A private cloud deployment model allows a company to maintain strict control over its data while still leveraging cloud infrastructure. In a private cloud, the resources are dedicated to a single organization, which can ensure enhanced security and compliance with data governance policies.
This is ideal for managing confidential data, as the company retains full control over its infrastructure, without sharing resources with other organizations, as would be the case in a public cloud.

Spot instances are typically less expensive than reserved instances but can be interrupted by the cloud provider when there is higher demand for resources. To ensure that workloads using spot instances remain resilient, they should be designed with checkpoints to save progress at regular intervals. This way, if the spot instance is interrupted, the workload can resume from the last checkpoint, minimizing the impact of the interruption.

A disaster recovery strategy is a plan that defines how an organization can recover its data, systems, and operations in the event of a disaster, such as a natural calamity, a cyberattack, or a human error. A disaster recovery strategy should include the following elements:
Backups: Backups are copies of data and files that are stored in a separate location from the original source. Backups help to restore the data in case of loss, corruption, or deletion. Backups can be performed manually or automatically, and can be stored on-premises, off-site, or in the cloud. Backups should be encrypted, secured, and tested regularly to ensure their integrity and availability.
Replication: Replication is the process of copying and synchronizing data and systems across multiple locations or platforms. Replication helps to maintain the consistency and availability of the data and systems in case of a failure or outage. Replication can be done at different levels, such as storage, database, application, or virtual machine. Replication can be synchronous or asynchronous, depending on the latency and bandwidth requirements.
Geo-redundancy: Geo-redundancy is a feature that allows the distribution and replication of data and systems across multiple geographic regions or zones. Geo-redundancy helps to ensure the resiliency and continuity of the data and systems in case of a regional disaster or disruption. Geo- redundancy can also improve the performance and latency of the data and systems by serving the requests from the nearest location. Geo-redundancy can be achieved by using cloud services that offer multi-region or multi-zone capabilities.

Baseline refers to the collection of data about the current state of infrastructure performance, which is what the company is logging. By gathering performance data, the company establishes a baseline that can be used to measure improvements, compare the performance of the new cloud environment, or identify areas of concern. This baseline data will provide a reference point for assessing the impact of migration to the cloud and ensuring that performance expectations are met.