Infrastructure Design
Scalability
- Auto-Scaling Groups:
- Configure auto-scaling groups to add/remove instances based on demand.
- Set up scaling policies based on metrics like CPU utilization, memory usage, or custom application metrics.
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Regularly test scaling policies to ensure they work as expected.
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Serverless Architectures:
- Use services like AWS Lambda, Google Cloud Functions, or Azure Functions for running code without provisioning servers.
- Design applications to be stateless and leverage managed services for databases, queues, and storage.
- Implement best practices for serverless architectures, such as minimizing cold starts and optimizing function performance.
High Availability
- Multi-Region Deployments:
- Deploy critical applications across multiple regions to ensure availability in case of a regional outage.
- Use global load balancers like AWS Global Accelerator or GCP Cloud Load Balancing to distribute traffic across regions.
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Implement data replication strategies to keep data in sync across regions.
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Multi-Zone Deployments:
- Distribute resources across multiple availability zones within a region to mitigate the impact of zone-specific failures.
- Configure load balancers to route traffic to healthy instances across zones.
- Ensure databases and other critical services are deployed in a multi-zone configuration.
Cost Optimization
- Resource Tagging:
- Implement a tagging strategy to categorize and track resource usage by project, environment, or department.
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Use tags to generate detailed cost reports and identify cost-saving opportunities.
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Rightsizing:
- Regularly analyze resource utilization and resize instances or services to match actual usage.
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Leverage tools like AWS Trusted Advisor, GCP Recommender, or Azure Advisor for rightsizing recommendations.
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Reserved Instances and Savings Plans:
- Purchase reserved instances or savings plans for predictable workloads to reduce costs.
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Continuously review and adjust reservations to match current and projected usage patterns.
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Idle Resource Management:
- Identify and eliminate idle resources, such as unused instances, volumes, or IP addresses.
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Implement automation to stop or terminate idle resources based on predefined policies.
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Cost Monitoring Tools:
- Use cloud provider tools like AWS Cost Explorer, GCP Cost Management, or Azure Cost Management to monitor and analyze costs.
- Set up budgets and alerts to notify stakeholders of unexpected cost increases.
Example Implementation
- Set Up Auto-Scaling for a Web Application:
- Create an auto-scaling group in AWS EC2 with a minimum of 2 instances and a maximum of 10 instances.
- Configure scaling policies to add instances when average CPU utilization exceeds 70% and remove instances when it drops below 30%.
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Test the auto-scaling policies by simulating traffic spikes and observing the scaling behavior.
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Deploy a Multi-Region Application:
- Deploy an application in AWS using AWS Elastic Beanstalk in two regions: US East (N. Virginia) and EU (Ireland).
- Configure Route 53 with latency-based routing to direct users to the closest region.
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Set up DynamoDB global tables to replicate data across both regions.
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Optimize Costs with Reserved Instances:
- Analyze historical usage data for a production environment using AWS Cost Explorer.
- Purchase a 1-year reserved instance plan for m5.large instances based on consistent usage patterns.
- Monitor and adjust reservations every quarter to ensure alignment with current usage.