40 AWS Interview Questions

AWS Config is great for managing your AWS environment because it allows you to assess, audit, and evaluate the configurations of your AWS resources. First, you'd enable AWS Config, and it will start recording configurations and changes over time. This historical data is invaluable for compliance auditing and troubleshooting.

You can then create custom rules or use built-in managed rules to continuously monitor the compliance of your resources. For example, you can set a rule to check whether your S3 buckets have public access blocked. Notifications via Amazon SNS can alert you whenever there’s non-compliance, which helps you take swift corrective action. It's superb for maintaining a well-governed, consistent environment.

Route 53 is Amazon's scalable and highly available Domain Name System (DNS) web service. Essentially, it translates human-readable domain names, like www.example.com, into IP addresses, which are used to route traffic to the correct servers. It can be used for domain registration, DNS routing, and health checking.

The way it works is pretty straightforward. When a user enters a domain name into their browser, Route 53 directs the query to the AWS infrastructure. Based on the routing policy set—such as simple, weighted, latency-based, or failover—Route 53 then resolves the DNS request to an appropriate IP address, ensuring that the user is directed to the best possible server instance, whether it's based on response time, geographical location, or server health.

Amazon S3 Glacier is a storage service optimized for infrequent access and archival data. It's designed to offer extremely low-cost storage for data that doesn't need to be accessed often but must be available for long-term retention, such as backups, compliance records, or old media files.

You should use S3 Glacier when you don't need immediate access to your data but want a cost-effective way to store large amounts of archival data securely and durably. For example, scenarios like long-term data backups, regulatory archives, and digital media archives are perfect use cases.

AWS Snowball is a data transfer service designed to securely migrate large amounts of data into and out of AWS. It involves a ruggedized physical appliance that you can order from AWS, fill with data, and then ship back. This is particularly useful when transferring data over the internet would be too slow or cost-prohibitive, especially for large-scale datasets that could take days or weeks to transfer online. Typical use cases include data center migrations, content distribution, disaster recovery, and periodically moving large datasets like those from scientific research or media production.

AWS Trusted Advisor is a service that provides real-time guidance to help you optimize your AWS environment. It looks at five main categories: cost optimization, performance, security, fault tolerance, and service limits. By analyzing your account, it offers best practice recommendations to help you improve your infrastructure, increase security, and reduce costs. It's like having an expert constantly monitoring your environment and suggesting improvements.

To secure data at rest in AWS, you can leverage services like AWS Key Management Service (KMS) to manage encryption keys. Many AWS storage services, such as Amazon S3, EBS, and RDS, support encryption at rest that can utilize KMS for key management. With these services, you can either use AWS-managed keys or create your own customer-managed keys.

Another way is to use server-side encryption, where AWS handles the encryption and decryption process for you. For example, in S3, you can use S3-Managed Encryption Keys (SSE-S3) or KMS-Managed Encryption Keys (SSE-KMS). You can also perform client-side encryption before storing the data in AWS, ensuring that data is encrypted before it even enters AWS infrastructure.

Lastly, ensure proper access control through IAM policies. Limit who can access KMS keys and encrypted data by setting fine-grained permissions and using IAM roles and policies effectively. This provides an additional layer of security for your encrypted data.

To migrate a database to Amazon RDS, you generally start by selecting the right database engine (like MySQL, PostgreSQL, etc.) and setting up an RDS instance. You'll then configure your security settings, ensuring that network access, IAM roles, and any other security protocols are properly set.

Next, you create a backup of your existing database and upload it to an Amazon S3 bucket. From there, you can use the RDS console or CLI to restore the database from the backup. Finally, you'll need to test the new RDS instance to make sure everything works as expected, update your application configuration to point to the new database, and then switch over your production traffic.

AWS CloudTrail is a service that logs all the API calls made in your AWS account. It records details like the identity of the API caller, the time of the call, the source IP address, the request parameters, and the response elements returned by the AWS services. This is crucial for governance, compliance, and auditing purposes.

The importance of CloudTrail lies in its ability to provide a complete history of user activity and API calls for your account. This information can be invaluable when trying to diagnose operational issues, understand user behavior, or ensure compliance with internal policies or regulatory requirements. It also helps in detecting any unauthorized access or unusual activity that might indicate a security breach.

An Elastic Load Balancer (ELB) in AWS distributes incoming application traffic automatically across multiple targets, such as EC2 instances, containers, and IP addresses, in one or more Availability Zones. It helps ensure that no single instance bears too much load, enhancing the fault tolerance and availability of your application. By balancing traffic, it can help your application scale horizontally to handle more load, and also provides health checks to ensure that traffic is only directed to healthy instances.

Amazon VPC, or Virtual Private Cloud, lets you carve out a private network within the AWS cloud. You can control various aspects like IP addressing, subnets, route tables, and network gateways. It’s like having your own data center, but it’s all virtual and managed through AWS.

Some of its main features include subnets that can be public or private, which is useful for separating your web servers from your database servers. Security is tight, thanks to network ACLs and security groups. You also have options for VPN connectivity to link your on-premises data centers to your VPC. Plus, with VPC Peering, you can connect multiple VPCs together for a more integrated network experience.

Stopping an EC2 instance halts it, which means the instance is shut down and the data on the root EBS volume is preserved. You can restart it later and it will boot up with the same instance ID. You're still charged for the storage, but not for the compute time while it's stopped.

Terminating an EC2 instance, on the other hand, actually deletes the instance. All the data stored on the root EBS volume is lost (unless you've taken a snapshot or have additional EBS volumes attached). You can't restart a terminated instance; you'd need to create a new one from scratch if you need it again.

AWS Lambda is a serverless computing service that lets you run code without provisioning or managing servers. You write your code and upload it to Lambda, and it handles the rest, automatically scaling and executing your code in response to triggers, like HTTP requests through API Gateway or changes in an S3 bucket.

Some common use cases include real-time file processing, such as resizing images on-the-fly when they’re uploaded to S3, or executing backend logic for web and mobile applications. It's also great for creating event-driven systems like data transformations and automating tasks like sending notifications or cleaning up logs.

Setting up and using IAM roles in AWS is straightforward. First, you go to the IAM console and create a role, choosing the trusted entity like an AWS service, another AWS account, or a web identity. Then, you attach policies to the role to define what permissions it has. For example, you might give it read access to an S3 bucket or full access to an EC2 instance.

Once the role is created, you can then assign it to resources. For example, for an EC2 instance, you can attach the IAM role to an instance at launch or to an existing instance. This allows the instance to assume the role and inherit its permissions, thus allowing it to interact with other AWS services securely.

Regions are distinct geographical areas that AWS uses to house its data centers. Each region comprises multiple isolated locations known as availability zones (AZs). Availability zones are designed to be independent but close enough to offer low-latency connectivity. Essentially, regions allow you to deploy your applications in different parts of the world, while availability zones within a region provide redundancy and high availability by spreading your resources across physically separate locations.

AWS Elastic Beanstalk is used to deploy and manage applications in the cloud without worrying about the infrastructure that runs those applications. You simply upload your code, and Elastic Beanstalk automatically handles capacity provisioning, load balancing, scaling, and application health monitoring. It supports a variety of platforms including Java, .NET, PHP, Node.js, Python, Ruby, and Docker, making it quite versatile for developers.

Managing secrets and sensitive information in AWS can be handled effectively using AWS Secrets Manager and AWS Systems Manager Parameter Store. AWS Secrets Manager allows you to securely store, rotate, and manage database credentials, API keys, and other secrets. It automatically rotates secrets according to a specified schedule, which helps in maintaining security best practices.

AWS Systems Manager Parameter Store lets you store configuration data and passwords as parameter values. You can grant permissions to specific IAM roles and users to control access to these parameters. Additionally, you can use key management services like AWS KMS to encrypt the parameters for added security. Combining these tools ensures that sensitive information is handled securely and efficiently within your AWS environment.

AWS Key Management Service (KMS) is used for creating and managing cryptographic keys, and controlling their use across a wide range of AWS services and in your applications. Its primary purpose is to help protect your data by using hardware security modules (HSMs) to generate and store keys with strong security. You can also audit key usage through AWS CloudTrail to ensure compliance and security best practices. Basically, it centralizes key management and simplifies integrating encryption and decryption features seamlessly into your services.

AWS, or Amazon Web Services, is a comprehensive cloud computing platform provided by Amazon. It offers a mix of infrastructure as a service (IaaS), platform as a service (PaaS), and packaged software as a service (SaaS) offerings. The key idea behind AWS is to provide scalable, reliable, and low-cost cloud computing solutions.

Among its main services, you'd find Amazon EC2 (Elastic Compute Cloud) for scalable virtual servers, Amazon S3 (Simple Storage Service) for object storage, and AWS Lambda for serverless computing. AWS also offers databases like Amazon RDS (Relational Database Service) and Amazon DynamoDB for NoSQL, along with tools for networking, application services, and IoT, to name a few. The breadth and depth of AWS services make it suitable for startups to large enterprises looking to scale efficiently.

Amazon EC2 (Elastic Compute Cloud) is essentially a web service that provides resizable compute capacity in the cloud. It’s essentially like renting virtual machines where you can run applications, manage the operating system, and handle data processing tasks. You get full control of the instances, and you can configure them to your needs, choose your operating system, and scale as necessary.

On the other hand, Amazon S3 (Simple Storage Service) is more about storage than computation. It’s designed for storing and retrieving any amount of data, at any time. It’s often used for storing large amounts of data like backups, documents, and media files. The emphasis here is on reliable, scalable storage with high availability, rather than computation.

In short, use EC2 when you need raw computing power to run your own applications, and use S3 when you need to store and access large volumes of data.

AWS CloudFormation provides a way to model and set up your Amazon Web Services resources so that you can spend less time managing those resources and more time focusing on your applications. It allows you to define your infrastructure as code, making it easy to replicate environments and ensure consistency across multiple deployments. You can also automate resource provisioning, which reduces the chance of manual errors and improves efficiency. Overall, it saves time, ensures consistency, and adds a layer of automation to your infrastructure management.

Amazon RDS is a managed relational database service, meaning it supports SQL-based databases like MySQL, PostgreSQL, MariaDB, Oracle, and Microsoft SQL Server. It handles tasks like backups, patching, and scaling, and is ideal for applications requiring complex queries and transactions involving multiple tables.

Amazon DynamoDB, on the other hand, is a fully managed NoSQL database. It's designed for high performance on large-scale data workloads, providing fast and predictable throughput. DynamoDB is great for use cases like real-time analytics, mobile apps, and IoT applications where low-latency data access is critical and you can leverage a key-value or document data model.

Auto Scaling in AWS is a feature that automatically adjusts the number of EC2 instances in your application based on the current demand. If your application sees an increase in traffic, Auto Scaling can add more instances to handle the load, and if the demand decreases, it can reduce the number of instances to save costs.

It primarily works through policies and thresholds you set. For example, you might configure Auto Scaling to add more instances when CPU utilization goes above a certain percentage, or remove instances when it drops below another percentage. It uses Amazon CloudWatch to monitor metrics and triggers scaling actions based on the rules you define. This way, your application can seamlessly scale up and down, maintaining performance and cost-efficiency.

Achieving high availability in AWS relies on utilizing its global infrastructure and various services. One key approach is to use multiple Availability Zones (AZs) within a region to ensure redundancy. Deploying your applications across multiple AZs means that even if one goes down, the others can take over, minimizing downtime.

Combining this with services like Elastic Load Balancing, which distributes incoming traffic across multiple instances, helps maintain performance and reliability. Additionally, leveraging auto-scaling policies ensures your application can handle varying loads by automatically adjusting the number of running instances based on demand.

For data storage, using Amazon RDS with Multi-AZ deployments or DynamoDB with built-in replication can protect against data loss and provide failover capabilities. Employing these strategies together can significantly boost your application's availability and resilience in the AWS cloud.

You can monitor AWS resources using Amazon CloudWatch. It collects monitoring and operational data in the form of logs, metrics, and events. For instance, you can set up CloudWatch Alarms to notify you if a specific threshold is breached, like CPU utilization or memory usage. Additionally, AWS CloudTrail helps by logging API calls for your account, which is useful for auditing and tracking changes. For more complex architectures, you might also want to consider third-party tools or AWS Trusted Advisor for additional insights and recommendations.

EBS, or Elastic Block Store, is a block storage system designed to work with EC2 instances. It behaves much like a physical hard drive would, offering low-latency performance and the ability to take snapshots for backup. On the other hand, EFS, or Elastic File System, is a managed file storage service that can be shared across multiple EC2 instances. It provides scalable, elastic storage with automatic scaling and can handle high levels of throughput and IOPS.

EBS is typically used when you need dedicated storage for a single EC2 instance that requires consistent, low-latency performance. It's ideal for databases or applications needing block-level storage. EFS, however, is your go-to when you need shared access across multiple instances, such as for web serving, content management, or big data analytics. With EFS, the storage capacity automatically grows and shrinks as you add and remove files, making it highly dynamic and easy to manage.

Amazon CloudFront is a content delivery network (CDN) service that speeds up the delivery of your static and dynamic web content, such as HTML, CSS, JavaScript, and media files, to users globally. It works by caching your content at edge locations around the world, and when a user requests your content, CloudFront delivers it from the nearest edge location, reducing latency and improving load times.

When you create a CloudFront distribution, you specify the origin servers, like an S3 bucket or an HTTP server, from which CloudFront retrieves the original version of the content. CloudFront then caches copies of this content at edge locations. If the content is already cached when a request is made, CloudFront serves it immediately; if not, it retrieves it from the origin and then caches it for future requests. This makes your applications perform better and scales seamlessly as your traffic grows.

The Shared Responsibility Model in AWS defines the balance of security responsibilities between Amazon Web Services and its customers. AWS is responsible for the security "of" the cloud, which includes infrastructure security, like hardware, software, networking, and facilities that run AWS Cloud services. Customers are responsible for security "in" the cloud—this covers the things they manage within their AWS environment, like their data, applications, identity and access management, and operating system configurations. This way, AWS ensures the global infrastructure’s security, while customers retain control and flexibility over their specific configurations and data security.

Amazon Redshift offers several key benefits. It provides fast query performance because of its columnar storage and advanced compression. This makes data retrieval efficient, even with large datasets. The scalability is another major perk; you can start small and scale up to petabytes of data without a lot of fuss, just by adding more nodes or leveraging concurrency scaling.

From a cost perspective, it's pretty flexible. You pay only for what you use, and there are options for both on-demand pricing and more economical reserved instances. Additionally, its integration with other AWS services like S3 and AWS Glue makes managing and analyzing big data a lot more seamless.

You can automate tasks in AWS using several tools and services. AWS Lambda lets you run code in response to events or triggers, which is great for automating processes without provisioning servers. AWS CloudFormation helps by allowing you to define and provision infrastructure as code, so you can consistently replicate environments by simply deploying a stack. Additionally, AWS Systems Manager and AWS Step Functions are both powerful for automating complex workflows and operational tasks. Combining these tools can significantly streamline your AWS operations.

Amazon EC2 offers several pricing models to help you manage your costs effectively based on your workload requirements. The most common one is On-Demand, where you pay for compute capacity by the hour or second with no long-term commitments. It’s great for short-term or unpredictable workloads that can't be interrupted.

Another model is Reserved Instances, where you commit to using EC2 over a period of one or three years in exchange for a significant discount. This is ideal for stable, predictable applications that need to run continuously. Spot Instances allow you to bid on spare AWS capacity at a lower price, which is perfect for flexible workloads that can tolerate interruptions. Lastly, there are Savings Plans which offer discounts in exchange for a commitment to a consistent amount of usage over one or three years, similar to Reserved Instances but more flexible across instance types.

Implementing disaster recovery in AWS starts with understanding your RTO (Recovery Time Objective) and RPO (Recovery Point Objective). Depending on those, you might choose different strategies. AWS offers several options, like backup and restore, pilot light, warm standby, and multi-site active-active.

For a simple backup and restore strategy, you can use AWS services like S3 for storing your backups and AWS Backup for managing your backup schedules and lifecycles. For more complex needs, setting up a pilot light involves maintaining a minimal environment that can scale up quickly when needed. You can also leverage Route 53 for DNS failover and AWS Lambda for automating failover processes.

For highly critical applications, a multi-site active-active setup across multiple AWS regions ensures the highest availability and resilience. This setup requires duplicates of your environment in different regions with data replication mechanisms like Amazon RDS cross-region replication or DynamoDB global tables.

AWS offers a wide range of storage options to meet different needs. For object storage, there's Amazon S3, which is great for storing and retrieving any amount of data from anywhere. If you need block storage for your EC2 instances, Amazon EBS is the way to go, giving you persistent storage that you can attach to your virtual machines.

For file storage, Amazon EFS provides scalable file storage for use with AWS Cloud and on-premises resources. If you're dealing with large-scale data, Amazon Glacier and S3 Glacier Deep Archive offer cost-effective archival storage. Then, there’s AWS Storage Gateway, which connects your on-premises software appliances with AWS cloud-based storage to provide seamless and secure integration. Each option is optimized for different use cases, so you can tailor your storage strategy to best fit your needs.

A big part of securing applications in AWS is leveraging the shared responsibility model. Use AWS services like IAM for fine-grained access control, making sure to follow the principle of least privilege. Regularly rotate credentials and use multi-factor authentication.

Utilize VPCs to isolate your network, and employ security groups and network ACLs to control traffic. Encrypt data at rest using AWS KMS and data in transit with TLS. Regularly patch your OS and applications; services like AWS Systems Manager can help automate this process. Finally, monitor everything with AWS CloudTrail and Amazon CloudWatch to get alerts on suspicious activities.

To set up a VPN connection in AWS, you'll typically use AWS Virtual Private Gateway and configure it with your on-premises environment. Start by creating a Virtual Private Gateway in the VPC console and attach it to your VPC. Next, you'll configure the Customer Gateway on AWS with your on-premises gateway device's public IP address and routing information.

Once both gateways are set up, create a VPN connection in AWS. You'll need to define your customer gateway parameters as well as any required route tables. After the connection is established, download the configuration file provided by AWS, which includes the necessary settings for your specific device, and apply these settings to your on-premises gateway. This sets up the secure IPsec tunnel, connecting your AWS resources with your on-premises network.

The AWS Well-Architected Framework provides a set of best practices for designing and operating reliable, secure, efficient, and cost-effective systems on AWS. It’s based on five pillars: Operational Excellence, Security, Reliability, Performance Efficiency, and Cost Optimization. Each pillar includes design principles and best practices that help you make informed decisions about your architecture, identify areas for improvement, and ensure that your applications are optimized for the cloud.

AWS Systems Manager is a versatile service that helps you manage and automate operational tasks across your AWS resources. We mainly use it for patch management, automating routine tasks, and managing configurations. For example, the Run Command feature lets you remotely manage the configuration of your instances at scale without manually logging in to each instance. Another neat functionality is the Parameter Store, which securely stores and manages secrets and configuration data.

Additionally, Systems Manager provides centralized operational insights through its OpsCenter and can visualize your resource data in the Resource Groups. All these tools together make troubleshooting and maintaining an AWS environment much more efficient. Overall, it streamlines and automates many of the day-to-day tasks, making it easier to manage your infrastructure.

AWS Direct Connect is a service that establishes a dedicated network connection from your premises to AWS. The main role of Direct Connect is to provide a more consistent network experience compared to internet-based connections, with lower latency and increased bandwidth options. This dedicated line can be essential for workloads requiring robust, high-performance connectivity, such as large data transfers, real-time data feeds, or secure connections to your on-premises environment.

Using Direct Connect can also be cost-effective compared to traditional internet connections, especially when transferring significant amounts of data to and from AWS. It allows for more predictable network performance and can simplify network architecture by reducing the number of hops your data travels through the public internet.

Cost optimization in AWS involves a mix of right-sizing your resources, using Reserved Instances and Savings Plans, and taking advantage of various AWS pricing models. You should regularly analyze your usage patterns and identify underutilized resources. For example, you can use AWS Trusted Advisor and Cost Explorer to identify savings opportunities, like moving to smaller instances or releasing unused Elastic IPs.

Another crucial practice is to take advantage of serverless options like AWS Lambda or services such as AWS Auto Scaling that adjust resources based on demand, which can significantly cut costs. Also, consider implementing cost allocation tags to track spending more efficiently and set budgets or alerts to avoid unexpected expenses.

AWS ECS (Elastic Container Service) and AWS EKS (Elastic Kubernetes Service) are both managed container orchestration services, but they cater to slightly different use cases and user preferences. ECS is AWS's own proprietary container orchestration service, which is tightly integrated with other AWS services. It's simpler to set up and manage, designed for users who prefer staying within the AWS ecosystem and don't need the complexity or specific features of Kubernetes.

EKS, on the other hand, runs Kubernetes, which is an open-source container orchestration system used widely across various environments. With EKS, you can leverage the vast Kubernetes ecosystem and tools, providing more flexibility and potentially better cross-cloud compatibility. It’s a great fit for teams that have experience with Kubernetes or need features specific to it, like custom controllers and configurations. Essentially, if you’re looking for simplicity and tight AWS integration, ECS might be the way to go; if you need the power of Kubernetes, EKS is your better choice.

AWS Organizations is all about simplifying the management of multiple AWS accounts. It lets you create groups of accounts, apply policies for governance, and manage them all from a single place. So, whether you need to enforce security protocols or manage billing, it centralizes and streamlines those tasks.

It also helps in resource sharing and consolidation of billing. For example, you can take advantage of volume discounts by pooling usage across multiple accounts. Basically, it’s a great tool for maintaining order and control when you’re dealing with several AWS accounts.