This is the second part of a mini-series where we discuss how to build distributed stateful real-time applications using actor model and clustering. The first part: https://www.slideshare.net/PeterCsala/akkademy-iii

1. Akka-demy II/II.
Peter Csala

2. 2
Agenda
• Distributed Sys. Challenges
• Clustering with Akka
• Put things together

3. 3
Previously on Lost…
Akka helps you to build
High performing
Low LatencyDecentralized
Elastic
Resilient
Extensible
Highly Concurrent
Distributed Systems

4. Challenges in Distributed Systems

5. 5
8 Fallacies of Distributed Computing
• The network is reliable
• Latency is zero
• Bandwidth is infinite
• The network is secure
• Topology doesn't change
• There is one administrator
• Transport cost is zero
• The network is homogeneous

6. 6
Distributed Systems’ Nemesis
• Guaranteed Delivery
• Synchronous RPC
• Distributed Shared Mutable State
• Serializable Distributed Transactions
• Etc.

7. 7
Why do we even bother?
• Speed >> High Performance
• Reliability >> Fault tolerant, Resilient
• Load ability >> Scalable
• Resource sharing >> Economical
• Etc.

8. 8
CAP Theorem

9. 9
CAP Theorem

10. 10
For further details
• YouTube, SlideShare

11. Clustering

12. 12
Akka package layering
Actors
Remoting
PersistenceClustering
Cluster
Aware
Routers
Cluster
Singleton
Distributed
Data
Sharding
Distributed
Pubsub
Cluster Client

13. 13
Low Latency – Routers
• Router & Rootees
• Dynamic or Static (Hocon)
• Group vs Pool
• Dynamic resizability
• Strategies
• RoundRobin, Broadcast
• ConsistentHashing
• SmallestMailbox

14. 14
Low Latency – Remoting
• Built on top of Akka.IO
• Peer 2 Peer communication
• akka.tcp://ActSys@node-51:8000/user/mysample
• IActorRef vs IActorSelection
• Identify, await ResolveOne
• Remote deploy capability

15. 15
Decentralized – Node Ring
• Seed node
• No leader election
• Nor leader selection
• Peer-To-Peer
• No SPOF
• At least once delivery
• Gossip Protocol

16. 16
Resilience – Cluster Membership
• Built on top of Remoting
• Failure detection
• Phi value
• Graceful shutdown
• Cluster aware routers
• Deploy rootees dynamically
– Elasticity
• Fine-grained control

17. 17
Resilience – Supervision
• Arrange actors into hierarchies
• Guardian actor can
– Resume, Restart, Stop, Escalate
• Strategies
– One-for-one, All-for-one, (Stopping)
• Let it crash philosophy
• Resurrection
– Props with Reflection
• PoisonPill
• Monitoring
– Lifecycle hooks
– DeathWatch
– Reaper pattern

18. 18
Resilience – Supervision
/user
/user/As
/user/As/A1 /user/As/A2
/user/Bs
/user/Bs/B1 /user/Bs/B2

19. 19
Resilience – Persistence
• Supports EventSourcing + CQRS
• Journals
• Snapshots
• Receive a Command
• Can be rejected
• Persist an Event
• Mash them into a snapshot
• Async callback
• Internally uses stashing
• AggregateRoot
– Parent can persist children events
• Recover events
• Replaying all events
• OnReplaySuccess
– When all events are processed
• Delete API???
• Lot’s different Plugin

20. 20
Resilience – Persistence
Actor
DoThis
DidThat

21. 21
Resilience – Persistence
Actor
DoThis
DidThat

22. 22
Resilience – Circuit Breaker
Closed
Open
Half
Open
Fail
Fast
Delay
Failure

23. 23
Consistency – At least Once
• Acknowledgement protocol
• Caller side
• It is a persistent actor
• Delivery
– Wrapping msg + deliveryId
• Resend ability
• ConfirmDelivery
• Callee side
• Confirm

24. 24
Elasticity – Sharding
• Shard
– Group of Actors
– Based on a hash function
– N / node
• ShardRegion
– Group of Shards
– Routes requets
– Handels actors’ lifecycles
– 1 / node
• Shard Coordinator
– Router between shards
– Distributes shards „evenly” among
nodes
– Semi-dynamic
– 1 / cluster (ClusterSingleton)
• Graceful shutdown
– Request it from ShardRegion
– It will propagate all the way down
– Asks for Hands-off
– Leaves the cluster

25. 25
Elasticity – Sharding

26. Put things together

27. 27
SPA + Stateless #1

28. 28
SPA + Stateful #1

29. 29
Summary
• Building a Distributed System is hard
• Akka tries to help you ease this pain
• Be aware what quality attributes are chasing