AWS Interview Questions and Answers for freshers in 2023 for AWS jobs in kolkata, Bangalore, Pune, Hyderabad, Delhi, Mumbai.
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AWS has become the most popular Cloud services in the year 2023.The continuous increase in demand for AWS Cloud Computing skills makes the golden opportunity for freshers and working professionals to get into this new domain by preparing and upgrading AWS skills keeping their previous experience relevant. The popularity of AWS has resulted in a high demand for professionals with AWS skills and expertise, especially in major cities such as Kolkata, Bangalore, Pune, Hyderabad, Delhi, and Mumbai.This has made it an attractive career choice for freshers, graduates, and professionals in 2023. The working professionals who are wotking in some different domains can also switch their career in AWS Cloud for a better career growth in near future. As a fresher, it's important to prepare yourself for AWS job interviews by familiarizing yourself with common AWS interview questions and answers. Apart from that you need hands on skills for relevent aws services and resources.
AWS Interview Questions and Answers - 2023 [ updated ]::
Public key-pair: A public key-pair is a file that is shared with other services or resources. It is a non-secret key that is used for encrypting data. When a service or resource needs to encrypt data, it uses the recipient's public key to do so. The recipient can then use their private key to decrypt the data.
AWS allows you to create a VPC with an IP address range of between /16 and /28. The smaller the IP address range, the fewer subnets you can create.
In general, you can have up to 200 subnets per VPC. However, the exact number of subnets you can create depends on the IP address range of the VPC and the size of the subnets you create
Strong Consistency: This consistency model ensures that all data reads will return the most recent version of the data, and all writes will be applied in the same order they were submitted. AWS services that support strong consistency include Amazon DynamoDB, Amazon DocumentDB, and Amazon Aurora.
Eventual Consistency: This consistency model allows for temporary inconsistencies between data replicas, but eventually all replicas will converge to the same state. AWS services that support eventual consistency include Amazon S3, Amazon Kinesis, and Amazon Simple Queue Service (SQS).
Read-after-Write Consistency: This consistency model ensures that all data reads after a write operation will return the most recent version of the data. AWS services that support read-after-write consistency include Amazon S3, Amazon DynamoDB, and Amazon RDS.
Session Consistency: This consistency model ensures that all data reads and writes within a session will be consistent. AWS services that support session consistency include Amazon ElastiCache and Amazon DocumentDB.
Consistent Prefix: This consistency model ensures that all data reads will return a consistent prefix of the data, even in the presence of concurrent updates. AWS services that support consistent prefix include Amazon DynamoDB and Amazon SimpleDB.
Monotonic Read Consistency: This consistency model ensures that a data read will never return an older version of the data than a previous read. AWS services that support monotonic read consistency include Amazon DynamoDB and Amazon S3.
Geo-Targeting is achieved by using a set of rules that us define in usr CloudFront distribution. These rules can be based on several criteria, such as the user's IP address or the country that the user is located in. We can then use these rules to specify which version of usr content to serve to users from different regions.
Recovery Time Objective (RTO) is the maximum amount of time it should take to restore an application after a disaster or outage. It is a measure of how quickly you need to get your application up and running again. For example, if your RTO is one hour, it means that you need to be able to restore your application within one hour of an outage.
Recovery Point Objective (RPO) is the maximum amount of data loss that you are willing to tolerate in case of a disaster or outage. It is a measure of how much data you can afford to lose. For example, if your RPO is one hour, it means that you can afford to lose up to one hour of data in case of a disaster. Both RTO and RPO are important considerations when designing a DR strategy in AWS. RTO and RPO can be achieved through a combination of techniques such as backups, replication, multi-region architectures, and disaster recovery services like AWS Disaster Recovery.