Takeaways from Codecamp Conference in Cluj

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Last week, on October 27th, our team attended CodeCamp in Cluj-Napoca. While our Talent Acquisition consultants were networking and meeting some of the best software engineers from Cluj, our Java developer Tudor Pătruțiu dived deep into the conference agenda and listened to speakers from Microsoft, Xpirit, Nagarro-ATCS, etc.

In this post, we’d like to share Tudor’s takeaways from the event with a broader software engineering community.

Codecamp Cluj: Key Takeaways

1. Architectural Thinking: Mark Richards

Recommended book – Fundamentals of Software Architecture: An Engineering Approach (can be accessed here)

A: Why is architectural thinking important?

An example: full event payload vs only key based payload.

Full payload:

loose or strict contract for payload (bandwidth issue)
data integrity issues
stamp coupling

Key based payload:

better data consistency
contract management
network

B. Architecture characteristics

business stakeholder and user satisfaction management
maintainability, testability, deployability
merger and acquisitions: standards, adaptability, portability

C. Technical depth vs technical breadth

maintain what you know
focus on the stuff you know you don’t know
start expanding technical breadth (e.g., Infoq, ThoughtWorks technology radar, DZone Refcardz)
20-minute rule: to develop your career, read an articles or scout for new technologies as a first thing in the morning

D. Analyzing trade-offs

Everything in Software Architecture is a trade-off. Analyze and understand the trade-offs.

business drivers: time to market
performance vs maintainability
Tip: avoid over-evangelizing a given solution
use Publisher and Subscriber instead of queues.

2. Distributed Tracing: Ana Maria Mihalceanu, Oracle

service level objectives: proof that you meet the SLA’s
which service calls were involved, were there exceptions
X-Trace -> Zipkin -> OpenTracing-> —— Open Telemetry – data collection with OpenTelemetry: OTLP
optmize the tracing strategy: SImpleSpanProccesor, BatchSpanProcessor, JaggerUI – to view traces
add Jagger config in ConfigMap for Kubetctl
attach images

3. Service contracts profitability in automotive: Claudio Ceccotti, Nagarro-ATCS

80% of machine learning is preparing/cleaning the data

4. Compliance and EU Data Boundary in Azure: Alexandra Ciortea, Microsoft

Compliance: grouped by different dimensions in Azure: US Gov, Financial, Health etc.
Shared responsibility model: the customer remains responsible for managing and configuring security
MDC – Microsoft Defender for Clouds
other cloud providers can be connected with MDC
audit reports to offer the compliance results (e.g ISO standards) – SCC kegak transfer mechanism for personal data leaving EU
data residency and data protection

5. Evolving your service landscape: Alex Thissen, Xpirit

typical service landscape: UI -> services (orders, payments)
simplified service landscape: consumers and providers
reasons for change: more features, performance, different data in payloads,change OAuth2 to OpenIDConnect
types of change: replace, side by side, hybrid but depends on breaking and non-breaking changes
contracts: service, operations, message, data, fault
contract compatibility: non-breaking changes (almost never): new endpoints,new methods
reducing coupling and dependencies: reduce the number of contracts
partition into domains (domain driven design/DDD): orders into ordering to avoid
direct coupling
indirection of communication: publisher-subscriber with a topic
softening impact of changes: add a gateway for stabilizing contracts,protocol transition, offers shielding:
- api management
- backend for frontend
- composer or aggregator
- reverse proxy

cloud patterns for handling transient faults: – retry
- circuit breaker
- bulkhead isolation
- timeout
- fallback

implementing multiple versions:
- semantic versioning: 3.1.2-alpha1
- date-based: 18.04 -linux
- contract testing: https://pact.io

6. Designing in the world of Microservices: Venkat Subramanian, Agile Developer Inc.

What are the characteristics of good design?

SOLID
DRY
high cohesion: technology based cohesion vs domain based cohesion – loose and low coupling

What is a microservice?

system of interconnected applications
multiple units of deployment
isolated deployment
universal data model is a disaster in the making
choose distributed data model with hidden details and shared details with sufficient mapping

Distributed architecture: