As a language, Java remains a major player in enterprise applications, but new emerging trends around Java in recent years have been rather interesting because these trends no longer surround Java's core features. In addition, there have been interesting developments and overall movement towards cloud hybridization. In this session, we will review the new features in Java 8 in respect to performance monitoring. Then, we will deep-dive into new emerging trends surrounding Java enterprise applications, such as micro-service refactoring, cloud hybridization, and emerging frameworks/JVM-based languages and how you can leverage AppDynamics in order to gain further visibility into your application stack. Key Takeaways: -New Java 8 Developments -AppDynamics on Hybrid Cloud -Java 8 Memory Management -JVM-based languages and AppDynamics -Microservices Architecture and AppDynamics This session was originally presented at AppSphere 2015.

1. What’s New in Java. Leveraging Java in
Hybrid Cloud
Val Chibisov, Senior Product Manager

2. Agenda
1. What’s new in Java? Java 8 – Memory Model
2. JVM-based Languages
3. Hybrid Cloud
4. Microservice Refactoring
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3. JAVA 8 – MEMORY MODEL

4. Java 7 – Recap – Java Memory Model
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Eden Survivor Survivor
Old Gen
Perm Gen
Heap
-Xmx
Native
Memory

5. Java 8 – Recap – Java Memory Model
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Eden Survivor Survivor
Old Gen
Heap
-Xmx
Native
Memory
Metaspace

6. Java 8 – PermGen Issues
• PermGen necessary size is hard to predict
– Results in either under-provisioning or over-provisioning
• GC performance improvements
• Support for advanced optimizations
– G1 concurrent class unloading
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7. Java 8 – Metaspace Changes
• PermGen
– Memory space is gone
• Metaspace memory allocation model
– Most class metadata is now allocated out of native memory
– No more classes which are used to describe class metadata
• Metaspace capacity
– Out of the box available allocation space is limited by the amount of available native
memory
– Dynamically resizes depending on the allocation demand at runtime
– Possible to use a flag (-XX:MaxMetaspaceSize=Y) in order to limit the amount of
native memory used for class metadata
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8. Java 8 – Metaspace Changes Ctd
• Metaspace garbage collection
– Garbage collection is triggered once the class metadata usage reaches the MaxMetaspaceSize
– Excessive Metaspace GCs may point to:
• Memory leaks of classes
• Memory leaks of classloaders
• Improper allocation sizing
– Metaspace tuning and monitoring is highly important to limit the frequency/delay of these GCs
• Java heap space impact
– There may be some increase of Java heap due to various data being moved to Java heap space
• Metaspace monitoring
– Hotspot 1.8 GC logs provide Metaspace usage
– AppDynamics!
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9. Java 8 – Metaspace – Magic Bullet?
• Magic Bullet?
– Not quite
– Memory caveats still remain
• Requires proper monitoring and proactive remediation
– Class metadata memory footprint
– Class memory leaks
– Class loader memory leaks
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10. AppDynamics – Passive Metaspace Monitoring
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11. AppDynamics – Proactive Metaspace Monitoring
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12. JVM-BASED LANGUAGES &
APPDYNAMICS

13. Scala
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• JVM-based flexible programming language
• Rising in popularity due to its extremely flexible functional-object-
oriented approach and Java interoperability

14. Groovy
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• Dynamic JVM-based object-oriented programming language
• Best trait: simplicity, dynamic language
• Superset of Java – easier to adopt

15. JRuby
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• JVM-based programming language
• Full access to Java toolchain
• Real system threads

16. JVM-based Language Stack Monitoring
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• AppDynamics enables deep monitoring and troubleshooting of JVM-
based languages!
• Proactive alerts
• Distributed cross-stack environment monitoring!

17. HYBRID CLOUD & APPDYNAMICS

18. Public Cloud
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• Mutlitenant environment
• You own a slice of a server in a cloud environment shared by other
clients
• Generally used for web servers or dev systems
Public

19. Public Cloud – Trade-Offs
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• Hardware Sharing
– Meeting compliance requirements is near to impossible in a public cloud
• Scalability
– On-demand resource availability
• Location independence
– Use computing resources local to clients/users Public

20. Private Cloud
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• “Single-tenant” environment dedicated to a single entity such as a
client or company
• Expanding on traditional enterprise datacenters
Private

21. Private Cloud – Trade-Offs
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• Security
– Cloud is scoped for a single entity
– Only such entity has access to the information in the private cloud
– Achieving compliance is much easier
Private
• Resource Management
– Manual management of computing resources
including: purchasing, housing, updating and
maintaining
• Direct Control

22. Hybrid Cloud
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• Combination of a Public Cloud Provider & Private Cloud Platform
• Huge surge in the adoption in the recent years
Hybrid
Private Public

23. Hybrid Cloud
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• Allows storage and processing of privileged data and applications in
private cloud
• Enables the use of vast computational resources of the public cloud
that relies on the sensitive data from private cloud
• Unique benefits of “Cloud Bursting”
Hybrid
Private Public

24. Monitoring Hybrid Cloud
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• Monitoring of complex Hybrid Cloud set-ups is far from straightforward
• Requires a solution that can trace distributed execution from private to
public cloud and vice versa
• Identification of the root-cause becomes extremely problematic
Hybrid
Private Public

25. AppDynamics & Hybrid Cloud
• Distributed tracing from private cloud infrastructures all the way to the
public cloud services
• Identify which services are causing issues down to the line number
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26. MICROSERVICES & APPDYNAMICS

27. Microservices
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• Big shift in modern enterprise
• Move from monolithic architectures to groups of independently
deployable services
• Huge surge in the adoption in recent years
Microservices

28. Microservices vs Monolithic
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Microservices
Monolithic

29. Monolithic Architecture
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• Encapsulates all of the functionality in a single application
• Traditional “Layered” approach to building systems
• Drawbacks:
– Agility is hindered
– Technology stack is hard to change
– Changes to the system requires complete rebuilding of entire
application
Monolithic

30. Microservices Architecture
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• Transforms a single application into a number of smaller “services”
• Typical service exhibits the following characteristics
– Independently deployable/upgradable
– Encapsulates a single “smaller” functionality
– Clear module boundary
• Drawbacks:
– Remote API calls can and will quickly become expensive
– Requires re-aligning of different teams
– Data consistency potentially needs to be actively managed
Microservices

31. Monitoring Microservices
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• Microservices are highly distributed by nature
• Monitoring health and performance becomes crucially important
– API calls need to be streamlined
– More individually moving parts = more ambiguity
– Hard to nail down the root of the problem
Microservices

32. Microservices & AppDynamics
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33. Thank You