Software Infrastructure Design, Integration, & Migration Roadmap

Infrastructure
Design, Integration,
& Migration
A complex framework simplified
Innovate Vancouver

System Integration
System integration is defined in engineering as the process of
bringing together the component sub-systems into one system (an
aggregation of subsystems cooperating so that the system is able to
deliver the overarching functionality) and ensuring that the
subsystems function together as a system,[1] and in information
technology[2] as the process of linking together different computing
systems and software applications physically or functionally,[3] to act
as a coordinated whole.
- https://en.wikipedia.org/wiki/System_integration

INTEGRATION BUSINESS CASE
This includes the
following components:
Hardware
Software
Technology
Examples include the following
technologies and tools:
Application Programming Interface API's
Infrastructure Platform as a Service
Enterprise Service Bus
Data Sources include the following
examples:
SQL Database
Point of Service POS Data
Inventory
Financials & Payments
Purchase Records
What Needs
Integrating?
What Integration Tool Does
the Business Need?
Which Type of Data
Requires Integration?
Benefits include the following
examples:
Merging Disparate Systems
Increasing Functionality
4Migrating from Legacy Systems to
Modern Apps
Increasing Data Driven Insights
Benefits of
Integrating
https://anyconnector.com/en/software-integration.html

INTEGRATION
MATURITY
ASSESSMENT
Architecture
Ownership
Development
Management Ops
Consumption Model
Infrastructure
Runtime
Security Model
AI Augmentation
IBM recommends using the
following checklist to evaluate your
company's integration maturity
readiness, as well as the maturity
level of your IoT Architecture:
1.
2.
3.
4.
5.
6.
7.
8.
9.
https://www.ibm.com/cloud/architecture/assessments/modern-integration

TYPES OF INTEGRATION Several Integration Architectures are often used to
design and manage the follow of cross-system data
exchange. Examples include the following
architectures:
1. Star Integration
2. Horizontal Integration
3. Vertical Integration
4. Common Data Format Integration
Each has their strengths and weaknesses, and are
suited for different company configurations and
structures.
https://anyconnector.com/en/software-integration.html

Principles of Cloud
Native Architecture
Design
The following principles can be used as a architecture
design scorecard for evaluating the following KPI's:
Principle 1: Operational Excellence Pillar
Principle 2: Security Pillar
Principle 3: Reliability Pillar
Principle 4: Performance Efficiency Pillar
Principle 5: Cost Optimization PIllar
https://aws.amazon.com/architecture/well-architected/?wa-lens-whitepapers.sort-by=item.additionalFields.sortDate&wa-lens-whitepapers.sort-order=desc

Software Integration Process
The following describes a generic high-level design and planning
roadmap for software integration and delivery:
1. Collect Definitions, Requirements, and Specifications
2. Analyze the Information
3. Develop Architecture and Management Plans
4. Create the Software Integration System
5. Begin Using the Integration System
6. Evaluate System Performance Periodically

INTEGRATORS
There are many types of physical and digital integrators. The type
selected will often depend on software, the type of data objects, IT
infrastructure, business requirements, use cases, and
communication protocols supported.
A few examples of integrators include the following:
Microservices
Application Programming Interface (API)
Enterprise Service Bus
Integration Platform as a Service (iPaaS)
WebHooks
Integrated Service Component (ISC)
Orchestrations
https://blog.vivantio.com/4-types-of-integration-methods-with-your-it-service-management-software

TYPES OF DATA
INTEGRATION
Data Lake
Data Hub
Data Virtualization/ Federation
Data Warehouse
Operational Data Store
The following models for data integration are evaluated and
selected based on the type and location of data prioritized for
migration and/or integration:
1.
2.
3.
4.
5.

Types of Migration
Rehosting Workloads
Replatforming Workloads
Adopting SaaS, IaaS, etc.
Refactoring Workloads
Retiring Workloads
Infrastructure design also includes consideration of where the
applications and data will be stored, if migration is required, risks, and
cost-benefit analysis of existing options.
Migration takes into consideration whether an existing application
should be retained or replaced with a new option, with possibly more
features. It also takes into consideration subscription fees, export
pathways, conversion risks and compatibility, data storage, and
retrieval costs, and maintenance requirements.
Migration to the cloud includes the following approaches:
1.
2.
3.
4.
5.

DATA MIGRATION PROCESS
Step 1 — refine the scope
Step 2 — assess source and target
systems.
Step 3 — set data standards.
Step 4 — estimate budget and set
realistic timelines
PLANNING
Unlike migration dealing with the company’s internal information,
integration is about combining data from multiple sources outside and
inside the company into a single view. It is an essential element of the data
management strategy that enables connectivity between systems and
gives access to the content across a wide array of subjects. Consolidated
datasets are a prerequisite for accurate analysis, extracting business
insights, and reporting.
Data migration is a one-way journey that ends once all the information is
transported to a target location. Integration, by contrast, can be a
continuous process, that involves streaming real-time data and sharing
information across systems.
planning,
data auditing and profiling,
data backup,
migration design,
execution,
testing, and
post-migration audit
DATA MIGRATION PROCESS

MIGRATION PLANNING
Application Inventory:
1. Identify All Applications
2. Determine the Application Owners
3. Document Application Versions, Requirements, and Dependencies
4. Establish whether or not an Application is Still Used
Prioritization:
1. Figure Out which Applications Should be Migrated First: Necessity,
Benefit, Ease of Migration
Plan:
1. Migrate in Batches or Individually
2. Which Migration Method will be Used
3. What Order of Steps Need to be Performed
4. What Tools are Required in Order to Complete the Migration Process
5. Do you have the Required Cloud Subscription Information Needed
6. Time Frame of the Migration: Critical Path & Dependencies (Testing,
Pilot, Availability, etc.)
7. Contingency Plan for the Migration (risk mitigation)
Source: https://www.linkedin.com/learning/design-a-cloud-migration-strategy/building-a-plan-of-attack?u=109339402

MANAGING THE
INTEGRATION PROCESS
Backlog Grooming
Sprint Planning.
Daily Scrum.
Sprint Review.
Sprint Retrospective.
Software development and configuration projects often use what is
referred to as an Agile Scrum framework. This includes two-week
sprints and the scrum ceremonies mentioned on the right.
Agile Scrum is the planning and delivery framework of choice for
most software projects because it supports iterative planning,
ongoing stakeholder and team consultation and engagement,
requirements validation, incremental delivery, with an emphasis on
quality and cost controls.

DATA
GOVERNANCE
Data Governance Models
1. De-centralized Execution – Single Business Unit
2. De-Centralized Execution – Multiple Business Units
3. Centralized Governance – Single or Multiple
Business Units
4. Centralized Data Governance & Decentralized
Execution
Data Governance Planning Process
1. Establish Data Governance Organization
2. Identify Strategic Master Data Objects
3. Allocate Ownership
4. Identify Master Data Maintenance Rules
5. Establish Master Data Maintenance
Procedures
6. Establish Tools for Master Data
Maintenance
7. Establish Rules and Jobs for Master Data
Archiving
https://nttdata-solutions.com/us/local-blog/grc-and-security-local-blog/inside-data-governance-part-1-an-introduction/
https://nttdata-solutions.com/us/local-blog/grc-and-security-local-blog/data-governance-models-%e2%94%82four-models-and-how-to-choose-which-is-best-for-your-organization/
https://nttdata-solutions.com/us/local-blog/grc-and-security-local-blog/inside-data-governance-part-3-the-7-steps-to-steer-you-towards-an-effective-data-governance-plan/
Maintaining the data involves a lot of work. Ignoring this component of
data migration and integration will result in duplication, faulty reporting,
low-quality analytics, and can impact product design and development,
inventory management, customer relationship management, and
more.......
This is why data governance is so important. The following sections
depict common data governance models and the planning process.

Designing for the
Business Model
Information Technology Architecture needs to be designed to fit the
needs and requirements of the business, customers, and external
stakeholders. It needs to drive scalable, efficient, and effective
insights, processes, and systems. It needs to provide a return on
investment, particularly because it involves so much effort to
design, install, implement, and maintain.
Many frameworks are available to further help design a model that
systems the business ecosystem. Take a look at the Business
Model Canvas, Enterprise Architecture Development Model, or the
Information Technology Infrastructure Library to support service
management, asset management, and integration of business
systems.

Software Infrastructure Design, Integration, & Migration Roadmap

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Software Infrastructure Design, Integration, & Migration Roadmap