In microservices migration, why does moving components gradually reduce risk compared to a big-bang migration?
Think about how small changes help catch problems early.
Gradual migration lets teams test each part separately, so problems can be fixed before they affect the whole system. This reduces risk.
Which architectural pattern best supports gradual migration in microservices?
Think about a pattern that lets you replace parts slowly.
The Strangler Fig Pattern allows gradual replacement of legacy parts with new microservices, reducing risk during migration.
During gradual migration to microservices, how does the approach impact system scalability?
Consider how microservices can be scaled separately.
Gradual migration enables scaling of new microservices independently, which improves resource use and system scalability.
What is a common tradeoff when choosing gradual migration over a big-bang approach?
Think about how doing things step-by-step affects time.
Gradual migration reduces risk but usually takes longer because changes happen in small steps.
A legacy monolith requires 4 hours downtime for a big-bang migration. If a gradual migration splits the system into 8 microservices migrated one by one, each requiring 15 minutes downtime, what is the total downtime?
Multiply the number of services by downtime per service.
8 services × 15 minutes = 120 minutes = 2 hours total downtime, which is less than 4 hours.