Forget Client - Server. How about Spokes - Council?

2008-01-08 10-minute read

What if we were to design a web-application (say, for example, a blogging program) that, from the start, was designed with the same goals that we would design a mass political organizing campaign? Not a small, local political organizing campaign but a massive, global campaign.

Let’s say:

  • Redundancy: no person or computer should occupy such a central role that if they were to be removed (COINTELPRO, network outage, etc.), the entire project would come crashing down. A redundant web-application would require us to have multiple servers on multiple Internet connections running the application in such as way so that if one fails, the application continues functioning. Ideally a server or link could go down without any loss of functionality, but I would be perfectly satisfied to tolerate a period of partial functionality provided there was an automated way to fail-over to backups within a reasonable time period. The fabled 99.999 uptime is not a political goal (although it might be a functional goal for a particular application).

  • Scalability: the project should be designed so that it can grow from 50 people or computers to 5,000 people or computers without needing to be significantly re-organized. Scalability can clash with redundancy. The best way to achieve redundancy would be to have every server able to run the entire application by itself (or operate with pure consensus in which all decisions are made by all people). Then, you can lose anyone (in fact you could get cut in half) and still function. That approach, however, is not scalable. What happens when you get more information than a single brain or hard drive can handle? Also - if everyone has to stay in sync, the more time and resources we spend keeping everyone and every server in sync (imagine trying to synchronize data bewteen 500 servers or do the formal consensus process with people who can’t fit in the same room). To be scalable we need a system that can delegate.

  • Security/Ownership balance: people and computers should be allowed to join the project and immediately have enough responsibility to feel a real sense of ownership while not having the power to bring down the entire project. A wise person once said: The only way to tell if someone is trustworthy is to trust them. Unlike in many physical situations, when working with data we have enormous opportunities to achieve this goal, provided we limit ourselves to public information. In our hypothetical blogging application, there is no private data. All data entered into the system is intended for public consumption. In this model, provided we carefully setup our system to securely preserve all versions of all data, we can invite anyone to be a server administrator. The worst thing that they can do is modify or delete a portion of the data, in which case we roll the data back to it’s original state and then cut off that administrator. Furthermore, the whole process can be publicly documented (since all the data is public already).

At the moment, there are precious few web applications that come near these goals (to be fair, there are precious few political organizing campaigns that adhere to these goals either). Most of our web applications (like blogs, or Drupal web sites, or wikis, or web-based databases) rely on a single server which, if removed, would cause the application to fail. Similarly, once a web site gets too many users, it can be very difficult to resolve that problem short of buying a new and more powerful server. Few of our currently designed programs enable us to securely accept help from others without fully trusting them.

In the corporate world, this type of design (minus the security/ownership part) is fairly standard. However, the tools are either proprietary or they are designed from a politically hierarchical perspective (rather than a single database server there is a cluster of database servers that still play a central role).

What would it mean to follow these goals in an web-application environment?


Almost all web-applications have at least one piece of private data: every user’s password. In an ideal world, we would all use a different password on every web application, however, we all know that world doesn’t exist. Most people use the same password everywhere, making it an important piece of private information. For our purposes, we just can’t use passwords this way without the risk of people having them compromised.

Open ID, a distributed authentication system that allows you to specify a third party to authenticate you, provides an elegant solution to this problem. If our application used OpenID for authentication, then the web application itself would never need to know the actual user’s password.

However, I think there’s an even better solution. The oldest distributed authentication system is Pretty Good Privacy (PGP) - commonly known by the free implementation called Gnu Privacy Guard (gpg).

If our application used gpg for authentication, the process of getting an account would go something like this:

  • The user clicks the create account link
  • They are asked to enter the gpg public key and their gpg id (they are also provided a link to instructions on how to create a gpg key pair). We would only need to get the public key (not the gpg id), but by getting the gpg id as well, we’d be able to do things like check public key servers to see if a gpg id has been revoked.
  • We’d then ask them to verify that they have the private key by presenting encrypted text and ask them to decrypt it (software like the FireGPG plugin for Firefox would be critical to make this process user friendly enough).
  • Now they have an account. In the future, they can login by decrypting a random encrypted string and the server never has to know their password.

The primary added benefit of using gpg is: every time the user posts a blog, they can digitally sign the blog, so that if the blog is every altered by a malicious system administrator, the signature verification would fail making that alteration easy to detect.


How would this application work on multiple servers in a coordinated way?

I’ll start by suggesting some terminology:

  • Spokes - Council design: the name I’m giving this approach. Technically, it’s still a Client - Server approach (because people will connect to it using their web browser clients), however, rather than connect to a single server, they will connect to a “council” of servers.

  • Council: refers to the collection of servers that are contributing to the particular implementation of the web application.

  • Spoke: refers to a single server in the council

Suppose I announce to the world: I’m starting a new blog server for the purposes of supporting a global, coalition-based organizing campaign. One aspect of the campaign is to get coalition members, most of whom have never blogged before, to blog about the campaign. Anyone can get a blog by going to

I have already setup a at least one spoke server (, so when you go to, you get a functional blogging application.

However, since I’m expecting a lot of growth (and I want to respect the three goals above) I also put a call out for tech collectives and organizations that are interested in supporting the project by donating server resources.

I am then contacted by Group B who says: We have a server connected to the Internet that we’d like to donate to the project.

I provide them with a script that they run on their server which downloads the source files, runs some tests to demonstrate that it is fully working, and then reports back to me that it is ready to go.

Then, I update the DNS record for so that it will, round robin style, include the new server’s IP address when a user goes to

So far so good. Now what?

User Maria goes to (and lands on She logs in with her gpg key and then clicks the button to create a blog. The server generates links in a form to ensure that she stays on the same server, although to Maria, it appears as though she is always on

She’s asked what username she wants for her blog and she selects “maria” ( She hits submit and recieves a message that her request is pending and asks her to check back in a few minutes.

Meanwhile, executes a dns query (the oldest distributed database system in the world) to see if is taken. If not, it submits a request to the authoritative name server for requesting that be created and given it’s own IP address. The authoritative DNS server could do any number of checks (complicated key exchanges or it could simply see if the IP address is an IP address belonging to a server in the DNS system), then it would create the record (provided nobody has slipped in earlier) and respond that the record was created.

Now, Maria can start blogging. When Maria publicizes her blog (, it is already setup to go to the right server, thanks to the domain name system.

Additional features could include: every user has a primary spoke plus one or more secondary spokes. All write requests are re-directed to the primary hosts, read requests are redirected to any of the secondary spokes. Perhaps when the original DNS record is created, it also creates which points to the primary host, while is setup round-robin style to go to all of the secondary spokes. The secondary spokes are responsible for pulling in data from the primary spokes to stay in sync.

This approach is redundant: if one server goes down, a routine can be run on the name server to remove that IP address and, if the server is a primary server, then promote one of the secondary servers to take over as the primary server. It’s also scalable. Servers can be configured to refuse new bloggers if they start running low on hard disk space, or they could add additional secondary servers for popular bloggers if they run low performance-based system resources. Ideally there would be administrative scripts that could transfer blog accounts from server to server.

Aggregation and Indexing

There are still a few features that we would want that don’t scale very well. The whole purpose of building a giant blog network is to provide a sense of unity - we want all of the blogs to be aggregated and search-able to build this unity. No matter which server you land on, it should show you the most recent 20 blog posts from accross the entire network. You should also be able to type a search term in the search box and search all the blogs.

Aggregation and indexing would get significantly more difficult and resource intensive as we add more servers. Aggregating blogs on 5 or 10 servers is not so difficult, but doing that for hundreds of servers each of which have hundreds of blogs could become a monumental task. Although technically this is a scalability problem, given our model, it could be addresses by throwing more computers at it (as opposed to hitting a wall that can’t be overcome without hardware upgrade). We could organize concentric circles of aggregating servers, so each server is only aggregating 5 - 10 servers and then an upstream server aggregates their aggregate. The same model could be applied to indexing. These network could produce an inner circle of servers that contain the entire aggregate and index for all servers to access.

Unsolved Problems

How would we establish lines of trust. While the system works well if one untrusted spoke flakes out, what happens if several spokes (which encompass the primary and secondary servers for a particular blog) all flake out together?