team level • Embrace the elas<city of the Cloud
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Thanks !