The monolith vs. microservices debate has been characterized as a modern vs. legacy issue. A more accurate assessment would be that failures lie not with the monolith versus microservices architecture but with a mismatch of expectations, readiness, and misunderstandings of trade-offs. Teams don’t make the wrong decisions; teams make decisions because the wrong reasons.
1. Architecture vs. Strategy Mistakes
One of the biggest pitfalls is treating micro-services as an entrepreneurial strategy and not from the perspective of addressing technical restrictions.
Microservices don’t inherently:
- Encourage faster movement
- Enhance Scalability
- Improve reliability
They offer these results only if certain conditions already exist. Some examples of such conditions include “autonomous teams and established DevOps adoption.”
Often, many teams might begin to adopt microservices because they believe the adoption can solve the organizational woes of slow deployment, lack of clarity on ownership, or the inability to scale. However, the strength or weakness that the organizational model has will be amplified or reinforced rather than changed or adjusted.
What gets missed: Architecture must track business structure and domain complexity, not the industry.
2. Monolithic Underestimation
Monoliths are often classified as “legacy” or “not scalable,” which is a misnomer.
- A well-structured monolith can:
- Scale horizontally
- Large user bases can be supported.
- The same principle enables rapid iteration.
- Be easier to test and debug
The real problem is not monoliths-it’s poorly designed monoliths: tightly coupled code, no module boundaries, and unclear ownership.
Ironically, many microservices systems wind up reimplementing a distributed monolith, wherein the services are interdependent to such an extent that nobody dares deploy or independently change them.
What’s missed: A modular monolith is generally the least complicated and most effective starting point.
3. Inattention to Organizational Readiness
Microservices are not solely a matter of technical architecture; they are an organizational architecture.
They take for granted that:
- Self managing teams
- Well-defined service ownership
- Strong DevOps and SRE practices
- Mature monitoring and incident response
- High tolerance for operational complexity
Teams that have these things in place often struggle less after their move to microservices than they did before.
Common symptoms include:
- Cascading failure events causing frequent power outages
- Confusing on-call rotations
- Blame shifting between the teams
- Slow debugging across service boundaries
What gets missed: Conway’s Law – the system reflects the communications structure, and if the development teams are not autonomous, the services cannot be either.
4. Overlooking the Cost of Microservices
Microservices add several costs that can be considered implicit or hidden, which in many ways may be underestimated
- Network latency and failure modes
- Observability toolkit based on distributed tracing
- API Versioning & Backwards Compatibility
- Data Consistency Challenges
Costs such as these do not appear immediately when the system is first implemented; they build up with time as the system expands.
The cost can far exceed the benefit for many years for smaller to mid-size systems.
What gets missed: While microservices add development complexity, operation complexity is even more challenging to rollback.
5. Thinking Microservices Equal Independent Deployment
One of the major benefits offered by microservices is the principle of independent deployment, although most teams still fail to meet this requirement.
Why?
- Loose synchronous coupling
- Lack of Clearly Defined Service Boundaries
- Cross-service transactions
- Talking APIs
When interdependent services need to be delivered simultaneously, otherwise the system will break down, the benefit no longer applies – though the added complexity still does!
What gets missed: True independence needs robust domain boundaries in addition to repository independence.
6. Premature Breaking-Up of Systems
Another mistake widely made is when an application breaks down into microservices without an understanding of the domain.
Early in the product’s lifecycle:
- Requirements evolve very quickly
- Domain Boundaries are not clear
- The rate of iteration is of far greater importance than the size of the
- Premature service extraction freezes the assumptions which will inevitably prove to be false.
What gets missed: Architecture needs to develop with growing knowledge. The initial confidence can be false.
7. Treating the Decision as Binary
This is often equated as a choice between a monolith and using microservices. For an ideal system, a hybrid model is often adopted.
Common effective patterns:
- Begin with the modular monolith
- Maintain separate high-change domains
- Accept heterogeneity where required.
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Conclusion
Typically, teams are not using either monoliths or microservices due to flaws with the technology; they themselves are misguided in the motivations for making that technology choice.
Monoliths do not succeed when the aspects of structure and discipline are disregarded.
