CLOUD DEPLOYMENT MODELS IN CLOUD COMPUTING
- 2. WHAT IS CLOUD DEPLOYMENT MODELS ► Cloud Deployment Model functions as a virtual computing environment with a deployment architecture that varies depending on the amount of data you want to store and who has access to the infrastructure. ► It defines your cloud architecture, scalability of your computing resources, what you can change, the services provided to you, and how much of the build you own. ► Cloud deployment models also define relationships between the cloud infrastructure and your users (what users are allowed to change or implement.) Types of Cloud Computing Deployment Models ► The cloud deployment model identifies the specific type of cloud environment based on ownership, scale, and access, as well as the cloud’s nature and purpose. The location of the servers you’re utilizing and who controls them are defined by a cloud deployment model. ► The following cloud deployment models are explained: public cloud model, community cloud model, private cloud model, virtual private cloud (VPC),hybrid cloud model, multi-cloud mode, Cloud bursting deployment model and edge computing
- 3. PUBLIC CLOUD DEPLOYMENT MODELS ► The public cloud makes it possible for anybody to access systems and services. The public cloud may be less secure as it is open to everyone. The public cloud is one in which cloud infrastructure services are provided over the internet to the general people or major industry groups
- 4. PUBLIC CLOUD DEPLOYMENT MODELS Advantages ► Minimal Investment ► No setup cost ► Infrastructure Management is not required ► No maintenance ► Dynamic Scalability Disadvantages ► Less secure ► Low customization
- 5. PRIVATE CLOUD DEPLOYMENT MODELS ► The private cloud deployment model is the exact opposite of the public cloud deployment model. It’s a one-on-one environment for a single user (customer). There is no need to share your hardware with anyone else. The distinction between private and public clouds is in how you handle all of the hardware. It is also called the “internal cloud” & it refers to the ability to access systems and services within a given border or organization.
- 6. PRIVATE CLOUD DEPLOYMENT MODELS Advantages ► Better Control ► Data Security and Privacy ► Supports Legacy Systems ► Customization Advantages ► Less scalable ► Costly
- 7. HYBRID CLOUD DEPLOYMENT MODELS ► Hybrid cloud model are made up of two or more cloud deployment models that work together to provide users with greater flexibility and choice when it comes to their cloud-based services. Creating a hybrid cloud means that a company is using the public cloud but also owns on-premises systems, and there is a connection between the two. Due to security requirements or data protection, some companies can’t operate only in the public cloud, so they may choose the hybrid cloud to combine the requirements with the benefits of a public cloud.
- 8. HYBRID CLOUD DEPLOYMENT MODELS Advantages: ► Scalability ► Flexibility ► Cost Efficiency ► Security ► Accessibility Disadvantages: ► Networking Issues ► Security Compliance ► Infrastructure Dependency ► Scalability of on-premise systems is still challenging and can cap the scalability of your system
- 9. TYPES OF HYBRID CLOUD DEPLOYMENT MODEL 1. Hybrid cloud model with staged migration ► Applications or workloads are moved/migrated from an on-premises data centre to a public cloud service provider’s infrastructure. The advantage of this model is that it allows you to use only what you need — allocating as much or as little as needed for each application or transaction. The disadvantage is that it might not provide the same level of control over how things operate as if they were hosted in-house (especially if they were hosted internally). 2. Hybrid cloud model with partially integrated apps ► This model involves moving some but not all applications or transactions into a public cloud environment while keeping others on-premises. This is a great option if your company has applications that can be run in on-premises environments or public clouds like AWS or Azure. 3. Hybrid cloud model with integrated apps ► The hybrid cloud model with integrated apps involves using PaaS software in the public cloud to integrate applications running on-premises and in the public cloud. ► The applications are deployed using IaaS software on-premises, and then they are integrated using PaaS software in the public cloud.
- 10. COMMUNITY CLOUD DEPLOYMENT MODEL ► Community Cloud deployment model allows system and services to be accessible by group of organizations. It shares the infrastructure between several organizations from a specific community. It may be managed internally by organizations or by the third-party.
- 11. Applications of Community cloud deployment model ► Government: Community clouds can be used by government agencies to share information and resources, such as data on crime or public health. ► Education: Community clouds can be used by schools and universities to share resources, such as course materials or research data. ► Healthcare: Community clouds can be used by healthcare organizations to share patient records or medical research data. ► Financial services: Community clouds can be used by financial institutions to share customer data or trading information. ► Manufacturing: Community clouds can be used by manufacturing companies to share product data or production schedules. ► Gaming communities might be considered community clouds. For instance, the PlayStation network involves many different entities coming together to engage in online gaming: Sony hosts the identity and access management (IAM) tasks for the network, a particular game company might host a set of servers that run digital rights management (DRM) functions and processing for a specific game, and individual users conduct some of their own processing and storage locally on their own PlayStations.
- 12. COMMUNITY CLOUD DEPLOYMENT MODEL ADVANTAGES ► You can establish a low-cost private cloud. ► It helps you to do collaborative work on the cloud. ► It is cost-effective, as multiple organizations or communities share the cloud. ► You can share resources, Infrastructure, etc., with multiple organizations. ► It is a suitable model for both collaboration and data sharing. ► Gives better security than the public cloud. ► It offers a collaborative space that allows clients to enhance their efficiency. DISADVANTAGES ► Here are the cons/drawbacks of the Community Cloud Deployment Model: ► Because of its restricted bandwidth and storage capacity, community resources often pose challenges. ► It is not a very popular and widely adopted cloud computing model. ► Security and segmentation are challenging to maintain.
- 13. MULTI-CLOUD DEPLOYMENT MODEL ► A cloud deployment model essentially defines where the infrastructure for your deployment resides and determines who has ownership and control over that infrastructure. ► The multi-cloud deployment model usually refers to the use of multiple public cloud providers to increase flexibility and fault tolerance, such as the use of Microsoft Azure, Amazon AWS, and Google Cloud. Private cloud can also be thrown into the mix to give extra reliability and flexibility ► Some services may be preferred on a certain cloud over another after evaluation by the business. ► Multi-cloud is also commonly used by businesses with critical workloads, such as government agencies or financial corporations ADVANTAGES ∙ Very high reliability ∙ Very high flexibility DISADVANTAGES ∙ Increased management complexity ∙ Increased staffing skills required
- 14. CLOUD BURSTING DEPLOYMENT MODEL It comes into practice when there is a peak in IT demand and a configuration in cloud computing where the private and public clouds deal together to deliver uninterrupted service. When the private cloud reaches its resource capacity limit, then in order to maintain uninterrupted services for the users, the private cloud redirects the overflow traffic to the public cloud. Thus, as per this configuration, the private cloud “bursts” into the public cloud when triggered with the high demand usage or a user makes a manual request. Once the situation is under control and less traffic is received, all the data is shifted to the primary private cloud.
- 16. CLOUD BURSTING DEPLOYMENT MODEL Benefits ► Cost. An organization only pays for extra compute resources when needed. Likewise, private cloud infrastructure costs can be kept low by maintaining only minimal resources. ► Flexibility. Cloud bursting can quickly adjust to cloud capacity needs. It also frees up private cloud resources. ► Business continuity. An application can burst over into the public cloud without interrupting its users. ► Peaks in traffic. If an organization is expecting a sudden increase in traffic, like during a holiday, cloud bursting can be used to facilitate any expected or unexpected peaks in compute resource demands. Challenges ► Security. If a public cloud is attacked, then an adjacent organization's data can be at risk. ► Data protection. It may be difficult to keep backups consistent when they are fed from multiple sources. ► Networking. Organizations may find it difficult to build low-latency and high-bandwidth redundant connections between public and private clouds. ► Incompatibility between the different environments and the limited availability of management tools.
- 17. VIRTUAL PRIVATE CLOUD(VPC) DEPLOYMENT MODEL ► It is a segregated private cloud environment that is usually facilitated and gotten within another cloud, commonly a public cloud. VPC reserves some of the public cloud’s resources for use by just one customer. A good analogy could be a restaurant environment that is packed with diners and a table has been reserved in that restaurant. This reserved table is like a virtual private cloud within the hosted (public) restaurant environment. The table can only be accessed by diners who have made a reservation.
- 18. VIRTUAL PRIVATE CLOUD(VPC) DEPLOYMENT MODEL BENEFITS OF VPC 1. Agility 2. Security 3. Hybrid clouds are easy to deploy 4. Improved performance 5. Availability 6. Satisfied customers 7. Increased resources to channel innovation DRAWBACKS OF VPC ► VPC generally costs more to operate than standard cloud hosting. ► Larger companies may not benefit as much as smaller companies from the large resources of VPC providers having many resources themselves in terms of updating and maintaining infrastructure. If they face tight data security regulations this can even be disadvantageous. ► While VPCs offer users an isolated environment in a public cloud where workloads can run, these workloads are still hosted outside their own data center. ► For highly regulated businesses with extensive compliance requirements e.g. financial or health organisations, this
- 19. VPC vs. Private cloud. • However, a virtual private cloud is basically a help given by a public cloud. • A private cloud is a solitary inhabitant cloud environment that is claimed, kept up with, and oversaw by the business. • It is commonly facilitated nearby or in an exceptional area. • You can plan a private region inside the public cloud's design utilizing the single-inhabitant thought of a virtual private cloud. • The high accessibility, adaptability, and cost- viability of the public cloud are as yet accessible to buyers while getting a charge out of higher security than commonplace multi-inhabitant public cloud choices. • There may be various ways to deal with scale a VPC and a public cloud account in unambiguous conditions. For instance, for VPCs, new capacity volumes could be open in blocks of a particular size. VPC vs. Public Cloud
- 20. EDGE COMPUTING DEPLOYMENT MODEL IN THE CLOUD ► Edge computing is the deployment of computing and storage resources at the location where data is produced. This ideally puts compute and storage at the same point as the data source at the network edge. ► It is a computing type that occurs at or near the end devices in real-time. ► The information is processed closer to the user’s site instead of a centralized data center. It only sends those requests to data centers that require more processing power. Why edge computing model? ► With the invention of cloud computing, there has been a massive increase in the amount of data generated. We can access any data from anywhere without any limitations. ► It enables us to produce more useful information without any geographical restrictions. But cloud computing is slightly slower as data needs to go to cloud servers for computations. This is where edge computing helps us. It reduces the latency of data transfer.
- 21. EDGE COMPUTING DEPLOYMENT MODEL IN THE CLOUD
- 22. COMPONENTS EDGE COMPUTING ► Edge devices: These are the devices that control data flow at the edge or boundary. They're usually ARM or x86 CPUs with at least two cores and 2GB of memory. These devices can handle computations without involving the cloud. It includes IoT sensors, computers, laptops, security cameras, and so on. ► Edge server: Servers that perform less complex computations located near to end- user are called edge servers. It is located in operation facilities like factories, stores, and hotels. It is constructed using industrial PCs. It's common to find edge servers consisting of 8 to 16 PC clusters, each having 16 or many cores, 16 or 32GB of Memory, and more than a Terabyte of storage. ► Edge gateway: It serves as an entry point to the cloud. It controls essential network function like firewall management, protocol translation, wireless connection, network termination, and so on. ► Cloud: A centralized server that does more complex computational work. It also helps in hosting the applications for edge users. It could be private or public, and it stores models like the neuron network that helps applications do their tasks.
- 23. EDGE COMPUTING DEPLOYMENT MODEL IN THE CLOUD Applications of edge computing ► Today’s edge computing is helping people in manufacturing, gaming, financial services, healthcare, retail, self-driving vehicles, the oil and gas industry, and many more. Edge computing has enabled businesses to operate at maximum capacity and more efficiently. Advantages of edge computing ► Being closer to the end-user improves response time and reduces latency. This is because data does not need to travel from user to cloud server and back. As a result, it causes a reduction in latency and improves response time. ► Data does not go to the cloud resulting in no traffic at the cloud link and most of the data analysis work also takes place at edge servers. Therefore, it provides better bandwidth availability and quick data analysis. ► It provides a more consistent user experience and improves overall performance. Most of the computations are done at edge servers, which is faster than doing the same computation in the cloud server. Therefore, users get a better and more consistent experience of the product. ► Fewer data travels to data centers providing more privacy to the users. Most of the data is located near edge devices and little data goes to cloud servers, Hackers will not find any useful data.
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