Public clouds
provide an adoption framework for businesses that helps to create an overall
cloud adoption plan that guides programs and teams in their digital
transformation. The plan methodology provides templates to create backlogs and
plans to build necessary skills across the teams. It helps rationalize the data
estate, prioritize the technical efforts, and identify the data workloads. It’s
important to adhere to a set of architectural principles which help guide
development and optimization of the workloads. A well-architected framework stands
on five pillars of architectural excellence which include:
- Reliability
- Security
- Cost Optimization
- Operational Excellence
- Performance efficiency
The elements
that support these pillars are a review, a cost and optimization advisor,
documentation, patterns-support-and-service offers, reference architectures and
design principles.
This guidance
provides a summary of how these principles apply to the management of the data
workloads.
Cost optimization is one of the primary benefits of using the right tool for
the right solution. It helps to analyze the spend over time as well as the
effects of scale out and scale up. An advisor can help improve reusability,
on-demand scaling, reduced data duplication, among many others.
Performance is
usually based on external factors and is very close to customer satisfaction.
Continuous telemetry and reactiveness are essential to tuned up performance.
The shared environment controls for management and monitoring create alerts,
dashboards, and notifications specific to the performance of the workload.
Performance considerations include storage and compute abstractions, dynamic
scaling, partitioning, storage pruning, enhanced drivers, and multilayer cache.
Operational
excellence comes with security and reliability. Security and data management
must be built right into the system at layers for every application and
workload. The data management and analytics scenario focus on establishing a
foundation for security. Although workload specific solutions might be required,
the foundation for security is built with the Azure landing zones and managed
independently from the workload. Confidentiality and integrity of data
including privilege management, data privacy and appropriate controls must be
ensured. Network isolation and end-to-end encryption must be implemented. SSO,
MFA, conditional access and managed service identities are involved to secure
authentication. Separation of concerns between azure control plane and data
plane as well as RBAC access control must be used.
The key
considerations for reliability are how to detect change and how quickly the
operations can be resumed. The existing environment should also include
auditing, monitoring, alerting and a notification framework.
In addition to
all the above, some consideration may be given to improving individual service
level agreements, redundancy of workload specific architecture, and processes
for monitoring and notification beyond what is provided by the cloud operations
teams.
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