Episode description

Links:

• The cloud economist starter kit: https://www.lastweekinaws.com/podcast/aws-morning-brief/cloud-cost-management-starter-kit-2/

Transcript

Corey: This episode is sponsored in part by LaunchDarkly. Take a look at what it takes to get your code into production. I’m going to just guess that it’s awful because it’s always awful. No one loves their deployment process. What if launching new features didn’t require you to do a full-on code and possibly infrastructure deploy? What if you could test on a small subset of users and then roll it back immediately if results aren’t what you expect? LaunchDarkly does exactly this. To learn more, visit launchdarkly.com and tell them Corey sent you, and watch for the wince.

Jesse: Hello, and welcome to the AWS Morning Brief: Fridays From the Field. I’m Jesse DeRose.

Amy: I’m Amy Negrette.

Jesse: This is the podcast within the podcast where we like to talk about all the ways we’ve seen AWS used and abused in the wild, with a healthy dose of complaining about AWS for good measure. Today, we’re going to be talking about balancing cost optimization work against feature work.

Amy: Buckle up everyone. I’ve got a lot of thoughts about this. Just kidding. It’s just the one: don’t.

Jesse: You heard it here first, folks. Don’t. Amy Negrette just says, “Don’t.”

Amy: Don’t. [laugh].

Jesse: So Amy, does that mean, don’t balance the work?

Amy: More like don’t choose. It’s always hard to make the argument to take an engineer off of feature work. This goes for 
all sorts of support tasks like updates and documentation, and as a group, we figured out that trying to put those off until an engineer has time to do it is not going to be a thing that becomes prioritized, it eventually gets deprioritized, and no one looks at it. And that’s why DocOps is the thing. It’s a process that now gets handled as part of and in parallel with software development.

Jesse: Yeah, I’ve had so many conversations in previous companies that I’ve worked for, where they basically said, “Well, we don’t have time to write documentation.” Or they will say, “The code is the documentation.” And, to their credit, there are a lot of places where the code is very cleanly documented, but if somebody is coming into this information for the first time and they don’t have technical knowledge or they don’t have deep expertise in what you’re looking at, they need documentation that is clear, understandable, and approachable. And it is so difficult to find that balance to actually make sure that that work is part of everything that you do.

Amy: And I think what the industry has decided is that if you make it a requirement for pull requests that if you’re going to make a change, you have to document that change somewhere, and that change if it has any kind of user impact, it will be displayed alongside it. That’s the only way to make it a priority with software. And cost optimization has to be treated in a similar respect.

Jesse: Yeah, so let’s talk about cost optimization as a process. To start, let’s talk about when to do it. Is this something that we do a little bit all the time, or do we do it after everything’s already done?

Amy: I know I just cited CostOps as a good model for this, even though that’s literally what we cannot do. We can’t treat cost optimization as something we do a little bit along the way because, again, speaking as an engineer, if I’m allowed to 
over-optimize or over-engineer something, I’m going to take that opportunity to do that.

Jesse: Absolutely.

Amy: And if we’re going to do project-wide cost optimization, we need to know what usage patterns are, we need to have a full user and business context on how any system is used. So, if we do a little at each step, you get stuck in that micro-optimization cycle and you’re never actually going to understand what the impact of those optimizations were. Or if you spent too much time on one part over-optimizing another part.

Jesse: It’s also really hard if this is a brand new workload that you’ve never run in the cloud before. You don’t necessarily know what the usage is going to be for this workload. Maybe you have an idea of usage patterns based on some modeling that you’ve done or based on other workloads that you’re running, but as a whole, if this is a brand new workload, you may be surprised when you deploy it and find out that it is using twice the amount of resources that you expected, or half the amount of resources that you expected, or that it is using resources and cycles that you didn’t expect.

Amy: Yeah. We’ve all been in the situation, or at least if you work with—especially with consumer software—that, you’re going to run into a situation where the bunch of users are going to do things that you don’t expect to happen within your application, causing the traffic patterns that you predicted to move against the model. To put it kindly. [laugh].

Jesse: Yeah. So, generally speaking, what we’ve seen work the best is making time for cost optimization work maybe a cycle every quarter, to do some analysis work: to look at your dashboards, look at whatever tooling you’re using, whatever metrics you’re collecting, to see what kind of cost optimization opportunities are available to you and to your teams.

Amy: So, that comes down to who’s actually doing this work. Are we going to assign a dedicated engineer to it in order to ensure it gets done? Anyone with the free cycles to do it?

Jesse: See, this is the one that I always love and hate because it’s that idea of if it’s everyone’s responsibility, it’s no one’s responsibility. And I really want everybody to be part of the conversation when it comes to cost optimization and cloud cost management work, but in truth, that’s not the reality; that’s not the way to get this work started. Never depend on free cycles because if you’re just waiting for somebody to have a free cycle, they’re never going to do any work. They’re never going to prioritize cost optimization work until it becomes a big problem because that work is just going to be deprioritized constantly. There’s a number of companies that I worked for in the past who did hackathons, maybe once a quarter or once every year, and those hackathons were super, super fun for a lot of teams, but there was a couple individuals who always picked up feature work as part of the hackathon, thinking, “Oh, well, I didn’t get a chance to work on this because my cycles were focused on something else, so now I’ll get a chance to do this.” No, that’s not what a hackathon is about.

Amy: You don’t hack on your own task list. That’s not how anything works.

Jesse: Exactly. So instead, rather than just relying on somebody to have a free cycle, kind of putting it out there and waiting for somebody to pick up this work, there should be a senior engineer or architect with knowledge of how the system works, to periodically dedicate a sprint to do this analysis work. And when we say knowing how the system works, we’re really talking about that business context that we’ve talked about many, many times before. A...