Right-sizing your application services: Rethinking microservices (ARC324)

Here's a detailed summary of the key takeaways from the video transcription:

Rethinking Microservice Sizing

Avoid the "Shiny Object Syndrome"

  • The industry has seen a trend of organizations trying to maximize the number of microservices, viewing it as an indicator of quality.
  • However, the number of microservices alone does not necessarily reflect the value being delivered.

Consider the Context

  • Decomposing a system into microservices should not be done in isolation; it needs to consider the specific context of the organization, such as team skills, business problems, operational profiles, and workload nature.
  • Blindly adopting a "one-size-fits-all" approach to microservices can lead to over-complexity and lack of value.

Focus on the Right Sizing

  • Microservice sizing should not be driven by the notion that "smaller is always better." The appropriate size depends on factors like:
    • Operational complexity
    • Resilience profile
    • Consumption patterns and bottlenecks
    • Business pressures
    • Release frequency
    • Team profiles

Evaluate the Return on Complexity

  • When decomposing a system into microservices, consider the trade-off between the benefits (e.g., agility, scalability) and the increased complexity (e.g., operational overhead, troubleshooting challenges).
  • Aim to find the right balance that maximizes the return on complexity for the organization.

Adopt a Value-Driven Approach

  • Map out a "Value Map" to visualize where different services should be placed based on factors like business criticality, throughput, and change frequency.
  • Use this map to guide the sizing and decomposition of microservices, focusing on the areas that will deliver the most value.

Expect Continuous Evolution

  • Microservice decomposition should be viewed as an ongoing, iterative process, not a one-time event.
  • Continuously collect data and insights from the running system to inform the right sizing and evolution of the microservice architecture.

Leverage Contextual Data

  • Gather and analyze data on factors like performance, scaling, fault tolerance, and operational complexity to assess the effectiveness of the microservice sizing.
  • Involve both architectural and operational teams in this data-driven approach to ensure the microservice decomposition aligns with the broader organizational needs.

By adopting a more contextual and value-driven approach to microservice sizing, organizations can avoid the pitfalls of the "shiny object syndrome" and build microservice architectures that truly deliver the desired benefits.

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