Implementing architectures to automatically recover from failure

What AWS service would you use to design a scalable and highly available architecture?

AWS Elastic Load Balancing (ELB) in combination with Auto Scaling helps in designing an architecture that can scale out (or in) according to demand and maintain high availability. ELB distributes incoming application traffic across multiple targets, such as EC2 instances, in multiple Availability Zones, while Auto Scaling adjusts the amount of compute capacity to handle the load efficiently.

Can you describe a scenario where Amazon RDS Multi-AZ deployment is beneficial?

Amazon RDS Multi-AZ deployment is beneficial for database workloads requiring high availability and durability. In the event of a database instance failure, AWS automatically switches to a standby replica in a different Availability Zone (failover), minimizing disruption. It’s also helpful during maintenance tasks as the standby can take over without service interruption.

How does Amazon Route 53 contribute to an architecture’s ability to recover from failure?

Amazon Route 53 supports various routing policies such as Failover routing policies, which allow the traffic to be automatically directed away from failed endpoints to healthy ones. This ensures that the application remains available even if a part of the infrastructure fails. Route 53 health checks can detect outages and reroute traffic accordingly.

In the context of AWS, how would you use a combination of AWS services to provide disaster recovery for a mission-critical application?

For mission-critical applications, you can use a combination of Amazon S3 for data backup, AWS Elastic Beanstalk or Amazon EC2 with Auto Scaling for application hosting, and AWS CloudFormation for resource provisioning. AWS RDS Multi-AZ or Amazon Aurora’s Global Databases can be used for the database layer. For cross-region disaster recovery, you can implement Cross-Region Replication in S3 and Amazon Aurora to ensure data is available in another region during a catastrophic failure in the primary region.

What role does AWS CloudWatch play in failure recovery?

AWS CloudWatch monitors AWS resources and the applications you run on AWS in real-time. It can trigger alarms, logs, and events when specified thresholds are breached or anomalies are detected, which can initiate automated responses or recovery actions such as Auto Scaling or restarting EC2 instances. CloudWatch helps in the early detection of failure, allowing for prompt remediation.

How do you configure automated backups in AWS, and how can they aid in failure recovery?

Automated backups can be configured in AWS using Amazon RDS, which provides automatic backups of your database within a user-defined window, retaining them for a period you specify. In cases of data loss or corruption, you can restore your database to any point within the retained period, greatly reducing recovery time after a failure.

Describe the steps to implement a failover strategy using Amazon S3 with versioning and cross-region replication.

To implement a failover strategy with Amazon S3, you would first enable versioning on your S3 bucket to keep historical versions of your objects, protecting against accidental deletions and overwrites. Then, set up cross-region replication to replicate objects to a secondary bucket in a different AWS region, providing a failover solution in the event of a regional service disruption.

What is AWS Elastic Beanstalk and how can it help in automatic failure recovery?

AWS Elastic Beanstalk is a service for deploying and scaling web applications and services developed with Java, .NET, PHP, Node.js, Python, Ruby, Go, and Docker. It automatically handles the details of capacity provisioning, load balancing, scaling, and application health monitoring, which helps in quick recovery from instance failure without manual intervention.

Explain how Amazon ECS facilitates failure recovery in a container-based architecture.

Amazon ECS handles container management and orchestration. It can detect if a container is unhealthy or fails and automatically stops it and launches a new instance of that container. It can also integrate with AWS Load Balancer and Auto Scaling to manage traffic distribution and ensure optimal resource allocation across containers, aiding in rapid failure recovery.

Describe the use of AWS Lambda for failure detection and recovery in serverless architectures.

AWS Lambda functions can be triggered by AWS CloudWatch alarms indicating an issue with a service or application performance. A Lambda function can execute recovery procedures such as invoking other microservices to redistribute the load, restore data from backups, or re-deploy application components automatically without the need for a full server or dedicated infrastructure. This functionality enhances the resilience of serverless architectures.

How can you ensure data resiliency and automatic recovery using Amazon DynamoDB?

Amazon DynamoDB provides built-in automatic recovery features. It replicates data across multiple facilities within an AWS Region to provide built-in high availability and data safety. Global Tables – the fully managed multi-region, multi-master database feature – further extends these capabilities, enabling automatic data replication across multiple AWS Regions for failover and low-latency access.

What strategies would you employ to automate the failover process in a multi-tier application on AWS?

For a multi-tier application on AWS, automate failover using AWS services such as:
– Elastic Load Balancing (ELB) to distribute traffic and detect unhealthy instances.
– AWS Auto Scaling to adjust the compute capacity automatically.
– Route 53 health checks and Failover routing policies for DNS redirection.
– Multi-AZ deployments for RDS to maintain database availability.
– AWS CloudFormation or AWS Elastic Beanstalk for application deployment automation and configuration management.
– SNS notifications and Lambda functions for orchestrating immediate responses to failures detected.