Exam SY0-601 topic 1 question 184 discussion

CF - I had to look it up, so for those that didn't know; "Many people use the terms fog computing and edge computing interchangeably because both involve bringing intelligence and processing closer to where the data is created" - https://www.techtarget.com/iotagenda/definition/fog-computing-fogging

F. Fog computing and A. Private cloud would BEST meet the requirements. Fog computing refers to a decentralized computing infrastructure where data and applications are processed at the edge of the network, closer to the devices that generate or collect the data. This reduces the latency between devices, as data does not have to travel back and forth from a central location. A private cloud architecture provides dedicated, isolated network infrastructure that is operated solely for an organization. This allows for the creation of a low latency network environment, as all the devices are connected to a private network that is managed by the organization. This type of architecture also provides more control over security, which is a key concern for organizations that process sensitive data.

F. Fog computing: Fog computing (also known as edge computing) involves performing computational tasks, including analytics, on devices at the edge of the network, closer to the data source. This reduces latency by processing data locally and can minimize the need for transmitting large amounts of data over the network. A. Private cloud: A private cloud allows for the deployment of resources in a dedicated environment, providing control over the infrastructure. While it may not directly address the low-latency requirement, having a private cloud can offer customization options, and if combined with edge computing (fog computing), it can contribute to meeting the overall requirements.

F. Fog computing C. Hybrid cloud

The best options to meet the requirements of low latency between network-connected devices and reduced bandwidth by performing analytics directly on the endpoints would be A. Private cloud and F. Fog computing. Private cloud is a type of cloud computing that delivers similar advantages to public cloud, including scalability and self-service, but through a proprietary architecture. Unlike public clouds, which deliver services to multiple organizations, a private cloud is dedicated to the needs and goals of a single organization. Fog computing, also known as fog networking or fogging, is a decentralized computing infrastructure in which data, compute, storage and applications are distributed in the most logical, efficient place between the data source and the cloud. It reduces the bandwidth needed and reduces the back-and-forth communication between sensors and the cloud, which can negatively affect performance. By doing this, it can save network bandwidth and use less resources to obtain the necessary results.

In this way, a private cloud can make it easier for an organization to customize its resources to meet specific IT requirements. Private clouds are often used by government agencies, financial institutions, any other mid- to large-size organizations with business-critical operations seeking enhanced control over their environment. Private Cloud = enhanced control over their environment. Hybrid Cloud = By moving workloads to the edge, devices spend less time communicating with the cloud, reducing latency, and they are even able to operate reliably in extended offline periods.

https://azure.microsoft.com/en-us/resources/cloud-computing-dictionary/what-are-private-public-hybrid-clouds Many organizations choose a hybrid cloud approach due to business imperatives such as meeting regulatory and data sovereignty requirements, taking full advantage of on-premises technology investment, or addressing *low latency issues.*

C-F: While a private cloud can provide security and control, it may not be as suitable for "low-latency" requirements in scenarios involving network-connected devices. Hybrid cloud environments can also incorporate edge computing, which processes data closer to the source (devices) to reduce latency and improve performance.

I don't see how hybrid has lower latency or somehow is a better pair with fog? please explain

Fog computing: Fog computing, also known as edge computing, is a decentralized computing infrastructure that extends computing resources to the edge of the network, closer to the devices and sensors generating data. This approach reduces latency since data processing and analytics can be performed locally on the endpoints, avoiding the need to send all data to centralized cloud servers. It also helps reduce bandwidth usage by filtering and processing data at the edge before sending relevant information to the cloud for further analysis or storage. Hybrid cloud: A hybrid cloud architecture combines a private cloud (on-premises infrastructure) and a public cloud (external cloud services). With a hybrid cloud, organizations can keep critical or sensitive data on-premises in the private cloud while leveraging the public cloud's scalability and resources for less sensitive or non-sensitive tasks. By using a combination of private and public clouds, organizations can optimize data storage and processing, achieving low latency and reduced bandwidth usage when necessary.

performing analytics directly on the endpoints: Fog Computing

The two options that would best meet the requirements of a cloud-based architecture with low latency between network-connected devices and reduced bandwidth by performing analytics directly on the endpoints are: F. Fog computing Fog computing is a distributed computing architecture that brings computing resources and application services closer to the edge of the network, enabling low latency and reducing the bandwidth required for data transfer. C. Hybrid cloud A hybrid cloud combines the benefits of a public and private cloud. By placing compute and storage resources closer to the edge of the network, organizations can take advantage of low latency and reduced bandwidth for applications that require real-time data processing. Therefore, options F and C would be the best choices for meeting the requirements described.

The two options that would BEST meet the requirements of low latency between network-connected devices and reduced bandwidth through endpoint analytics are: C. Hybrid cloud: A hybrid cloud architecture would allow the systems engineer to leverage both public and private cloud resources. The private cloud could be used to perform endpoint analytics, while the public cloud could be used for other cloud-based services. This would reduce the latency between network-connected devices while still leveraging cloud-based resources. F. Fog computing: Fog computing is a decentralized computing architecture that allows for analytics to be performed at the edge of the network, closer to the source of the data. This reduces the amount of data that needs to be transmitted to the cloud, reducing the bandwidth requirements and improving latency. Fog computing is often used in IoT environments where devices are geographically distributed and require low latency communications.

Fog computing and hybrid cloud would BEST meet the requirements. Fog computing is a distributed computing architecture that performs analytics and other processing on the edge of a network, which reduces the amount of data that needs to be transmitted and the associated bandwidth requirements. Hybrid cloud is a cloud computing environment that uses a mix of on-premises, private cloud and third-party public cloud services. It provides low latency between network-connected devices and reduces bandwidth requirements by performing analytics directly on the endpoints

Fog for sure. But Hybrid Cloud combines public and private cloud. How is that going to allow for lower latency between network devices? Public cloud involves services on the internet available for anyone to access. Its gotta be something else

F. Fog computing: Fog computing, also known as edge computing, is a distributed computing model that brings computation and data storage closer to the network's edge. By performing analytics directly on the endpoints, it reduces the bandwidth required, and by leveraging a cloud-based architecture, it provides low-latency communication between devices. C. Hybrid cloud: A hybrid cloud is a combination of public and private clouds that enables the sharing of workload between them. By leveraging a hybrid cloud architecture, the systems engineer can design the system to perform the analytics on the private cloud, reducing the bandwidth required, and leverage the public cloud for low-latency communication between the network-connected devices.

Fog computing and hybrid, hybrid cloud is best solution for low latency, not private.