The document discusses SEDA (Staged Event-Driven Architecture), a framework for building highly concurrent and load-conditioned internet services. SEDA decomposes applications into stages separated by queues, allowing events to be inspected and prioritized during heavy loads. It also enables dynamic control of resource management through monitoring of application performance. Java and the actor model are proposed as suitable tools for implementing SEDA's staged approach.

1. SEDA Java
Benjamin Tan
Team Leader@DBAppSecurity
Twitter: tanbamboo

2. Agenda
• SEDA
• Java
• Actor

3. SEDA
• SEDA: A new architecture for Internet services
• A general-purpose framework for high concurrency and
load conditioning
• Decomposes applications into stages separated by queues
• Adopt a structured approach to event-driven
concurrency
• To appear in the Eighteeth Symposium on Operating
Systems Principles (SOSP-18), Chateau Lake Louise,
Canada, October 21-24, 2001.
• http://www.cs.berkeley.edu/~mdw/

4. SEDA features
• Enable load conditioning
• Event queues allow inspection of request streams
• Can perform prioritization or filtering during heavy load
• Dynamic control for self-tuning resource management
• System observes application performance and tunes runtime parameters
• Apply control for graceful degradation
‣ Perform load shedding or degrade service under overload
• Simplify task of building highly-concurrent services
• Decouple load management from service complexity
• Use of stages supports modularity, code reuse, debugging
• Dynamic control shields apps from complexity of resource management

5. SEDA
Staged Event-Driven Architecture (SEDA)
file data
I/O
request
accept handle file
connection connection HTTP miss I/O
request cache
parse check miss
packet cache
packet packet
read send write
packet cache hit response packet
Decompose service into stages separated by queues
• Stage Queue
• Each stage performs a subset of request processing
• Stages internally event-driven, typically nonblocking
• Stage
• Queues introduce execution boundary for isolation and conditioning
Each stage contains a thread pool to drive stage execution
• However, threads are not exposed to applications
• Dynamic control grows/shrinks thread pools with demand
Stages may block if necessary

6. • Stage Queue
SEDA
•
•

7. •
•

8. Java
•
• CPU

9. Active List
•
ThreadLocal
• JUC concurrent

10. Counter
• AtomicInteger 1500EPS
1500
•
•

11. Java
• :
•
•
•

12. CPU
• CPU MEM Stage
CPU ( )
• IO Stage
CPU 3~5
HTTP

13. Actor
• SEDA
•
• Stage Queue
• Stage

14. Actor
• Actor
Context
• Actor Mailbox
• Topology Actor

15. Actor
• “self-heals, systems that never stop”
?
•
CPU ?