Microservices Patterns, Issues, Migration Processes

Microservice migration
motivations, patterns and
antipatterns
Davide Taibi
davide.taibi@tut.fi
www.taibi.it
Davide Taibi - Colloquium Series - SPLAB ZHAW

Main Research Areas
• Cloud and Web software Engineering
• Microservices, Serverless
• Migration Processes
• Anti Patterns
• Orchestration
• Technical Debt

Software Architecture Evolution
D.Taibi, V.Lenarduzzi, C.Pahl, A.Janes. Microservices Architectural Styles: Agile or not Agile? XP 2017

Microservices Migration Processes
Goal:
Microservice Migration
• Motivations and Expected Benefits
• Processes
• Issues
21 companies interviewed
D. Taibi, Lenarduzzi, V. , and Pahl, C. , “Processes, Motivations and Issues for Migrating to Microservices
Architectures: An Empirical Investigation”, IEEE Cloud Computing Journal, vol. 4, no. 5, 2017.

Microservices - KölnMicroservices - Köln
Migration Motivation

Migration Process (1/2)

Migration Process (2/2)

Main Issues Identified
Technical Issues
• Decoupling from the monolithic system
• Database migration and data splitting
• Communication among services
• Service orchestration complexity

Effort-Related issues
• Effort estimation and overhead
• effort at least 20% higher
• Effort required for the DevOps infrastructure
• Effort required for library conversion

Other issues
• People’s minds
• ROI achieved in longer time (or never) compared to monolithic
systems

Microservices Architectural Patterns
Goal
Classify the architectural Patterns proposed in the Literature
D. Taibi, Lenarduzzi, V. , and Pahl, C. , “Architectural Patterns for Microservices: A Systematic Mapping Study”,
in 8th International Conference on Cloud Computing and Services Science, CLOSER , 2018.

Paper Selection
Searched for
(microservice* OR micro-service*) AND (architect* OR migrat* OR modern* OR
reengineer* OR re-engineer* OR refactor* OR re-factor* OR rearchitect* OR
re-architect* OR evol*)
Included
non peer-reviewed contributions if their number of citations was higher than
those of average peer-reviewed papers
Summary
65% of these papers were published at conferences
23% were accepted at workshops
only 7% of the papers were published as journal articles
nearly 5% (2 papers) are non peer-reviewed websites

Paper Selection

Pattern Categories
• Orchestration and Coordination
• Deployment strategies
• Data management / Data Storage

Shopping
Cart
Product
Catalog
Recommender
System
API
Gateway
Client-
Specific APIs
Protocol
Translation
API Gateway PatternOrchestration and Coordination

Shop. Cart
Instance 1
Service 1
REST
API
Registr
y
Client
REST
API
Registr
y
Client
REST
API
Registr
y
Client
Shop. Cart
Instance 2
Shop. Cart
Instance 3
Service
Registr
y
Register
Registry
-aware
client
Client-Side Discovery Pattern
Orchestration and Coordination

Shop. Cart
Instance 1
Service 1
Load
Balancer
REST
API
Registry
Client
REST
API
Registr
y
Client
REST
API
Registr
y
Client
Shop. Cart
Instance 2
Shop. Cart
Instance 3
Service
Registry
Load Balance
Register
Query
Request
Server-Side Discovery Pattern
Orchestration and Coordination

Advantages and Disadvantages of the Identified Patterns

Classification of Advantages and Disadvantages of the Identified Patterns

Emerging Issues
Comparison of SOA and Microservices.
• differences not thoroughly investigated.
• lack of comparisons (e.g., performance, development effort, maintenance).
Microservices Explosion.
• When qualities degrade?
Negative Results.
• In which contexts do microservices turn out to be counterproductive? Are there
anti-patterns?

DevOps
• DevOps pipeline is only partially covered by research work.
• Only few papers propose specific techniques, and apply them to
small example projects.
• Release-specific techniques have not been investigated in our
selected works.
• No empirical validation have been carried out in the selected
works.

Microservice Antipatterns
and Bad Smells FOCUS: MICROSERVICES
56 IE E E S O F T WA R E | PU BLI S H E D BY T H E I E E E CO M PU T E R S O CI E T Y 074 0 -74 5 9/18 / $ 3 3.0 0 © 2 018 I E E E
On the Definition
of Microservice
Bad Smells
Davide Taibi and Valentina Lenarduzzi, Tampere University of
Technology
// To identify microservice-specific bad
smells, researchers collected evidence of
bad practices by interviewing developers
experienced with microservice-based systems.
They then classified the bad practices into
11 microservice bad smells frequently
considered harmful by practitioners. //
MICROSERVICES ARE CURRENTLY
enjoying increasing popularity and
diffusion in industrial environments,
being adopted by several big players
such as Amazon, LinkedIn, Netflix,
and SoundCloud. Microservices are
relatively small and autonomous ser-
vices that work together, are mod-
eled around a business capability,
and have a single and clearly defined
purpose.1,2 Microservices enable
independent deployment, allowing
small teams to work on separated
and focused services by using the
most suitable technologies for their
job that can be deployed and scaled
independently.1,2 Microservices are
a newly developed architectural
style. Several patterns and platforms
such as nginx (www.nginx.org) and
Kubernetes (kubernetes.io) exist on
the market. During the migration
process, practitioners often face com-
mon problems, which are due mainly
to their lack of knowledge regarding
bad practices and patterns.3,4
In this article, we provide a cata-
log of bad smells that are specific to
systems developed using a micro-
service architectural style, together
with possible solutions to overcome
these smells. To produce this catalog,
we surveyed and interviewed 72 ex-
perienced developers over the course
of two years, focusing on bad prac-
tices they found during the develop-
ment of microservice-based systems
and on how they overcame them. We
identified a catalog of 11 microservice-
specific bad smells by applying an
open and selective coding5 proce-
dure to derive the smell catalog from
the practitioners’ answers.
The goal of this work is to help
practitioners avoid these bad prac-
tices altogether or deal with them
more efficiently when developing or
migrating monoliths to microservice-
based systems.
As with code and architectural
smells, which are patterns com-
monly considered symptoms of bad
design,1,6 we define microservice-
specific bad smells (called “micro-
service smells” hereafter) as
indicators of situations—such as un-
desired patterns, antipatterns, or bad
practices—that negatively affect
software quality attributes such as
understandability, testability, extensi-
bility, reusability, and maintainability
of the system under development.
Background
Several generic architectural-smell
detection tools and practices have
been defined in the past years.7–9
Moreover, several microservice-
specific architectural patterns have
been defined.10 However, to the best
of our knowledge, no peer-reviewed
work and, in particular, no empirical
studies have proposed bad practices,
antipatterns, or smells specifically
concerning microservices.
However, some practitioners have
started to discuss bad practices in
microservices. In his ebook Micro-
services AntiPatterns and Pitfalls,
IEEE Software May/June 2018
D. Taibi and Lenarduzzi, V. , “On the Definition of Microservice Bad
Smells”, IEEE Software , vol. 35, no. 3, 2018.

Microservices Bad Smells
Exploratory Survey (72 practitioners) [2]
11 Smells identified
• Cyclic Dependencies
• Problem of Microservices Explosion
• More than 50 connected microservices become unmanageable

Microservice Bad Smells

Migration to Microservices
and Technical Debt
L. Valentina and Davide, T. , “Microservices, Continuous Architecture, and Technical Debt Interest: An
Empirical Study”, in Euromicro/SEAA, Prague, 2018.

Case Study - RQs
RQ1: Is the TD of a monolithic system higher than the TD of the
same system developed with a microservices architectural style?
RQ2: Is the TD of a monolithic system growing with the same trend
as a microservices-based system?

Case Study - Object
One Italian Company
Document Management System
Java
Deployed on Microsoft Azure
Delivered as a web application +desktop application to
support document uploading

Case Study - Object
Monolithic system
280K lines of code
>12 years old
Expected Benefits
-Ease maintenance
-Separate each business process
-Reduce the need for synchronization between the two
development teams.

Case Study - Object
6 business process extracted into 6 MS
Two of the six microservices were deeply re-
architected after the first release
MS1: MySQL replaced by MongoDB
MS2: re-written from Java to in Python

Case Study – Results
0
2000
4000
6000
8000
10000
12000
14000
TechcnicalDebt
Microservice1 Microservice2 Microservice4 Microservice3
Mar.2017
Jan.2018
April2017
May2017
June2017
July2017
Aug.2017
Sept.2017
Oct.2017
Nov.2017
Dec.2018

Case Study Results: TD Trend
TD Trend TD Trend Predicted TD
without Migration
No Migration
Overall System TD
Monolithic System Microservice Migration

Case Study Results
The TD of the monolithic system is lower than TD after the
migration.
TD tends to be more stable and to increase slower in each
microservice compared to the whole system’s technical debt
The Total TD grows faster compared to the TD growth before the
migration.

Microservices Slicing with Process Mining
Can we use process mining techniques to support slicing?
Industrial Case Study with a SME
• Legacy system developed in 2006
• Document Management System for tax accountants
• > 1000 Classes

Idea
Mining log files to identify business processes
Identify potential MS candidate
• Low coupling
• High Cohesion

5-steps process
Step 1: Process Mining
Step 2: Process Usage Ranking
Step 3: Process-driven identification of decomposition solutions
Step 4: Circular Dependencies, Cohesion, and Coupling
Step 5: Identification of decomposition alternatives

Log Files Example
ID Start Timestamp Complete
Timestamp
Activity Class Method
1 02.01.2018
12:00:00:00
02.01.2018
12:00:00:36
Create Invoice MainInvoice createInvoice()
2 02.01.2018
12:00:01:00
02.01.2018
12:00:01:39
Validate
Invoice
ValidateInvoice validate()
3 02.01.2018
12:00:01:40
02.01.2018
12:00:01:45
Save Invoice MainInvoice save()
4 02.01.2018
12:00:01:45
02.01.2018
12:00:01:55
Save Invoice DB INVOICE
5 02.01.2018
12:00:01:56
02.01.2018
12:00:02:05
Save Invoice DB ACCOUNTANT

Slicing Example
InvoiceForm.submitButtonClick
MainInvoice.createInvoice() ValidateInvoice.validate()
MainInvoice.save()
MainInvoice.sendToMinistry() SDI Webservice
(Ministry of Finance Information System)
INVOICE
ACCOUNTANT
CUSTOMER
MainInvoice.updateStatus() AmazonGlacier.storePermanently()
DBManager.read()
InvoiceForm.getInvoiceDetails()
MainInvoice.getInvoice()
DBManager.save()
DBManager
WebApp
MainInvoice
Microservice 1
Microservice 2

Microservices Adoption Framework
• How to decide if migrate to Microservices or Not?
• Which measure should be considered?
• Literature: Limited comparison between MS and Monothic systems
• Limited number of empirical studies on software qualities

MS Adoption Framework - Approach
• Systematic Mapping Study
• Metrics adopted in studies comparing MS and Monolithic systems
• Survey (52 practitioners)
• Which measures have you considered before migrating?
• Which measures were useful?
• Which measures should have been considered?
• How useful are the metrics adopted in the mapping studies?

Preliminary Results (Mapping Study)
Product related
PerformanceAvailability Maintenance
CHARACTERISTICS
(RQ2)
Meantimetorecover
Downtime
Meantimetofailure
CPUutilization
ResponseTime
Pathlength
Usageofcontainers
Impactofprogramminglanguage
#featurepermicroservice
#requestsperminute
Complexity
Testability
MEASURES
(RQ3)
Process related Cost
Developmentindependencebetweenteams
Continuousdelivery
Reusability
Personnel Infrastructure
Developmentcost
Costperhour
Costpermillionofrequests
Scalability
Waitingtime

Microservices and FaaS
Practitioners started migrate to microsercvices and FaaS
Mixed Approach (microsercvices + Functions)
Open Issues
• When and Why Extract a feature as Function or as Microservice?
• Which pattern should be adopted

Conclusion
Microservices - Cagliari 11.07.2018Microservices - Köln
26/06/2017
Microservices - Köln
26/06/2017
Migration Motivation Migration Process (1/2)
Microservices - Cagliari 11.07.2018
Microservices Architectural Patterns
Goal
Classify the architectural Patterns proposed in the Literature
D. Taibi, Lenarduzzi, V. , and Pahl, C. , “Architectural Patterns for Microservices: A Systematic Mapping Study”,
in 8th International Conference on Cloud Computing and Services Science, CLOSER , 2018.
Microservices Bad Smells
Exploratory Survey (72 practitioners) [2]
11 Architectural Smells identified
• Cyclic Dependencies
• Problem of Microservices Explosion
• More than 50 connected microservices become unmanageable
Microservices Technical Debt
8.9.201848
TD Trend TD Trend Predicted TD
without Migration
No Migration
Overall System TD
Monolithic System Microservice Migration
Process Mining Slicing
Microservice 1
Microservice 2
Microservice Adoption Framework
Microservices and FaaS
Practitioners started migrate to microsercvices and FaaS
Mixed Approach (microsercvices + Functions)
Open Issues
• When and Why Extract a feature as Function or as Microservice?
• Which pattern should be adopted

References
• D. Taibi, Lenarduzzi, V. , and Pahl, C. , “Processes, Motivations and Issues for Migrating to
Microservices Architectures: An Empirical Investigation”, IEEE Cloud Computing Journal, vol. 4, no.
5, 2017.
• D. Taibi, Lenarduzzi, V. , and Pahl, C. , “Architectural Patterns for Microservices: A Systematic
Mapping Study”, in 8th International Conference on Cloud Computing and Services Science,
CLOSER , 2018
• D. Taibi and Lenarduzzi, V. , “On the Definition of Microservice Bad Smells”, IEEE Software , vol.
35, no. 3, 2018
• P. Rosati, Fowley, F. , Pahl, C. , Taibi, D. , and Lynn, T. , “Making the Cloud work for Software
Producers: linking Architecture, Operating Cost and Revenue”, in 8th International Conference on
Cloud Computing and Services Science, 2018
• L. Valentina and Davide, T. , “Microservices, Continuous Architecture, and Technical Debt Interest:
An Empirical Study”, in Euromicro/SEAA, Prague, 2018

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