Scale Business Peaks and Save Costs with Amazon AutoScaling
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The document discusses how Amazon AutoScaling allows companies to seamlessly scale their compute capacity on Amazon EC2 instances up and down automatically based on demand, allowing businesses to handle unpredictable load bursts efficiently and save costs by not over-provisioning resources when demand is low. It provides examples of how AutoScaling can be configured to address both unpredictable and predictable load patterns and bursts and the benefits it provides around availability, costs savings, and avoiding lost customers.
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Scale Business Peaks and Save Costs with Amazon AutoScaling
- 1. Scale New Business Peaks with Amazon AutoScaling Harish Ganesan CTO 8KMiles
- 2. Scale New Business Peaks with Amazon AutoScaling Harish Ganesan CTO and Co-Founder 8KMiles harish@8kmiles.com
- 3. Load Patterns of Business E-commerce Online Ticketing Compute Compute Weekly Weekly Online Travel Online Tests / Campaigns Compute Compute Yearly Yearly
- 4. Load Burst Types Un Predictable Bursts Predictable Bursts Compute Compute Time Time
- 5. Traditional Scaling Lost customers • Fixed capacity • Under utilization of resources • Lost Customers Amazon Auto Scaling • Align no. of instances with demand • Flexible capacities and scaling sizes • Save costs
- 6. Amazon AutoScaling • Handle all the variety of load bursts and patterns • Scale out Amazon EC2 instances seamlessly and automatically when demand increases • Scale down unwanted Amazon EC2 instances automatically and save money when demand subsides • Decide the scaling based on AWS CloudWatch metrics
- 7. Amazon AutoScaling Architecture EC2 Instance Elastic Load Balancer … Amazon CloudWatch Scale Up Scale Up Key Concepts : Rule EC2 Instance • Launch Configuration Scale Down Scale Down • Auto Scaling Group Rule • Trigger Scale Up • Policy Predefined Scaling • Alarm Auto Scaling Scale Down Activity Group
- 8. Auto Scaling : Unpredictable Burst Un Predictable Bursts • Configure On demand Auto Scaling policy Compute • Create policies for both Scaling out and Scaling down scenarios Time • Auto Scaling will respond to changing conditions dynamically %as-‐create-‐auto-‐scaling-‐group as-‐group -‐-‐availability-‐zones us-‐east-‐1c – launch-‐configura@on my-‐lconfig -‐-‐max-‐size 24 -‐-‐min-‐size 4 -‐-‐cooldown 180 -‐-‐load-‐balancers my-‐load-‐balancer
- 9. Auto Scaling : Predictable Burst Predictable Bursts Compute • Configure Time based Auto Scaling plan • PutScheduledUpdateGroup Time Action - specify the date and time of execution, minimum, maximum, and desired Instance size of capacity % as-‐put-‐scheduled-‐update-‐group-‐ac@on my-‐group –name My-‐scale-‐ up -‐-‐ @me 2011-‐11-‐12T02:00:00Z -‐min 10 -‐max 50
- 10. Candidates for Auto Scaling • Web Tier • Applica@on Tier • Caching Tier • Load Balancing Tier • Other Stateless Tiers
- 11. Auto Scaling Benefits : Cost Savings 35 % savings 30 % savings Compute Compute Time Time 30 % savings 35 % savings Compute Time
- 12. Auto Scaling Benefits : No Lost customers We can closely align our Infrastructure with our load requirements and save costs Benefits of AutoScaling – work in Happier DevOpsprogress !!! Source: AWS
- 13. Key Points to Remember • Log Files , Data Files and Sessions • Multiple AZ s inside a Region • EBS Backed AMI s are faster to launch • Multiple Instances Types in an Auto Scaling group • Combining Custom CloudWatch Metrics opens huge possibilities • Evaluate Traditional Monitoring
- 14. Thank You For more details on how we can help your business , contact cloud@8KMiles.com Visit us at cloud.8KMiles.com