Se repasarán algunas de las tendencias en arquitectura de software actuales, para que se usan, sus ventajas, sus desventajas y su estado de madurez. Con mayor o menor frecuencia cada uno de nosotros escucha temas relacionados con BigData, con Cloud, con Microservices, con NoSQL, etc. Esta charla recorre algunos de estos temas desde una mirada de un desarrollador GeneXus, ¿qué implican estos temas para nosotros?, ¿qué estado de madurez tienen algunos de estos temas?

1. Architecture Trends
Gastón Milano
@gmilano
Gmilano@genexus.com

2. I learned very early the difference between knowing the name of something
and knowing something

3. Trends

4. #GX25
Trends

5. #GX25
if you procrastinate long enough most problems just solve
themselves
Peak of Inflated Expectations

6. #GX25
IOT
Cloud
Big Data
NewSQL
Microservices

7. Cloud

8. #GX25
IAAS (how)
PAAS (what)
CLOUD

9. #GX25
Machine Learning
Notifications
Analytics
Media
Storage
Compute
PAAS

10. #GX25
CONFIGURATION OVER IMPLEMENTATION

11. Big Data

12. #GX25

13. #GX25
Data volume
Small Big
c
o
m
p
ut
e
Big
Small OLTP + OLAP
SPECIALIZED COMPUTING

14. Content Formats (aka
DataSources)

15. NoSQL

16. Why is NoSQL faster than
SQL?

17. What NoSQL?
Graph Columns
Key/Value Document

18. Some people can’t resist
getting the next new thing
because it’s new

20. Tradeoffs: In NoSQL the DBMS is
in your code
Standard API
Transaction
Query optimization
Data navigation

21. #GX25
Why doesn’t your database
scale ?

22. #GX25
Architecture Evolution
Client/Server (same machine)
Client/Server (App Server)
Client/Server (Bigger database)
WebApps + Load Balancers + Services
Shards
Cache… at every layer

23. #GX25
NoSQL
No, SQL
NewSQL

27. SQL
ACID
Non-Locking
Scalability

28. #GX25
1 digit petabytes !!

29. #GX25
GeneXus
Key/Value: Redis, Memcached
Columns: SAP Hana
Document: Lucene / Solr
New datastores for Transactions !

30. #GX25
Classical architectures are enough today for most OLTP OLAP systems.
Relational algebra is still useful. The key is distributed parallel database implementations.
Declarative models enable optimizers. (MPP vs MapReduce)

31. Microservices

32. #GX25
Microservices vs Monolithics

34. Challenges
Data Sharing ?
Data Replication?
SOA ?
Operations ?
Deployment ?

35. Microservice solves one business use
case

37. Problems — Complexity
Data Sharing ?
Data Replication?
SOA ?
Operations ?
Deployment ?

38. GeneXus Microservices

39. #GX25
Cloud
NewSQL
BigData
Microservices
IOT

40. The first principle is that you must not fool yourself and you are the
easiest person to fool

41. #GX24
Thank you!