Observe, Orient, Decide, Act. I love simple but elegant models, and The OODA loop developed for combat operations by John Boyd is just that. Designed for situations like fighter jet combat, it fits high stress situations that require quick responses. Although comically less extreme, it is a very useful model for handling system administration incidents because it highlights what goes right and what goes wrong when a sysadmin or devops team deals with the unexpected.
OODA in Practice
As an example let’s say you have reports that your website is slow and sometimes timing out. Step one is to gather facts and Observe. For sysadmins this means looking through your logs, the reports themselves, and/or your monitoring system.
Once you have collected data it needs to be digested so you can Orient yourself to the situation. Orienting is the act of analyzing and interpreting the data. For example, logs contain many fields, but to turn that data into information the logs need to be queried to find anomalies or patterns. We create graphs or generate summary statistics, whatever we need to do to understand the situation. This often is naturally done alongside observation. In order to truly fix problems we try to come up with a hypothesis based on the data and our experience to find the real cause.
Eventually somebody has to Decide to do something, even it is just deciding to jump back to observation to get more information. For example, if there are indications that the database is slow, then you might decide to go back and collect more information about the performance of the database server and restart the loop.
The last stage is to actually Act and make some changes that will either fix the problem, test a hypothesis, or allow you to observe more information that can be analyzed. If you think certain queries are making the database server slow eventually someone has to decide to fix them and take action.
This is a loop that will almost always have many iterations. With this model a good sysadmin team can iterate the loop rapidly, smoothly, and intelligently. Also over time a good team develops tools to make the loop go faster and gets better at working together to tighten the loop.
This framework brings light to problematic patterns that come up in system administration. Each stage of the loop has common problems and often the loop isn’t navigated in a logical way.
When it comes to observation, the most common problem seems to be a lack of data or a willful skipping of this phase. Often there just isn’t anywhere near enough logging and monitoring to diagnose problems in a scientific way. There can also be a lack of discipline to take the time to actually collect the data needed to pinpoint issues in a smart way. If there is too much friction around getting the data or collecting it in the first place it can lead to skipping this phase. All of this leads to one of my pet peeves that comes up in system administration — guessing.
Guessing also shows up in the orientation phase. If the observation phase has been skipped or done poorly then you can’t really orient, all you can do is grope around hoping to get lucky. Sometimes guessing can make sense when it is based on experience — but that is really using heuristics and not guessing. A lack of good analytical skills and/or experience can also lead to guessing. If the data is there but nobody knows how to interpret it well then all you can do is guess. Also if the observation and orientation phases are too slow then the pressure builds and in panic people will just start trying random things.
If there are problems with deciding and acting then there tends to be organizational or personality problems. If it isn’t clear who should be making decisions, or if there is a lot of fighting around what decision to take then the team needs to sit down and have some frank conversations to hash out their problems. Everyone should be willing to move forward with choices and trust each other or the loop can get bogged down in this phase. Failure to act during a crisis can be frustrating so the team needs to have the skill and confidence to act with expertise.
OODA Done Right
Contrast all those problems with your ideal sysadmin team facing an urgent incident. Each stage is highly automated and is constantly improving. In a great team when major problems come up instantly everyone starts collecting and sharing data. The monitoring systems have all the information they need and they have already built tools to quickly analyze it. The alerts themselves have already automated much of the observation phase because they describe the components of the problem. With a good team this sort of monitoring likely exists if the there is continuous improvement around monitoring and they learn and implement what is needed based on past experience.
With good monitoring and analysis tools a smart team quickly comes up with several good possibilities based on their experience and what they are seeing after orienting themselves. They can then quickly decide to pick a theory and implement it because they know they can try other ideas quickly and they trust each other. They also will accept feedback (new information) at any stage and adjust smoothly.
Why it Matters
If there are problems at any stage of the model, then all of the other stages will suffer when it comes to facing incidents. The same model can be applied to longer term projects or strategy as well. It gives us a framework to analyze how we have performed and where we can focus on improving to prepare for the next unknown incident. Facing incidents with skill can make a failure feel like a success and the OODA loop can help you make sure that happens every time.