Comet for highly scalable applications

Comet for Highly- Scalable Applications Michael Carter and Arthur Lee diagrams by Jacob Rus 24 October 2007 The Ajax Experience Boston

What is Comet? “Comet” describes a model of user interaction Pushing real-time updates to web browsers Renkoo Gmail Chat Meebo

Old Method: Polling Otherwise known as “hammering the server” App (Event Dispatcher (Event Queues inside) Browsers

Polling Overview Old and busted Pros: • Easy to implement • Client side • Server side Cons: • Wasted requests • Additional latency

Enter Long-Polling The new hotness Pros: • Latency—gone! • Client side still easy Cons: • Difﬁcult to scale server-side • Conceptually more complicated

Vertical Scaling: How do you scale comet on a single server? photo by Michael (mx5tx)

Vertical Scaling: How do you scale comet on a single server? Wrong way: Use a threaded server like Apache or IIS Threaded Comet Dispatcher • Supports a few Browsers Event Connect dozen users Queue Queue App • CPU usage and latency go through the roof as users are added

Vertical Scaling: How do you scale comet on a single server? Wrong way: Use a threaded server like Apache or IIS Compared to polling: Latency reduced for very light load Avg. latency depends on the order of events As much as 7× the CPU for moderate load CPU-bound at moderate load

Vertical Scaling: How do you scale comet on a single server? Right way: Use an event-based architecture • Supports as Event-Based Comet Dispatcher many users as Browsers Event Connect CPU and I/O Queue Pool App can handle • CPU usage scales linearly and latency remains low

Vertical Scaling: How do you scale comet on a single server? Right way: Use an event-based architecture Compared to polling: Decreased latency and CPU usage Compared to threaded Comet: Vastly decreased CPU usage Order of events irrelevant Performance degrades gracefully

Horizontal Scaling: How do you scale comet across many servers? photo by ulybug

Horizontal Scaling: How do you scale comet across many servers? Wrong way: Build the whole software stack into the comet server Embed publish-subscribe architecture into comet server Keep application state within comet nodes Allow comet nodes to communicate with each-other

Horizontal Scaling: How do you scale comet across many servers? Wrong way: Build the whole software stack into the comet server • Design is inﬂexible, can’t Application Node scale for some Comet Nodes uses • Hard to scale to many nodes A B C D E F in the best case Browsers

Horizontal Scaling: How do you scale comet across many servers? Wrong way: Build the whole software stack into the comet server • Design is inﬂexible, can’t Application “A” sends message Node to “E” scale for some Comet Nodes uses • Hard to scale to many nodes A B C D E F in the best case Browsers

Horizontal Scaling: How do you scale comet across many servers? Wrong way: Build the whole software stack into the comet server • Design is inﬂexible, can’t Application “E” sends response Node to “A” scale for some Comet Nodes uses • Hard to scale to many nodes A B C D E F in the best case Browsers

Horizontal Scaling: How do you scale comet across many servers? Right way: Share nothing between nodes • No CPU or I/O overhead of sharing state Application Node • Comet CPU usage Nodes scales linearly and latency remains low Browsers

Horizontal Scaling: How do you scale comet across many servers? Right way: Use Orbited «wink» Distributed hash table Application Hash Pre-deﬁned Nodes Function Comet hash function Nodes Leave authenti- cation to app layer A B C D E F Browsers

Horizontal Scaling: How do you scale comet across many servers? Right way: Use Orbited «wink» Distributed hash table “B” sends Application Hash Pre-deﬁned Nodes message Function to “E” Comet hash function Nodes Leave authenti- cation to app layer A B C D E F Browsers

Horizontal Scaling: How do you scale comet across many servers? Right way: Use Orbited «wink» Distributed hash table “E” sends Application Hash Pre-deﬁned Nodes response Function to “B” Comet hash function Nodes Leave authenti- cation to app layer A B C D E F Browsers

Publish / Subscribe Pushing published events to groups of browsers What’s it good for? Applications for which multiple users need the same live updates

Publish / Subscribe Pushing published events to groups of browsers What’s it good for? Applications for which multiple users need the same live updates real-time chat

Publish / Subscribe Pushing published events to groups of browsers What’s it good for? Applications for which multiple users need the same live updates stock tickers real-time chat

Scaling Pub/Sub How do you scale publish/subscribe horizontally? If we start with a single comet node, which dispatches events to multiple users in multiple groups then how do we scale up to multiple comet nodes?

Scaling Pub/Sub How do you scale publish/subscribe horizontally? If we start with a single node, which dispatches events to multiple users in multiple groups… A single comet Application Node node serves all users and all Comet Dispatcher groups Node Browsers

Scaling Pub/Sub How do you scale publish/subscribe horizontally? …then how do we scale up to a pair of nodes? Either we arrange Application Node nodes by group: All of a group’s Comet Dispatcher Nodes events are sent by one node Browsers

Scaling Pub/Sub How do you scale publish/subscribe horizontally? …then how do we scale up to a pair of nodes? Or we arrange Application Node nodes by user: A user receives Comet Dispatcher Nodes all events from the same node Browsers

Scaling Pub/Sub How do you scale publish/subscribe horizontally? But how, speciﬁcally? Split the architecture into layers Do not mix pub/sub layer App Publish/Subscribe Cloud with comet dispatcher Comet Dispatcher Nodes Treat pub/sub layer as a black box Browsers

Pub/Sub Options Publish/subscribe already has solutions Don’t reinvent the wheel: Many well-understood, scalable publish/subscribe solutions exist • Internet Relay Chat: Nearly 20 years old. Scales well for large groups of users. • XMPP (Jabber): Flexible protocol. Does presence well, in addition to messaging. • Java Message Service: It’s enterprise, baby.

Pub/Sub with Orbited Orbited can be easily added to a pub/sub stack Scaling through modularity: Its simplicity makes Orbited easy to add to any web app architecture Orbited handles Orbited comet dispatch Pub/Sub Stack Internet IRC or Jabber Relay IRC Bridge Chat handles publish/ Orbited subscribe Application / App servers do Web Server Browser everything else

Conclusion: • Polling latency unacceptable • Comet solves this problem • Impossible to scale Comet with threaded design • Event-based architecture is necessary • Horizontal scaling requires “share nothing” design • Publish/subscribe is a difﬁcult problem • Scaling pub/sub is easiest with layered architecture

Michael Carter CarterMichael@gmail.com http://www.orbited.org/ 24 September 2007 AJAXWorld

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