CONSULTING

Consulting services : de-risk and accelerate your Data-driven Enterprise Architecture initiative

In addition to the training classes and online learning resources we offer a variety of consulting services. There are four main consulting offerings:

  • Enterprise Data-driven EA adoption
  • Data-driven EA migration
  • Data-driven Enterprise Architecture review
  • Remote office hours

Enterprise Data-driven Enterprise Architecture Adoption

Through a combination of consulting and training, we work with you to enable your organization to successfully adopt the Data-driven Enterprise Architecture.

We will train:

  • leaders – understand the essentials of the Data-driven Enterprise Architecture, why it matters and what needs to be done to ensure success
  • architects – how to define a Data-driven Enterprise Architecture, refactor a monolith to services and define the technical architecture
  • developers – how to implement services

Through consulting, we will:

  • Help you create a Data-driven Enterprise Architecture adoption roadmap
  • Assess and improve your Data-driven Enterprise Architecture process
  • Help you select applications to migrate to the Data-driven Enterprise Architecture
  • Work with you to define the target architecture for each application and the associated technical architecture
  • Help developers refactor a monolith to services
  • Periodically review your progress and give advice

You will learn how to avoid various adoption anti-patterns including:

  • ..

Data-driven Enterprise Architecture Migration

Through a combination of consulting and training, we work with you to develop the skills and the strategy for incrementally refactoring your monolithic application to a microservice-based architecture. During the engagement we work with you to define the initial microservice architecture and teach you what you need to know in order to to successfully migrate to a microservice architecture.

An engagement typically consists of the following steps:

  • Engagement kickoff:
    • Discuss key metrics:
      • Development: lead time, deployment frequency, …
      • Operational: change failure rate, availability, mean time to recover, …
    • Conduct retrospective: what’s working well, what needs to be improved
    • Review how to document architecture
  • Review requirements
    • Understand the domain, for example, by using event storming
    • Identify architecturally significant stories/scenarios including those that are complex, latency/availability sensitive, etc.
  • Review AS-IS monolithic application architecture:
    • Key elements of the architecture
    • Technical architecture
    • How architecturally significant stories/scenarios flow through the architecture
  • Review development and delivery organization’s structure
  • Review development and delivery practices including
    • Code quality
    • The flow from development to production including automated deployment pipeline
    • Automated testing strategy
  • Identify training needs and deliver training, such as:
    • architecture design principles
    • Strategies for refactoring a monolith to EA
  • Brainstorm TO-BE:
    • Perform build-vs-buy analysis to identify system components that use
    • Service decomposition, define responsibilities, APIs, and collaborations
    • Technical architecture to support services including: inter-process communication mechanisms, deployment infrastructure, etc.
    • Development and delivery organization’s structure
    • Development and delivery practices
  • Create plan for refactoring monolith to Data-driven EA based on effort/impact

Estimated duration: n-n days in-person or remote equivalent

After the initial engagement, we periodically provide any needed technical review and guidance.


Data-Driven Enterprise Architecture Review

The goal of this review is to assess your current Enterprise architecture, and recommend ways to improve it. We also include training to address any gap in skills.

An engagement typically consists of the following steps:

  • Engagement kickoff:
    • Discuss key metrics:
      • Development: lead time, deployment frequency, …
      • Operational: change failure rate, availability, mean time to recover, …
    • Conduct retrospective: what’s working well, what needs to be improved
    • Review how to document architecture
  • Review requirements
    • Understand the domain, for example, by using event storming
    • Identify architecturally significant stories/scenarios including those that are complex, latency/availability sensitive, etc.
  • Review AS-IS Enterprise Architecture:
    • Key elements of the architecture including services, and their APIs
    • Service granularity and service to/from team mapping
    • How services collaborate to implement architecturally significant stories/scenarios
    • Technical architecture including deployment and monitoring architecture
  • Review development and delivery organization’s structure
  • Review development practices including
    • Code quality
    • The flow from development to production including automated deployment pipeline
    • Automated testing strategy
  • Identify training needs and deliver training, such as:
    • Data-driven Enterprise Architecture design principles
  • Identify areas that need improvement and make recommendations:
    • TO-BE Service architecture
    • TO-BE Technical architecture
  •  
    • Deployment pipeline
    • Development and delivery organization’s structure
    • Development practices including automated testing
  • Review and prioritize recommendations by effort/impact

Estimated duration: 5-7 days in-person or remote equivalent

After the initial engagement, we periodically provide any needed technical review and guidance.


Remote Office Hours

Got a specific Data-driven Enterprise Architecture-related question? Book time with Steve Force.