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How do you break a Monolith into Microservices at Scale? This ebook shows strategies and techniques for building scalable and resilient microservices.
- We have identified a problem. It can be with almost anything: scalability, reliability, auditability, any Quality Measure.
- We're pursuing a specific technology. Typically, something that has the lowest impact on our architecture.
- We can't address anything other than this specific technology variation -- we can't change the application software or buy hardware.
Once we're in the Faerie Dust realm, what can we do?
- Pick a data model that doesn't fit the use cases. i.e., lumped many discrete details into a single text field that has "rich semantic content". Work around this mistake by using wild-card matches.
- Complained about performance and dug into nuanced details of LIKE clause and full-text search. Lots of study time spent on LIKE clause processing and how to improvement performance.
- Refused to discuss the actual use case or the mismatch between data structures and requirements.
The design didn't match the use cases. Faerie Dust won't help.
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