Taking on a new platform design recently I thought it was interesting to see how things evolved in the past years and how we design and think about platform architecture.
So what do we do ?
As system developers, system administrators and system engineers, what do we do ?
- We develop software
- We design architectures
- We configure systems
But it isn’t the purpose of our jobs, for most of us, our purpose is to generate business value. From a non technical perspective we generate business value by creating a system which renders one or many functions and provides insight into its operation.
And we do this by developing, logging, configuration and maintaining software across many machines.
When I started doing this - back when knowing how to write a sendmail configuration file could get you a paycheck - it all came down to setting up a few machines, a database server a web server a mail server, each logging locally and providing its own way of reporting metrics.
When designing custom software, you would provide reports over a local AF_UNIX socket, and configure your software by writing elegant parsers with yacc (or its GNU equivalent, bison).
When I joined the OpenBSD team, I did a lot of work on configuration files, ask any members of the team, the configuration files are a big concern, and careful attention is put into clean, human readable and writable syntax, additionally, all configuration files are expected to look and feel the same, for consistency.
It seems as though the current state of large applications now demands another way to interact with operating systems, and some tools are now leading the way.
So what has changed ?
While our mission is still the same from a non technical perspective, the technical landscape has evolved and went through several phases.
The first era of repeatable architecture
We first realized that as soon as several machines performed the same task the need for repeatable, coherent environments became essential. Typical environments used a combination of cfengine, NFS and mostly perl scripts to achieve these goals.
Insight and reporting was then providing either by horrible proprietary kludges that I shall not name here, or emergent tools such as netsaint (now nagios), mrtg and the like.
The XML mistake
Around that time, we started hearing more and more about XML, then touted as the solution to almost every problem. The rationale was that XML was - somewhat - easy to parse, and would allow developers to develop configuration interfaces separately from the core functionality.
While this was a noble goal, it was mostly a huge failure. Above all, it was a victory of developers over people using their software, since they didn’t bother writing syntax parsers and let users cope with the complicated syntax.
Another example was the difference between Linux’s iptables and OpenBSD’s pf. While the former was supposed to be the backend for a firewall handling tool that never saw the light of day, the latter provided a clean syntax.
Infrastructure as code
Fast forward a couple of years, most users of cfengine were fed up with its limitations, architectures while following the same logic as before became bigger and bigger. The need for repeatable and sane environments was as important as it ever was.
At that point of time, PXE installations were added to the mix of big infrastructures and many people started looking at puppet as a viable alternative to cfengine.
puppet provided a cleaner environment, and allowed easier formalization of technology, platform and configuration. Philosophically though, puppet stays very close to cfengine by providing a way to configure large amounts of system through a central repository.
At that point, large architectures also needed command and control interfaces. As noted before, most of these were implemented as perl or shell scripts in SSH loops.
On the monitoring and graphing front, not much was happening, nagios and cacti were almost ubiquitous, while some tools such as ganglia and collectd were making a bit of progress.
Where are we now ?
At some point recently, our applications started doing more. While for a long time the canonical dynamic web application was a busy forum, more complex sites started appearing everywhere. We were not building and operating sites anymore but applications. And while with the help of haproxy, varnish and the likes, the frontend was mostly a settled affair, complex backends demanded more work.
At the same time the advent of social enabled applications demanded much more insight into the habits of users in applications and thorough analytics.
New tools emerged to help us along the way:
- In memory key value caches such as memcached and redis
- Fast elastic key value stores such as cassandra
- Distributed computing frameworks such as hadoop
- And of course on demand virtualized instances, aka: The Cloud
Some daemons only provide small functionality
The main difference in the new stack found in backend systems is that the software stacks that run are not useful on their own anymore.
Software such as zookeeper, kafka, rabbitmq serve no other purpose that to provide supporting services in applications and their functionality are almost only available as libraries to be used in distributed application code.
Infrastructure as code is not infrastructure in code !
What we missed along the way it seems is that even though our applications now span multiple machines and daemons provide a subset of functionality, most tools still reason with the machine as the top level abstraction.
puppet for instance is meant to configure nodes, not cluster and makes dependencies very hard to manage. A perfect example is the complications involved in setting up configurations dependent on other machines.
Monitoring and graphing, except for ganglia has long suffered from the same problem.
The new tools we need
We need to kill local configurations, plain and simple. With a simple enough library to interact with distant nodes, starting and stopping service, configuration can happen in a single place and instead of relying on a repository based configuration manager, configuration should happen from inside applications and not be an external process.
If this happens in a library, command & control must also be added to the mix, with centralized and tagged logging, reporting and metrics.
This is going to take some time, because it is a huge shift in the way we write software and design applications. Today, configuration management is a very complex stack of workarounds for non standardized interactions with local package management, service control and software configuration.
Today dynamically configuring bind, haproxy and nginx, installing a package on a Debian or OpenBSD, restarting a service, all these very simple tasks which we automate and operate from a central repository force us to build complex abstractions. When using puppet, chef or pallet, we write complex templates because software was meant to be configured by humans.
The same goes for checking the output of running arbitrary scripts on machines.
Where we’ll be tomorrow
With the ease PaaS solutions bring to developers, and offers such as the ones from VMWare and open initiatives such as OpenStack, it seems as though virtualized environments will very soon be found everywhere, even in private companies which will deploy such environments on their own hardware.
I would not bet on it happening but a terse input and output format for system tools and daemons would go a long way in ensuring easy and fast interaction with configuration management and command and control software.
While it was a mistake to try to push XML as a terse format replacing configuration file to interact with single machines, a terse format is needed to interact with many machines providing the same service, or to run many tasks in parallel - even though, admittedly , tools such as capistrano or mcollective do a good job at running things and providing sensible output.
The future is now !
Some projects are leading the way in this new orientation, 2011 as I’ve seen it called will be the year of the time series boom. For package management and logging, Jordan Sissel released such great tools as logstash and fpm. For easy graphing and deployment etsy released great tools, amongst which statsd.
As for bridging the gap between provisionning, configuration management, command and control and deploys I think two tools, both based on jclouds1 are going in the right direction:
- Whirr2: Which let you start a cluster through code, providing
recipes for standard deploys (zookeeper, hadoop)
- pallet3: Which lets you describe your infrastructure as code and
interact with it in your own code. pallet’s phase approach to cluster configuration provides a smooth dependency framework which allows easy description of dependencies between configuration across different clusters of machines.
Who’s getting left out ?
One area where things seem to move much slower is network device configuration, for people running open source based load-balancers and firewalls, things are looking a bit nicer, but the switch landscape is a mess. As tools mostly geared towards public cloud services will make their way in private corporate environments, hopefully they’ll also get some of the programmable