Monitoring Sucks Watch Your Language
The following post is a recap of what was discussed in the 07/21/11 #monitoringsucks irc meeting
Before I get any further, I just want to thank everyone who attended, either in virtual person or in spirit. There have been so many awesome discussions going around this topic since we started. I am truly priviledged to interact with each and every one of you. I struggle to count myself a peer and I can only hope that I provide something in return.
I mentioned to someone today that I’m literally sick of the current landscape. I consider the current crop of monitoring solutions to be technologically bankrupt. The situation is fairly untenable at this point.
I just installed (after having a total loss of an existing Zenoss setup) Nagios again. I’m not joking when I say that it depressed the everliving hell out of me. The monitoring landscape simply has not kept up with modern developments. At first it was mildly frustrating. Then it was annoying. Now it’s actually a detriment.
Now that we have that out of the way….
Darmok and Jalad at Tanagra
Communication is important. Like Picard and Dathon, we’ve been stranded on a planet with shitty monitoring tools and we’re unable to communicate about the invisibile threat of suck because we aren’t even speaking the same language. I say event, you hear trigger, I mean data point. So the first order of business was to try and agree on a set of terms. It was decided that we would consider these things primitives. Here they are:
Please read through this before jumping to any conclusions. I promise it will all become clear (as mud).
a numeric or boolean data point
The data type of a metric was something of a sticking point. People were getting hung up on data points being various things (a log message, a “status”, a value). We needed something to describe the origin. The single “thing” that triggered it all. That thing is a metric.
So why numeric OR boolean? It was pretty clear that many people considered, and rightly so I would argue, that a state change is a metric. A good example given by Christopher Webber is that of a BGP route going away. Why is this a less valid data point than the amount of disk space in use or the latency from one host to another? Frankly, it’s not.
But here’s where it gets fuzzy. What about a log message. Surely that’s a data point and thus a metric.
Yes and No. The presence of a log message is a data point. But it’s a boolean. The log message itself?
metadata about a metric
Now metadata itself is a loaded term but in this scope, the “human readable” attributes are considered context. Going back to our log example. The presence of the log message is a metric. The log message itself is context. Here’s the thing. You want to know if there is an error message in a log file. The type of error, the error message text? That’s context for the metric to use in determining a course of action.
Plainly speaking, metrics are for machines. Context is for humans. This leads us to….
metric combined with context
This is still up in the air but the general consensus was that this was a passable definition. The biggest problem with a group of domain experts is that they are frequently unable to accept semantic approximation. Take the discussion of Erlang Spawned process:
- It’s sort of like a VM on a VM
- NO IT’S NOT.
The fact is that an Erlang spawned process has shades of a virtual machine is irrelevant to the domain expert. We found similar discussions around what we would call the combination of a metric and its context. But where do events come from?
the source of a metric
Again, we could get into arguments around what a resource is. One thing that was painfully obvious is that we’re all sick and tired of being tied to the Host and Service model. It’s irrelevant. These constructs are part “legacy” and part “presentation”.
Any modern monitoring thought needs to realize that metrics no longer come from physical hosts or are service states. In the modern world, we’re taking a holistic view of monitoring that includes not only bare metal but business matters. The number of sales is a metric but it’s not tied to a server. It’s tied to the business as a whole. The source of your metrics is a resource. So now that we have this information - a metric, its context and who generated it - what do we do? We take….
a response to a given metric
What response? It doesn’t MATTER. Remember that these are primitives. The response is determined by components of your monitoring infrastructure. Humans note the context. Graphite graphs it. Nagios alerts on it. ESPER correlates it with other metrics. Don’t confuse scope here. From this point on, whatever happens has is all decided on by a given component. It’s all about perspective and aspects.
Temba, his arms wide
I’m sure through much of that, you were thinking “alerting! graphing! correlation!”. Yes, that was pretty much what happened during the meeting as well. Everyone has pretty much agreed (I think) at this point that any new monitoring systems should be modular in nature. As Jason Dixon put it - “Voltron”. No single system that attempts to do everything will meet everyone’s needs. However, with a common dictionary and open APIs you should be able to build a system that DOES meet your needs. So what are those components? Sadly this part is not as fleshed out. We simply ran out of time. However we did come up with a few basics:
getting the metrics
It doesn’t matter if it’s push or pull. It doesn’t matter what the transport is - async or point-to-point. Somehow, you have to get a metric from a resource.
Extract the metric and resource from an event. Do something with it. Maybe you send the metric to another component. Maybe you “present” it or send it somewhere to be presented. Maybe you perform a change on a resource (restarting a service). Essentially the decision engine.
While you might be thinking of graphing here, that’s a type of presentation. You know what else is presentation? An email alert. Stick with me. I know what’s going through your head. No..not that…the other thing.
This is pretty much correlation. We didn’t get a REAL solid defintion here but everyone was in agreement that some sort of analytics is a distinct component.
The “other” stuff
As I said, we had to kind of cut “official” things short. There was various discussion around Storage and Configuration. Storage I personally can see as a distinct component but Configuration not so much. Configuration is an aspect of a component but not a component itself.
Remember when I said I know what you’re thinking? This is what I think it was.
You can look at the above items and from different angles they look similar. I mean sending an email feels more like event processing than presentation. You’d probably be right. By that token, drawing a point on a graph is technically processing an event. The fact is many components have a bit of a genetic bond. Not so much parent/child or sibling but more like cousins. In all honesty, if I were building an event processing component, I’d probably handle sending the email right there. Why send it to another component? That makes perfect sense. Graphing? Yeah I’ll let graphite handle that but I can do service restarts and send emails. Maybe you have an intelligent graphing component that can do complex correlation inband. That makes sense too.
I’m quite sure that we’ll have someone who writes a kickass event processor that happens to send email. I’m cool with that. I just don’t want to be bound to ONLY being able to send emails because that’s all your decision system supports.
Shaka, when the walls fell
Speaking personally, I really feel like today’s discussion was VERY productive. I know that you might not agree with everything here. Things are always up for debate. The only thing I ask is that at some point, we’re all willing to say “I know that this definition isn’t EXACTLY how I would describe something but it’s close enough to work”.
So what are the next steps? I think we’ve got enough information and consensus here for people to start moving forward with some things. One exercise, inspired by something Matt Ray said, that we agreed would be REALLY productive is to take an existing application and map what it does to our primitives and components. Matt plans on doing that with Zenoss since that’s what he knows best.
Let me give an example:
Out of the box, Nagios supports Hosts and Services which map pretty cleanly to resources. It is does not only collection but event processing and presentation. It not only supports metrics but also context (Host down is the boolean metric. “Response timeout” is the context. Through something like pnp4nagios, it can support different presentations. It has very basic set of Analytic functionality.
Meanwhile Graphite is, in my mind, strictly presentation and deals only with metrics. It does support both numeric and boolean metrics. It also has basic resource functionality but it’s not hardwired. It doesn’t really do event handling in the strict sense. Analytics is left to the human mind. It certainly doesn’t support context.
I’d love to see more of these evaluations.
Also, I know there are tons of “words” that we didn’t cover - thresholds for instance. While there wasn’t a total consensus, there was some agreement that somethings were attributes of a component but not a primitive itself. It was also accepted that components themselves would be primitives. You correlation engine might aggregate (another word) a group of metrics and generate an event. At that point, your correlation engine is now a resource with its own metrics (25 errors) and context (“number of errors across application servers exceeded acceptable limits”) which could be then sent to an event processor.
That’s the beauty of the Voltron approach and not binding a resource to a construct like a Host.
Special note to the Aussies
I’m very sorry that we couldn’t get everyone together. I’ve scheduled another meeting where we can start from scratch just like this one, or build on what was discussed already. I’m flexible and willing to wake up at whatever time works best for you guys
Thanks again to everyone who attended. If you couldn’t be there, I hope you can make the next one.