What are the best ways to design projects for cloud computing?

1. Define clear business objectives and align them with cloud strategy. 2. Choose the right cloud service and deployment models. 3. Architect for scalability and leverage microservices. 4. Prioritize security with encryption and access controls. 5. Establish robust backup and disaster recovery plans. 6. Optimize costs with monitoring and resource management. 7. Automate routine tasks using IaC and orchestration. 8. Ensure compliance and governance adherence. 9. Train your team and promote collaboration. 10. Continuously review and update your design for efficiency and innovation.

I think cloud-native applications are composed of multiple components, some IaaS, some PaaS, and some SaaS. Companies I've spoken with do well when they consider the talents and expertise of their teams in relation to the kinds of applications they'll build in the cloud. For example, for some customers, Kubernetes is too complex and they'll want to use a more opinionated and serverless solution, like Elastic Container Service (AWS) or Azure Container Apps. They might like having tight control over their database, or they might prefer a more managed solution. Balancing the application architecture against the ability of the app/dev ops teams has helped some customers be more successful in adoption of the cloud.

There are three primary cloud service models: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Each model offers varying levels of control, responsibility, and customization over cloud resources. For instance, IaaS grants you the highest level of control and flexibility but also entails greater responsibility for managing and maintaining the infrastructure. PaaS, on the other hand, provides a pre-built platform for application development and deployment, but it imposes some limitations on your choice of tools and technologies. In contrast, SaaS delivers the utmost convenience and simplicity but sacrifices control and customization over software functionality and configuration.

Policies for data backup and disaster recovery are another pivotal aspect to consider. The cloud service model you choose should include well-defined strategies for backing up your data and recovering it in case of unexpected disruptions. This ensures business continuity and minimizes downtime, safeguarding your critical information. The security measures implemented by the cloud provider should align with your organization's data protection requirements and compliance standards. Robust identity management and authorization mechanisms are equally vital, ensuring that only authorized personnel have access to sensitive data and resources within the cloud environment.

Decision is the key here when you are choosing the Right Cloud service model, pretty much below are your choices here: - Infrastructure as a Service (IaaS), - Platform as a Service (PaaS), or - Software as a Service (SaaS) This choice has to be directly dependent on the level of control and management you require. Therefore, it is imperative that you make the wise choice at this step itself :-)

It is not a well-known model, but sometimes overlooked is the community cloud. This deployment model is best if several organizations share your solutions with common concerns, such as regulatory compliance or industry-specific requirements. Consider this if you're part of a group that shares specific needs and can benefit from shared resources. A few common examples are healthcare, government, and education. I would also like to ask you to consider your IT team's expertise when deciding on a deployment model. Their experiences can be a deciding factor between a successful or struggling solution.

Always choose the reputable cloud service provider which can offer the services and implementation needs for your best suitability. Also, you need to consider the factors like: - Which location you need to have data centers located at - Key security protocols around it - Compliance requirements etc..

Service Delivery Model, Seamless Infrastructure Integration, Operational Flexibility Ease, Provisioning throughput optimization are the few critical factors to consider.

Choosing the appropriate cloud deployment model is primarily a balance between availability, security, and cost. Private clouds, leveraging dedicated resources and connections, are considered ideal for security and often chosen for data subject to strict regulatory guidelines such as healthcare and finance. Public clouds are most commonly used and are sufficient for most requirements. Security mechanisms are published by the cloud provider and configured as needed. Multi-cloud implementations are a separate discussion. 'Multi-cloud' involves implementing on multiple cloud providers simultaneous, often for disaster recovery or redundancy.

Cloud system need to be efficient and available 24x7. Need to make sure it is design to handle the maximum load and it handle maximum user capacity. Slowness will create problem, need to design such a way that control the slowness. It will help to earn the trust of the public which will increase the business.

- Always design your projects to be more scalable - Take all the advantage you can from the cloud elasticity and handle the varying workloads and traffic spike scenarios as well. - Use the correct auto-scaling to add or remove resources as required.

One question I always ponder is how to measure the success of an architecture. I tend to place significant emphasis on adaptability. Design your architecture with future business changes in mind. Consider future requirements post the initial release and assess how well your architecture decisions would hold. Finally, consider stress-testing your architecture against extreme scenarios. For example, if you have decided on a microservices architecture, consider the number of microservices your team will create before it becomes too complex to manage and maintain.

In most cases, I recommend leveraging the cloud-native services. Architects often decide to use containers or virtual machines to avoid the "vendor's lockdown". As a result, they utilize only the basic capabilities offered by the cloud and harm the project. A delivered solution should provide the expected business outcome as effectively as possible, but managing a fleet of virtual machines does not meet that requirement.

We should migrate initially for a pilot data set or application preferably with the simplest approach (lift and shift or rehost) This will help us understand the migration process better in terms of cost, risk. When we want to move over bigger items we have SOP's, checklists and know what to look for.

In a cloud migration, we need to consider legacy applications and how they will be consuming the new data, or we must update those applications and consider time and costs. In order way, we should make a replication processes

- Define clear governance objectives that align with your organization's goals. Determine the desired outcomes, such as cost control, security, compliance, and resource optimization. - Create a dedicated team responsible for implementing and maintaining the governance framework. - Choose a governance model that suits your organization's needs - Develop cloud policies and standards that outline the rules - Ensure that your cloud environment complies with relevant industry regulations - Implement cost controls to monitor & optimize cloud spending - Implement robust access controls & identity management systems. - Implement resource provisioning & scaling policies to ensure efficient resource usage

Regulations surrounding waste management are complex and vary by jurisdiction, potentially complicating the implementation of AI solutions.

- Leverage the performance optimization tools to identify and address the bottlenecks. - Create a plan to continuously monitor the performance for all your applications and infrastructure. - Optimize the API uses strategies as well as well as monitoring and logging overall.

Have a vision of optimisation (cost, performance, security, operational, reliability, sustainability) and modernisation on the horizon to take full advantage of the cloud.

More than anything, having a long term vision is the key. What is your uptime SLA, what geographies do you want to expand to, where are your customers located or expanding, whether you want a managed services or in-house experts, whether you want to build or continue to use some of the foundational services yourself or use the native services, do you foresee moving to a hybrid cloud or a public or private cloud etc are questions you need to answer upfront as much as possible. Choosing the right cloud provider, right architechture and having a long term view will save you lot of cost, time as well as market share in the future. Pivoting your cloud strategy later is not as easy as it appears.

Choose vendor’s that support & provide most featured from resiliency,security & failover point of view.Also application availability & how quickly it can bounce e back when it fails really matters when it comes to customers perspective

Prepare for agile - “agility” is not just a set of project management processes, it is a principle in action. A cloud product needs to evolve - making itself better as it does. Cloud engineering and product teams need to evolve too - making themselves more efficient as they do. This means with everything they do - they get better and leaner with time.

Avoid vendor lock in! As you design the system, think about how how you would migrate the system to an alternate cloud provider if you needed to. Failing to do so could lock you in to that vendor and leave you unable to take advantage of lower prices or newer technology that might be offered by a different vendor in the future.