Define a capacity model according to the business requirements

• Test the limits for predicted and random spikes and fluctuations in load

Monitor the health of the entire solution

Control the consumption of resources used by an instance of an application, an individual tenant, or an entire service.

Divide a data store into a set of horizontal partitions or shards.

Use a queue that acts as a buffer between a task and a service that it invokes in order to smooth intermittent heavy loads.

Prioritize requests sent to services so that requests with a higher priority are received and processed more quickly than those with a lower priority.

Generate prepopulated views over the data in one or more data stores when the data isn't ideally formatted for required query operations.

Create indexes over the fields in data stores that are frequently referenced by queries.

Use an append-only store to record the full series of events that describe actions taken on data in a domain.

Segregate operations that read data from operations that update data by using separate interfaces

Have each component of the system participate in the decision-making process about the workflow of a business transaction, instead of relying on a central point of control.

Prefer async inter-service communication, such as message or event

Plan security readiness
Strive to adopt and implement security practices in architectural design decisions and operations with minimal friction.

Design to protect confidentiality
Prevent exposure to privacy, regulatory, application, and proprietary information through access restrictions and obfuscation techniques.

Design to protect integrity
Prevent corruption of design, implementation, operations, and data to avoid disruptions that can stop the system from delivering its intended utility or cause it to operate outside the prescribed limits. The system should provide information assurance throughout the workload lifecycle.

Design to protect avalability
Prevent or minimize system and workload downtime and degradation in the event of a security incident by using strong security controls. You must maintain data integrity during the incident and after the system recovers.

Sustain and evolve your security posture
Incorporate continuous improvement and apply vigilance to stay ahead of attackers who are continuously evolving their attack strategies.

Establish a security baseline that's aligned to compliance requirements, industry standards, and platform recommendations. Regularly measure your workload architecture and operations against the baseline to sustain or improve your security posture over time.

Maintain a secure development lifecycle by using a hardened, mostly automated, and auditable software supply chain. Incorporate a secure design by using threat modeling to safeguard against security-defeating implementations.

Classify and consistently apply sensitivity and information type labels on all workload data and systems involved in data processing

Create intentional segmentation and perimeters in your architecture design and in the workload's footprint on the platform. The segmentation strategy must include networks, roles and responsibilities, workload identities, and resource organization.

Implement strict, conditional, and auditable identity and access management (IAM) across all workload users, team members, and system components.

Isolate, filter, and control network traffic across both ingress and egress flows.

Encrypt data by using modern, industry-standard methods to guard confidentiality and integrity.

Protect application secrets by hardening their storage and restricting access and manipulation and by auditing those actions.

Implement a holistic monitoring strategy that relies on modern threat detection mechanisms

Establish a comprehensive testing regimen that combines approaches to prevent security issues, validate threat prevention implementations, and test threat detection mechanisms.

Define and test effective incident response procedures