I don’t really do “women stuff”. I don’t really identify with any gender and I find a lot of the advice to be condescending and overly delicate, and it’s just a really boring thing to think and talk about. For me.
But I’m feeling guilty after turning down a bunch of requests to do shit for International Women’s Day next week. So I’m gonna do a thing I’ve been avoiding doing for years, and write down my (deeply problematic but practical) advice.
Toughen up. For your first 10 years or 3 jobs in the industry, you’re a junior contributor. You need them way more than they need you, so suck it up. Try not to dwell on the bullshit. Work hard and level up and always angle for more money and power when you can.
Stay technical. There are a thousand paved ramps out of engineering roles and only a few hard paths back in. Technical excellence is currency in this industry, even more so if your credibility is gonna get challenged again and again. So don’t stop engineering til you’re great at it.
Use your power for good. Once you become a senior contributor — and i’m not talking bullshit titles but real seniority, when people are coming to you for help far more than you go to them — then you can afford to get sensitive. …On behalf of others. The research convincingly shows that women get punished for advocating for themselves, but not for advocating for others. It’s a sweet loophole, use it.
If you feel like table flipping out of tech, just remember the rest of the world is at LEAST as sexist as tech is, but without the money and power and ridiculous life-coddling. Where exactly do you think you’re going to go?
Don’t quit tech: quit your job. There are LOTS of tolerable-to-great companies out there. If you stay and suffer, you’re just rewarding the shitholes with your presence. Don’t reward the shitholes any more than you can help it.
Learn shit, save your money, amass great power. Then use it to fuck shit up.
I have a very cynical reaction to the word “values”, especially in the context of corporate entities. At best it’s a disingenuous marketing campaign, usually it’s more like a red blaring light shining on their degenerate hypocrisies and weakest aspirations.
But we’ve been doing a lot of hiring. And one day I realized that most of our top candidates were asking the same two questions: 1) how do technical decisions get made, and 2) what are our company values?
After a few rounds of stuttering and sounding like an idiot, I decided it was time to mayyyybe stop sounding like an idiot and come up with an answer.
But it’s hard to do something you don’t believe in, let alone something as cheesy and heart-on-your-sleeve as write a company values statement. So first I had to talk myself into believing it was worth doing. Which went something like this:
Candidates I respect seem to think this thing matters, therefore it must matter to me too.
Well, some are worse than others. The ones I feel cynical about are the worst. (Facebook’s were a running joke because nobody believed them)
I didn’t hate Linden Lab’s values .. until we stopped believing in them. Hmm, so what was valuable about them?
Well, people used them to help resolve conflicts and make decisions. Nice.
Ok, what else do I hate? Values that are overly broad or include their opposite (“we work hard AND play harder”, “we’re empathetic BUT tough-minded”), are overly generic or too obvious (“no assholes” — duh), are unmemorable laundry lists, or too angelic and earnest (this list is not going to get you laid, capitalist scum).
Ok. So. Our values should be particular (they should not apply just as well to any other company), they should help make decisions and resolve conflict (if they aren’t useful/if we don’t use them then what’s the point), they should be pithy and a bit snarky (an aesthetic choice, just a spoonful of bile to help the medicine go down).
I started jotting down values fodder on my phone, while walking back and forth between home and work, which is how I do all my writing these days. I spent a couple weeks spewing notes out. It was a mess.
Then I sat down with Ginsu, my wizard of a COO, because I knew[*] he had the unique power to sift through my ramblings and craft a pithy message from vast effluvia. After bouncing it around a bit and soliciting everyone’s feedback, we were left with this list, which we quietly back-posted.
What I love about the list that it is specific, actionable, and truly echoes things we say every day to each other (“Everything is an experiment”, “Fast and mostly-right is better than slow and perfect”, and “We hire adults”), as well as bringing bits of our heritage (“Feedback is a gift”is lifted from Facebook; “Do it with style” comes from Linden Lab).
I like that I overhear people repeating the phrases to each other as they do their work and argue and urge each other on. I even love that there are huge, known flaws with it (“do it with style” notoriously does not scale) because that reminds me this is a living document, that we have committed to its care and feeding and regular revisioning.
I even love that you may read it and think, “This place is not for me.” If a place is for everyone, it is not for anyone in particular. I am okay with being a particular place, for particular people at a particular time in our lives. Specificity elicits passion in a way that generic never can.
Nothing lasts forever. As we close this round of funding and the end of the beginning chapter of this company, it’s nice to take a breath, pause, and put a stamp on it.
Lately I’ve been doing some career counseling for people off Twitter (long story). The central drama for many people goes something like this:
“I’m a senior engineer, but I’m thinking about being a manager. I really like engineering, but I feel like I’m just solving the same problems over and over and it seems like the real problems are people problems. I have to be a manager to get promoted. I hope it isn’t terrible, once I make the switch. I hear it’s terrible.”
I’ve been meaning to write this post for a while. There’s a lot but let’s start with: Fuck the whole idea that only managers get career progression. And fuckkkk the idea you have to choose a “lane” and grow old there. I completely reject this kind of slotting.
“Your advice is bad and you should feel bad”:
The best frontline eng managers in the world are the ones that are never more than 2-3 years removed from hands-on work, full time down in the trenches. The best individual contributors are the ones who have done time in management.
And the best technical leaders in the world are often the ones who do both. Back and forth. Like a pendulum.
I’ve done this a few times myself now; start out as an early or first infra engineering hire, build the stack, then build the team, then manage the team, then … leave and start it all over again. I get antsy, I get restless. I start to feel like I know what I’m doing (… a telltale sign something’s wrong).
It’s a good cycle for people who like early stage companies, or have ADD. But I don’t see people talking about it as a career path. So I’m here to advocate for it, as an intentional and awesome way of life.
There are lots of people who do both well - but serially. Not simultaneously.
(h/t to @sarahmei who was tweetstorming this up at the EXACT SAME TIME as i was writing this. Yes Virginia, internet feminists ARE linked by a mystical hive brain.)
On being a manager (of technical projects)
Promoting managers from within means you get those razor sharp skills from the people who just built the thing. That gives them credibility, while they struggle with their newly achieved incompetence in a different role.
That’s one of the only ways you can achieve the temporary glory of a hybrid manager+tech lead. This is an unstable combination, because your engineering skills and context-sharpness are decaying the longer you do it.
You can only really improve at one of these things at a time: engineering or management. And if you’re a manager, your job is to get better at management. Don’t try to cling to your former glory.
Management is highly interruptive, and great engineering — where you’re learning things — requires blocking out interruptions. You can’t do these two opposite things at once. As a manager, it is your job to be available for your team, to be interrupted. It is your job to choose to hand off the challenging assignments, so that your engineers can get better at engineering.
5. Both code and people require the same thing to thrive: focused, sustained attention. No one does both well.
Conversely: the best tech leads in the world are always the ones who done time in management. This is not because they’re always the best programmers or debuggers; it’s because they know how to get shit done, which means they know how to communicate and manage other people.
A tech lead is a manager … but their first priority is achieving the task at hand, not grooming and minding the humans who work on it.
They still need the full manager toolset. They’ll need to know how to rally people and teams and motivate them, or how to triage and restart a stalled project that everybody dreads. They still need to connect the dots between business objectives and technical objectives, and break down big objectives into components. They need to be able to size up a junior engineer’s ability and craft a meaningful assignment, one that pushes their boundaries without crushing them … then do the same for another twenty contributors. This is management work, from the slightly shifted perspective of “Get Thing X Done” not “care for these people”.
So these tech leads usually spend more time in meetings than building things, and they will bitch about it but do it anyway, because writing code is not the best use of their time. Tech is the easy part, herding humans is the harder part.
Senior engineers who have both these toolsets are the kind of tech leads you can build an org around, or a company around. They get shit done. And they are rare.
Almost all of them have spent considerable time in management.
We don’t talk about this nearly enough: the immense breadth and strength that accrues to engineers who make a practice of going back and forth.
Being an IC is like reverse-engineering how a company works with very little information. A lot of things seem ridiculous, or pointless or inefficient from the perspective of a leaf node. .
Being a manager teaches you how the business works. It also teaches you how people work. You will learn to have uncomfortable conversations. You will learn how to still get good work out of people who are irritated, or resentful, or who hate your guts. You will learn how to resolve conflicts, dear god will you ever learn to resolve conflicts. (Actually you’ll learn to YEARN for conflicts because straightforward conflict is usually better than all the other options.) You’ll go home exhausted every day and unable to articulate anything you actually did. But you did stuff.
You’ll miss the dopamine hit of fixing something or solving something. You’ll miss it desperately.
One last thing about management. There’s a myth that makes it really hard for people to stop managing, even when it makes them and everyone around them miserable. And that’s the idea that management is a promotion.
Management is NOT a promotion.
1. Becoming a manager is not a promotion - it's a lateral move onto a parallel track. You're back at junior level in many key skills.
Seriously, fuck that so hard. It is SUCH an insidious myth, and it leads to so many people managing even though they hate managing and have no business managing, and also starves the senior eng pool of the great mentors and elder wizards we need.
Management is not a promotion, management is a change of profession.And you will be bad at it for a long time after you start doing it. If you don’t think you’re bad at it, you aren’t doing your job.
Managing because it feeds your ego is a terrific way to be sure that your engineers get to report to someone miserable and resentful, someone who should really be writing code
or finding something else that brings them joy.
There’s nothing worse than reporting to someone forced into managing. Please don’t be one of the reasons people burn out hard on tech.
It isn’t a promotion, so you don’t have any status to give up. Do it as long as it makes you happy, and the people around you happy. Then stop. Go back to building things. Wait til you get that itch again.
This morning there was yet another comment thread on hacker news about Yet Another outage involving MongoDB and data loss, this time by some company called “CleverTap”.
To summarize: the CleverTap engineering team noticed that the WiredTiger storage engine was faster than MMAPv1 for MongoDB. They decided to … “upgrade the following weekend” (that sentence alone made my eyes bulge).
According to the blog post, they upgraded from 2.6 to 3.0, while simultaneously changing storage engines from MMAPv1 to WiredTiger, while leaving zero secondaries snapshot nodes with data on MMAPv1. All over the course of 3 days.
(They are also running sharded mongo, with a mere 300 ops/sec on each primary, which RAISES A LOT OF QUESTIONS but I already feel like I’m beating up on these kids so I won’t pursue that.)
(But seriously what the *hell* can you be doing to have such a low request rate, that you
need to shard at an infinitesimal volume? Why did you specify it in req/min instead of req/sec? What is the breakdown of reads/writes? What is the lock percentage? What is the avg object size?? Are these like multi-MB documents???? Why did you pause all incoming traffic and process it after the upgrade? If the primary can’t take the extra load, why not rs.syncFrom() a secondary? If that doesn’t work, don’t you have other, bigger problems??)
Most bafflingly of all: why wait only a few minutes after electing a new WiredTiger primary for the first time ever, and then immediately DELETE your only known-good copies of the data on MMAPv1 and re-sync over them with WiredTiger?
Okay. So here’s the thing: you are clearly a team of accidental DBAs. You are operations and software engineers who have found yourselves in charge of the data.
It’s cool. I am too! It’s a really neat and fun place to be in. DBAs and network admins are kind of the last remaining priesthoods in our industry.
There’s a lot of powerful and fun stuff to be done for generalists who pick up specialty knowledge in one of those areas, or specialists (like my neteng friend Leslie) who start bringing their skills back to the generalist side and merging the two.
(Oh Right, We Wrote A Book About This!!!)
My friend Laine and I are writing a book for people on the data side, called “Database Reliability Engineering“, which is aimed at generalist engineers who want to learn how to deal with data responsibly and effectively.
(Actually that’s a good point, I am supposed to be pitching this book! — which is really mostly Laine with a smidgen of me but it’s going to be super awesome. Consider this your sales pitch.)
So first, as an accidental DBA, you should obviously buy this book :). Second: stateful services require a different mindset[*]. It’s cool that you are running your own databases! But reading post mortems like this where the conclusion is “MongoDB sucks” makes me fucking grind my teeth.
Stop treating your databases like stateless services.
There are lots of ways that MongoDB (and every other database on the planet) really sucks. Mongo set themselves up for special rage by overpromising too much early on, and seeming tone deaf to criticism from real database engineers.
But *I* can criticize Mongo all day long. You children on hacker news who have never run it don’t get to. 😛 If you don’t know what the fuck you’re talking about, if you’re cargo culting other people’s years-old complaints, just shut up already.
Managing stateful services like databases means that you need to be more paranoid than you did with stateless services. With stateless services the best practices are to to roll early, roll fast, roll often, roll back. When you’re dealing with state, you need to be careful.
With stateful services you can’t play it fast and loose like that. You’re going to have data loss, corruption, unpredictable results, catastrophic failures that you can’t simply roll back from. Data loss can be ruinous to your company. (This can also be true for stateless services that sit close to your data and mutate it a lot.)
But that’s what makes it fun. 🙂
When we were moving from MMAPv1 to RocksDB at Parse, we ran hybrid replica sets for 6-9 months. We were paranoid. It was justified! We spent half a year capturing production workloads and replaying them, electing Rocks primaries and rolling back, and even then keeping snapshots and secondaries of both storage engines for *months*.
This isn’t because MongoDB sucks. It’s the nature of the game, it’s the difference between stateful and stateless services.
Do you know that there was a total query engine rewrite in 2.6? We spent months flushing out tons of crazy bugs. Do you know about the index intersection changes? We helped chase down bugs in those too. (You’re welcome.)
You can’t just go “dudes it’s faster” and jump off a cliff. This shit is basic. Test real production workloads. Have a rollback plan. (Not for *10 days* … try a month or two.)
If CleverTap had run their plan past anyone experienced with data, they would have called out all of those completely predictable failures, and advised them to change it:
Make one change at a time. Do a major version upgrade separately from the storage engine upgrade.
Delay between each change. Two weeks is absolutely minimal, any thing less is careless. Let them bake.
Storage engine changes are scary. It takes years to gain confidence in a new way of laying bits down on disk. (Whenever people bitch and moan about mongo, I remind them that I’ve still lost WAY more data to MyISAM, InnoDB, and MySQL overall than Mongo.
You can run lots and lots of replicas (up to 7 votes per replica set, even more nodes) per each replica set in Mongo. This is a killer feature. Why didn’t you use it?
Keep backups around for months in the new storage engine *and* the old storage engine, just in case. Have two hidden snapshot nodes. The only cost is in dollars, which is fucking cheap compared to data or engineering time.
If you are a new accidental DBA, you have to make a point of learning things. Go to conferences. Read books. Buy bottles of whiskey for your data friends and pick their brains. Remember that they know things you do not. Don’t blame the vendors when you fucked up.
Network engineering is the same way, but mistakes tend to be a lot less … permanent. You drop some packets.. like grains of sand. ^_^
Remember that you’re in charge of keeping people’s data safe and secure. You have much to learn. Learn it.
And get off my fucking lawn. ❤
Some slides from a couple of relevant talks I’ve given on the subject:
[*] P.S.: “Stop treating your stateful services like stateless services” … this is a fact, but it’s not the aspiration. DB folks should all be leaning in to the model of learning to treat our stateful services like stateless services, with the same casual disregard for individual nodes. This is hard, and it’s going to take some time, but it’s clearly where the world is heading and it’s definitely a good thing. 🙂 The learning goes both ways!
Last week was the West Coast Velocity conference. I had a terrific time — I think it’s the
best Velocity I’ve been to yet. I also slipped in quite late, the evening before last, to catch Gareth’s session on DevOps vs SRE.
And it was worth it! Holy crap, this was such a fun barnburner of a talk, with Gareth schizophrenically arguing both for and against the key premise of the talk, which was about “Google Infrastructure for Everyone Else (GIFEE)” and whether SRE is a) the highest, noblest goal that we should all aspire towards, or b) mostly irrelevant to anyone outside the Google confines.
Which Gareth won? Check out the slides and judge for yourself. 🙃
At some point in his talk, though, Gareth tossed out something like “Charity probably already has a blog post on this drafted up somewhere.” And I suddenly remembered “Fuck! I DO!” it’s been sitting in my Drafts for months god dammit.
So this is actually a thing I dashed off back in April, after CraftConf. Somebody asked me for my opinion on the internet — always a dangerous proposition — and I went off on a bit of a rant about the differences and similarities between DevOps and SRE, as philosophies and practices.
Time passed and I forgot about it, and then decided it was too stale. I mean who really wants to read a rehash of someone’s tweetstorm from two months ago?
Well Gareth, apparently.
SRE vs DevOps: TWO PHILOSOPHIES ENTER, BOTH ARE PHENOMENALLY SUCCESSFUL AND MUTUALLY DUBIOUS OF ONE ANOTHER
It also has some really fucking obnoxious blurbs. Things like about how “ONLY GOOGLE COULD HAVE DONE THIS”, and an whiff of snobbery throughout the book as though they actually believe this (which is far worse if true).
You can’t really blame the poor blurb’ers, but you can certainly look askance at a massive systems engineering org when it seems as though they’ve never heard of DevOps, or considered how it relates to SRE practices, and may even be completely unaware of what the rest of the industry has been up to for the past 10-plus years. It’s just a little weird.
So here, for the record, is what I said about it.
1) a lot of the philosophical volleying between devops / SRE comes down to a failure to recognize the overwhelming power of context.
Google is a great company with lots of terrific engineers, but you can only say they are THE
BEST at what they do if you’re defining what they do tautologically, i.e. “they are the best at making Google run.” Etsyans are THE BEST at running Etsy, Chefs are THE BEST at building Chef, because … that’s what they do with their lives.
Context is everything here. People who are THE BEST at Googling often flail and flame out in early startups, and vice versa. People who are THE BEST at early-stage startup engineering are rarely as happy or impactful at large, lumbering, more bureaucratic companies like Google. People who can operate equally well and be equally happy at startups and behemoths are fairly rare.
And large companies tend to get snobby and forget this. They stop hiring for unique strengths and start hiring for lack of weaknesses or “Excellence in Whiteboard Coding Techniques,” and congratulate themselves alot about being The Best. This becomes harmful when it translates into to less innovation, abysmal diversity numbers, and a slow but inexorable drift into dinosaurdom.
2) operations engineering is a specialized skill set *at large scale* or *on hard ops problems*. many -- most? companies don't have those.
Everybody thinks their problems are hard, but to a seasoned engineer, most startup problems are not technically all that hard. They’re tedious, and they are infinite, but anyone can figure this shit out. The hard stuff is the rest of it: feverish pace, the need to reevaluate and reprioritize and reorient constantly, the total responsibility, the terror and uncertainty of trying to find product/market fit and perform ten jobs at once and personally deliver to your promises to your customers.
At a large company, most of the hardest problems are bureaucratic. You have to come to terms with being a very tiny cog in a very large wheel where the org has a huge vested interest in literally making you as replicable and replaceable as possible. The pace is excruciatingly slow if you’re used to a startup. The autonony is … well, did I mention the politics? If you want autonomy, you have to master the politics.
3) the outcomes associated with operations (reliability, scalability, operability) are the responsibility of *everyone* from support to CEO.
Everyone. Operational excellence is everyone’s job. Dude, if you have a candidate come in and they’re a jerk to your office manager or your cleaning person, don’t fucking hire that person because having jerks on your team is an operational risk (not to mention, you know, like moral issues and stuff).
But the more engineering-focused your role is, the more direct your impact will be on operational outcomes.
4) therefore, the more literate you are with operational skills, the more effective and powerful you can be -- esp as a software engineer.
As a software engineer, developing strong ops chops makes you powerful. It makes you better at debugging and instrumentation, building resiliency and observability into your own systems and interdependent systems, and building systems that other people can come along and understand and maintain long after you’re gone.
As an operations engineer, those skills are already your bread and butter. You can increase your power in other ways, like by leveling up at software engineering skills like test coverage and automation, or DBA stuff like query optimization and storage engine internals, or by helping the other teams around you level up on their skills (communication and persuasion are chronically underrecognized as core operations engineering skills).
5) specialization is not a bad thing. specialization is how we scale and do capitalism! the problem is when this becomes compartmentalizing.
This doesn’t mean that everyone can or should be able to do everything. (I can’t even SAY the words “full stack engineer” without rolling my eyes.) Generalists are awesome! But past a certain inflection point, specialization is the only way an org can scale.
It’s the only way you make room for those engineering archetypes who only want to dive deep, or who really really love refactoring, or who will save the world then disappear for weeks. Those engineers can be incredibly valuable as part of a team … but they are most valuable in a large org where you have enough generalists to keep the oars rowing along in the meantime.
6) so: Google SRE has an incredibly powerful set of best practices, that enable them to run the largest site in the world incredibly well.
So, back to Google. They’ve done, ahem, rather well for themselves. Made shitbuckets of money, pushed the boundaries of tech, service hardly ever goes down. They have operational demands that most of us never have seen and never will, and their engineers are definitely to be applauded for doing a lot of hard technical and cultural labor to get there.
Mostly because it comes off a little tone deaf in places. I’m not personally pissed off by
the google SRE book, actually, just a little bemused at how legitimately unaware they seem to be about … anything else that the industry has been doing over the past 10 years, in terms of cultural transformation, turning sysadmins into better engineers, sharing on-call rotations, developing processes around empathy and cross-functionality, engineering best practices, etc.
If you try and just apply Google SRE principles to your own org according to their prescriptive model, you’re gonna be in for a really, really bad time.
However, it happens that Jen Davis and Katherine Daniels just published a book called Effective DevOps, which covers a lot of the same ground with a much more varied and inclusive approach. And one of the things they return to over and over again is the power of context, and how one-size-fits-all solutions simply don’t exist, just like unisex OSFA t-shirts are a dirty fucking lie.
Google insularity is … a thing. On the one hand it’s great that they’re opening up a bit! On the other hand it’s a little bit like when somebody barges onto a mailing list and starts spouting without skimming any of the archives. And don’t even get me started on what happens when you hire long, longterm ex-Googlers back into to the real world.
So, so many of us have had this experience of hiring ex-Googlers who automatically assume that the way Google does a thing is CORRECT, not just contextually appropriate. Not just right for Google, but right for everyone, always. Which is just obviously untrue. But the reassimilation process can be quite long and exhausting when the Kool-Aid is so strong.
8) DevOps as a philosophy is much more sensitive to context than SRE philosophy, because it grew from a broader collaborative base.
Because yeah, this is a conversation and a transformation that the industry has been having for a long time now. Compared with the SRE manifesto, the DevOps philosophy is much more crowd-sourced, more flexible, and adaptable to organizations of all stages of developments, with all different requirements and key business differentiators, because it’s benefited from loud, mouthy contributors who aren’t all working in the same bubble all along.
And it’s like Google isn’t even aware this was happening, which is weird.
9) that's it, basically all i'm saying is "all blanket statements are false" including probably this one 🙂 #devops#sre
Orrrrrr, maybe I’m just a wee bit annoyed that I’ve been drawn into this position of having to defend “DevOps”, after many excellent years spent being grumpy about the word and the 10000010101 ways it is used and abused.
(Tell me again about your “DevOps Engineering Team”, I dare you.)
(^^ thanks to @kellan and others who particularly influenced/clarified my thinking around #8, the crowdsourcing of devops)
P.S. I highly encourage you to go read the epic hours-long rant by @matthiasr that kicked off the whole thing. some of which I definitely endorse and some of which not, but I think we could go drink whiskey and yell about this for a week or two easy breezy ❤
So, a few hot takes on that …
1) SRE, as practiced by Google, is really just Ops with a lot of management support
The theme of my talk was basically: what should software engineers know and care about when it comes to operations in a world where we are outsourcing more and more core functionality?
If you care about running a quality service or product, or providing your customers with a reasonable level of service, you have to care about operational concerns like design, resiliency, instrumentation and debuggability. No matter how many abstractions there are between you and the bare metal.
If you chose a provider, you do not get to just point your finger at them in the post mortem and say it’s their fault. You chose them, it’s on you. It’s tacky to blame the software or the service, and besides your customers don’t give a shit whose “fault” it is.
So given an infinite number of things to care about, where do you start?
What is your mission, and what are your differentiators?
The first question must always be: what is your mission? Your mission is not writing software. Your mission is delivering whatever it is your customers are paying you for, and you use software to get there. (Code is kind of a liability so you should write as little of it as necessary. hey!! sounds like a good argument for #serverless!)
Second: what are your core differentiators? What are the things that you are doing that are unique, and difficult to replicate, or the things where you have to actually be world class experts in those things?
Those are the things that you will have the hardest time outsourcing, or that you should think about very carefully before outsourcing.
You can outsource labor, but you can’t outsource caring. And nobody but you is in the position to think about your core differentiators and your product in a holistic way.
If you’re a typical early startup, you’re probably using somewhere between 5 and 20 SaaS products to get rid of some of the crap work and offload it to dedicated teams who can do it better than you can, much more cheaply, so you are freed up to work on your core value proposition.
But you still have to think about things like reliability, your security model, your persistent storage models, your query performance, how all these lovely services talk to each other, how you’re going to debug them, how you’re going to repro when things go wrong, etc. You still own these things, even if you don’t run them.
For example, take AWS Lambda. It’s a pretty great service on many dimensions. It’s an early version of the future. It is also INCREDIBLY irritating and challenging to debug in a practically infinite number of insanity-inducing ways.
** Important side note — I’m talking about actual production systems. Parse, Heroku, Lambda, etc are GREAT for prototyping and can take you a long, long way. Early stage startups SHOULD optimize for agility and rapid developer iteration, not reliability. Thx to @joeemison for reminding me that i left that out of the recap.
Focus on the critical path
Your users don’t care if your internal jenkins builds are broken. They don’t care about a whole lot of things that you have to care about … eventually. They do care a lot if your product isn’t actually functional. Which means you have to think through the behavioral and failure characteristics of the providers you’re relying on in any user visible fashion.
Ask lots of questions if you can. (AWS often won’t tell you much, but smaller providers will.) Find out as much as you can about their cotenancy model (shared hardware or isolation?), their typical performance variance (run your own tests, don’t trust their claims), and the underlying storage systems.
Think about how you can bake in resiliency from the user’s perspective, that doesn’t rely on provider guarantees. If you’re on mobile, can you provide a reasonable offline experience? Like Parse did a lot of magic here in the APIs, where it would back off and retry saves if there were any errors.
Can you fail over to another provider if one is down? Is it even worth it at your company’s stage of maturity and engineering resources to invest in this?
How willing are you to be locked into a vendor or provider, and what is the story if you find yourself forced to switch? Or if that service goes away, as so many, many, many of them have done and will do. (RIP, parse.com.)
Listen, outsourcing is awesome. I do it as much as I can. I’m literally helping build a service that provides outsourced metrics, I believe in this version of the future! It’s basically the latest iteration of capitalism in a nutshell: increased complexity –> increased specialization –> you pay other people to do the job better than you –> everybody wins.
But there are tradeoffs, so let’s be real.
The service, if it is smart, will put strong constraints on how you are able to use it, so they are more likely to deliver on their reliability goals. When users have flexibility and options it creates chaos and unreliability. If the platform has to choose between your happiness vs thousands of other customers’ happiness, they will choose the many over the one every time — as they should.
Limits may mysteriously change or be invented as they are discovered, esp with fledgling services. You may be desperate for a particular feature, but you can’t build it. (This is why I went for Kafka over Kinesis.)
You need to think way more carefully and more deeply about visibility and introspection up front than you would if you were running your own services, because you have no ability to log in and use strace or gdb or tail a logfile or run any system profiling commands when things go dark.
In the best case, you’re giving up some control and quality in exchange for experts doing the work better than you could for cheaper (e.g. i’m never running a fucking physical data center again, jesus. EC24lyfe). In a common worse case, it’s less reliable than what you would build AND it’s also opaque AND you can’t tell if it’s down for you or for everyone because frankly it’s just massively harder to build a service that works for thousands/millions of use cases than for any one of them individually.
Ohhhh and let’s just briefly talk about state.
The serverless utopia mostly ignores the problems of stateful services. If pressed they will usually say DynamoDB, or Firebase, or RDS or Aurora or something.
Real question how does state get persisted with #serverless?
I understand scale out of stateless servers, but who stores the state?
This is a big, huge, deep, wide lake of crap to wade in to so all I’m going to say is that there is no such thing as having the luxury of not having to understand how your storage systems work. Queries will get slow, and you’ll need to be able to figure out why and fix them. You’ll hit scaling cliffs where suddenly a perfectly-usable app just starts timing everything out because of that extra second of latency coming from …
The hardware underlying your instance will degrade (there’s a server somewhere under all those abstractions, don’t forget). The provider will have mysterious failures. They will be better than you, probably, but less inclined to give you satisfactory progress updates because there are hundreds or thousands or millions of you all clamoring.
The more you understand about your storage system (and the more you stay in the lane of how it was intended to be used), the happier you’ll be.
These trends are both inevitable and, for the most part, very good news for everyone.
Operations engineering is becoming a more fascinating and specialized skill set. The best engineers are flocking to solve category problems — instead of building the same system at company after company, they are building SaaS solutions to solve it for the internet at large. Just look at the massive explosion in operational software offerings over the past 5-6 years.
This means that the era of the in-house dedicated ops team, which serves as an absorbent buffer for all the pain of software development, is mostly on its way out the door. (And good riddance.)
People are waking up to the fact that software quality improves when feedback loops are tighter for software engineers, which means being on call and owning services end to end. The center of gravity is shifting towards engineering teams owning the services they built.
This is awesome! You get to rent engineers from Google, AWS, Pagerduty, Pingdom, Heroku, etc for much cheaper than if you hired them in-house — if you could even get them, which you probably can’t because talent is scarce.
But the flip side of this is that application engineers need to get better at thinking in traditionally operations-oriented ways about reliability, architecture, instrumentation, visibility, security, and storage. Figure out what your core differentiators are, and own the shit out of those.
Nobody but you can care about your mission as much as you can. Own it, do it. Have fun.
I just got back from the very first ever @serverlessconf in NYC. I have a soft spot for well-curated single-track conferences, and the organizers did an incredible job. Major kudos to @iamstan and team for pulling together such a high-caliber mix of attendees as well as presenters.
I’m really honored that they asked me to speak. And I had a lot of fun delivering my talk! But in all honesty, I turned it down a few times — and then agreed, and then backed out, and then agreed again at the very last moment. I just had this feeling like the attendees weren’t going to want to hear what I was gonna say, or like we weren’t gonna be speaking the same language.
Which … turned out to be mmmmostly untrue. To the organizers’ credit, when I expressed this concern to them, they vigorously argued that they wanted me to talk *because* they wanted a heavy dose of real talk in the mix along with all the airy fairy tales of magic and success.
So #serverless is the new cloud or whatever
Hi, I’m grouchy and I work with operations and data and backend stuff. I spent 3.5 years helping Parse grow from a handful of apps to over a million. Literally building serverless before it was cool TYVM.
So when I see kids saying “the future is serverless!” and “#NoOps!” I’m like okay, that’s cute. I’ve lived the other side of this fairytale. I’ve seen what happens when application developers think they don’t have to care about the skills associated with operations engineering. When they forget that no matter how pretty the abstractions are, you’re still dealing with dusty old concepts like “persistent state” and “queries” and “unavailability” and so forth, or when they literally just think they can throw money at a service to make it go faster because that’s totally how services work.
I’m going to split this up into two posts. I’ll write up a recap of my talk in a sec, but first let’s get some things straight. Like words. Like operations.
What is operations?
Let’s talk about what “operations” actually means, in the year 2016, assuming a reasonably high-functioning engineering environment.
At a macro level, operational excellence is not a role, it’s an emergent property. It is how you get shit done.
Operations is the sum of all of the skills, knowledge and values that your company has built up around the practice of shipping and maintaining quality systems and software.It’s your implicit values as well as your explicit values, habits, tribal knowledge, reward systems.Everybody from tech support to product people to CEO participates in your operational outcomes, even though some roles are obviously more specialized than others.
Saying you have an ops team who is solely responsible for reliability is about as silly as saying that “HR defines and owns our company culture!” No. Managers and HR professionals may have particular skills and responsibilities, but culture is an emergent property and everyone contributes (and it only takes a couple bad actors to spoil the bushel).
Thinking about operational quality in terms of “a thing some other team is responsible for” is just generally not associated with great outcomes. It leads to software engineers who are less proficient or connected to their outcomes, ops teams who get burned out, and an overall lower quality of software and services that get shipped to customers.
These are the specialized skill sets that I associate with really good operations engineers. Do these look optional to you?
It depends on your mission, but usually these are not particularly optional. If you have customers, you need to care about these things. Whether you have a dedicated ops team or not. And you need to care about the tax it imposes on your humans too, especially when it comes to the cognitive overhead of complex systems.
So this is my definition of operations. It doesn’t have to be your definition. But I think it is a valuable framework for helping us reason about shipping quality software and healthy teams. Especially given the often invisible nature of operations labor when it’s done really well. It’s so much easier to notice and reward shipping shiny features than “something didn’t break”.
The inglorious past
Don’t get me wrong — I understand why “operations” has fallen out of favor in a lot of crowds. I get why Google came up with “SRE” to draw a line between what they needed and what the average “sysadmin” was doing 10+ years ago.
Ops culture has a number of well-known and well-documented pathologies: hero/martyr complexes, risk aversion, burnout, etc. I understand why this is offputting and we need to fix it.
Also, historically speaking, ops has attracted a greater proportion of nontraditional oddballs who just love debugging and building things — fewer Stanford CS PhDs, more tinkerers and liberal arts majors and college dropouts (hi). And so they got paid less, and had less engineering discipline, and burned themselves out doing too much ad hoc labor.
But — this is no longer our overwhelming reality, and it is certainly not the reality we are hurtling towards. Thanks to the SRE movement, and the parallel and even more powerful & diverse open source DevOps movement, operations engineers are … engineers. Who specialize in infrastructure. And there’s more value than ever in empathy and fluid skill sets, in engineers who are capable of moving between disciplines and translating between specialties. This is where the “full-stack developer” buzzword comes from. It’s annoying, but reflects a real craving for generalist skill sets.
The BOFH stereotype is dead. Some of the most creative cultural and technical changes in the technical landscape are being driven by the teams most identified with operations and developer tooling. The best software engineers I know are the ones who consistently value the impact and lifecycle of the code they ship, and value deployment and instrumentation and observability. In other words, they rock at ops stuff.
The Glorious Future
And so I think it’s time to bring back “operations” as a term of pride. As a thing that is valued, and rewarded. As a thing that every single person in an org understands as being critical to success. Every organization has unique operational needs, and figuring out what they are and delivering on them takes a lot of creativity and ingenuity on both the cultural and technical front.
“Operations” comes with baggage, no doubt. But I just don’t think that distance and denial are an effective approach for making something better, let alone trash talking and devaluing the skill sets that you need to deliver quality services.
You don’t make operational outcomes magically better by renaming the team “DevOps” or “SRE” or anything else. You make it better by naming it and claiming it for what it is, and helping everyone understand how their role relates to your operational objectives.
And now that I have written this blog post I can stop arguing with people who want to talk about “DevOps Engineers” and whether “#NoOps” is a thing and maybe I can even stop trolling them back about the nascent “#NoDevs” movement. (Haha just kidding, that one is too much fun.)
I mean how hard can it be to just glue together APIs that other people have written and support and scale? 🤔 #serverless#NoDevs