Cloud computing and distributed computing are two major technological advancements that have revolutionized the way we process, store and distribute data. Both offer unique advantages, and the understanding of their capabilities is pivotal to evolving in the modern technology landscape. A comprehensive understanding of the nuances of both is essential for anyone preparing for the AWS Certified Data Engineer – Associate (DEA-C01) examination, as the AWS platform offers services implementing these technologies.
Cloud Computing
Cloud computing is a model for delivering computing services that include servers, storage, databases, networking, software, analytics, at an enterprise scale over the internet. It provides a simple way to access servers, storage, databases and a broad set of application services over the internet.
Cloud Computing service models are often categorized into three types:
- Infrastructure as a Service (IaaS)
- Platform as a Service (PaaS)
- Software as a Service (SaaS)
AWS is a leading cloud service provider that offers all three service models. It has a wide array of well-architected frameworks that a Data Engineer could utilize for designing and managing robust, secure, and efficient systems.
Distributed Computing
On the other hand, distributed computing is a model in which components of a software system are shared among multiple computers. The aim is to improve efficiency and performance. It is about processing large volumes of data that cannot be managed by a single machine, by splitting the data and distributing it over multiple machines, hence the term distributed computing.
AWS offers several services for performing distributed computing tasks. AWS Elastic Map Reduce (EMR) is an exam-important service based on distributed computing. It utilizes a Hadoop framework that allows processing of large sets of data across a scalable EC2 instance cluster. Kinesis and AWS Lambda can also allow distributed computing for real-time data and event-driven systems.
Cloud and Distributed Computing Together
Cloud computing and distributed computing can work hand in hand. Cloud provides the infrastructure (IaaS or PaaS level) to host the distributed systems and take care of the underlying resource management while distributed computing perform the task of data processing. Think of it as a symbiotic relationship that ultimately leads to improved efficiency and performance.
Conclusion
For the AWS Certified Data Engineer – Associate (DEA-C01) exam, the understanding of cloud and distributed computing goes hand in hand. The understanding of AWS services like EMR, S3, Lambda and Kinesis and their roles in cloud and distributed computing models will provide a critical advantage. AWS has markedly enhanced and simplified the way enterprises can leverage these technologies, and an understanding of this can significantly boost your preparations towards the exam. So, understanding these fundamentals can improve both in the examination scenario and real-world cloud computing applications.
Practice Test
True/False: Distributed computing and cloud computing are the same.
- True
- False
Answer: False.
Explanation: Distributed computing refers to a computing system where components located in networked computers interact and coordinate their actions in order to achieve a common goal while cloud computing is a type of computing that relies on shared computing resources rather than having local servers or personal devices to handle applications.
What is a key characteristic of cloud computing?
- a) Shared pooling of resources
- b) Decreased scalability
- c) Lowered accessibility
- d) Single-tenant model
Answer: a) Shared pooling of resources.
Explanation: In cloud computing, the pooling of resources is a crucial aspect that enhances its benefits such as cost-efficiency, ease of accessibility, and scalability.
True/False: In distributed computing, if one of the nodes fails, the whole system will typically fail.
- True
- False
Answer: False.
Explanation: Distributed computing is inherently designed for fault tolerance; if one node fails, others can continue to operate.
Which of the following AWS services might you use for a cloud-based database solution?
- a) Amazon RDS
- b) Amazon S3
- c) Amazon EC2
- d) Amazon Glacier
Answer: a) Amazon RDS.
Explanation: Amazon RDS is a distributed relational database service provided by AWS. The other options are cloud storage (S3 and Glacier) and compute instance services (EC2).
Real-time analytics and video processing are typical uses for:
- a) Big Data
- b) Cloud Computing
- c) Distributed Computing
- d) Edge Computing
Answer: c) Distributed Computing.
Explanation: Distributed computing allows for concurrent processing and thus is ideal for real-time analytics and video processing.
True/False: AWS S3 is a perfect choice for distributing heavy workload because of its durable storage facility.
- True
- False
Answer: True.
Explanation: AWS S3 provides 999999999% durability, making it ideal for distributing heavy workload and backing up important data.
Who is responsible for patching and managing the OS in an AWS managed service like Amazon RDS?
- a) The customer
- b) AWS
- c) Third party
- d) None of the above.
Answer: b) AWS.
Explanation: With Amazon RDS, AWS handles the time-consuming tasks of patching, backing up, and upgrading the database software.
What type of service is AWS Elastic Beanstalk?
- a) Infrastructure as a Service (IaaS)
- b) Database as a Service (DBaaS)
- c) Function as a Service (FaaS)
- d) Platform as a Service (PaaS)
Answer: d) Platform as a Service (PaaS).
Explanation: AWS Elastic Beanstalk is a PaaS that offers a platform for developers to easily deploy and run applications in several languages.
Which of the following is NOT a characteristic of cloud computing according to NIST?
- a) On-demand self-service
- b) Measured service
- c) Broad network access
- d) Resource pooling
- e) Capital expense
Answer: e) Capital expense.
Explanation: Capital expense is not a characteristic of cloud computing; cloud computing helps reduce capital expense by transforming it into operational expense.
True/False: AWS Lambda allows you to run code without provisioning or managing servers.
- True
- False
Answer: True.
Explanation: AWS Lambda is a serverless compute service that lets you run your code without provisioning or managing servers.
What is the AWS storage solution designed for archiving and long-term backup?
- a) Amazon S3
- b) Amazon RDS
- c) Amazon EC2
- d) Amazon Glacier
Answer: d) Amazon Glacier.
Explanation: Amazon Glacier is a low-cost storage service designed for secure, durable, and flexible storage for data archiving and long-term backup.
Transient failure resilience and Continuous processing are advantages of:
- a) Cloud Computing
- b) Real-Time Systems
- c) Batch Processing
- d) Distributed computing
Answer: d) Distributed computing.
Explanation: Distributed computing has the ability to handle transient failures and continuous processing effectively due to its decentralized architecture.
True/False: Interoperability might be a problem in adopting cloud computing.
- True
- False
Answer: True.
Explanation: Because different cloud providers have different standards and APIs, interoperability might be a barrier to adopting cloud computing.
What AWS service could you use to coordinate complex microservices architectures and workflows?
- a) Amazon S3
- b) AWS Step Functions
- c) AWS Redshift
- d) Amazon DynamoDB
Answer: b) AWS Step Functions.
Explanation: AWS Step Functions provides a way to coordinate multiple AWS services into serverless workflows so you can design and run complex applications.
Big data processing and distributed machine learning are typical tasks for:
- a) Distributed Computing
- b) Cloud Computing
- c) Both of the above
- d) None of the above
Answer: c) Both of the above.
Explanation: Both distributed computing and cloud computing support big data processing and distributed machine learning due to their large-scale resource capabilities and processing power.
Interview Questions
What services are featured in Amazon’s distributed computing platform?
Amazon’s distributed computing platform includes services such as Amazon S3, Amazon EC2, Amazon Redshift, and Amazon EMR.
What are the key capabilities of Amazon S3 in AWS?
Amazon S3 provides object storage through a web service interface. It provides scalability, data availability, security, and performance.
In AWS, what is a benefit of Amazon Redshift for big data analytics?
Amazon Redshift is a fast, simple, cost-effective data warehousing service. It enables users to analyze all their data using their favorite analytics tools.
What is AWS EC2 used for in the context of distributed computing and cloud computing?
AWS EC2 refers to Amazon Elastic Compute Cloud. It’s used to provide scalable computing capacity in the AWS Cloud. This eliminates the need for an organization to invest in hardware, leading to faster development and launch of applications.
Describe the fundamental difference between cloud computing and distributed computing.
Distributed computing involves dividing a large problem into smaller parts, which are solved by different computers on a network. Cloud computing, on the other hand, refers to delivering computing services over the internet, allowing access to processing power, storage, and applications on an on-demand basis.
What is the role of Amazon EMR in AWS?
Amazon EMR provides a managed Hadoop framework that makes it easy, fast, and cost-effective to process vast amounts of data across dynamically scalable Amazon EC2 instances.
In cloud computing architecture, what is the storage layer responsible for?
The storage layer in cloud computing architecture is responsible for managing and storing data collected from different resources efficiently.
How does Elastic Load Balancing help in AWS?
Elastic Load Balancing automatically distributes incoming application traffic across multiple targets, such as Amazon EC2 instances, containers, and IP addresses. It improves the availability and fault tolerance of your applications.
What are the advantages of distributed computing in AWS?
Distributed computing in AWS offers several advantages such as scalability, cost-effectiveness, and high availability. It allows processing of large datasets in a parallel and distributed manner.
What is Amazon S3’s role in data archiving and long-term backup?
Amazon S3 offers a low-cost storage service for data archiving and long-term backup. It is designed for durability, and stores data for disaster recovery, helping organizations to keep data safe and retrievable.
How does CloudWatch fit into AWS’s framework?
Amazon CloudWatch provides monitoring and observability of AWS resources and applications. It collects and tracks metrics, collects and monitors log files, provides automated reactions to changes in AWS resources.
What principles does the CAP theorem relate to in distributed systems?
CAP theorem underlines the idea that it is impossible for a distributed data store to simultaneously provide more than two out of the following three guarantees: Consistency, Availability, and Partition tolerance.
What does data durability mean in the context of Amazon S3?
Data durability refers to the long-term, reliable storage of data. Amazon S3 is designed to provide 99.999999999% durability of objects over a given year.
How does AWS safeguard user data on the cloud?
AWS provides several security capabilities and services to increase privacy and control network access. These include Network firewalls built into Amazon VPC, and encryption in transit with TLS across all services.
What is the advantage of using Amazon Redshift over a traditional data warehouse?
Amazon Redshift is specifically designed to deliver superior performance and scalability by using AWS cloud infrastructure. It provides automatic scaling, concurrent and fast query execution, high data compression rates, and a lot more which make it superior to traditional data warehouses.
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