Platform engineering is the newest buzzword in IT operations. And like all different buzzwords, it’s at risk of changing into meaningless—at risk of which means no matter some firm with a “platform engineering” product desires to promote. We’ve seen that occur to too many helpful ideas: Edge computing meant every thing from caches at a cloud supplier’s information heart to cell telephones to unattended information assortment nodes on distant islands. DevOps meant, effectively, no matter anybody wished. Culture? Job title? A specialised group inside IT?
We don’t need that to occur to platform engineering. IT operations at scale is simply too necessary to depart to likelihood. In her forthcoming e book Platform Engineering, Camille Fournier notes that platform engineering has been used to imply something from an ops group wiki to dashboards to APIs to container orchestration with Kubernetes. All of those have some bearing on platform engineering. But none of them are platform engineering. Taken collectively, they sound just like the story of blind males describing an elephant: one grabs maintain of a tusk, one other the tail, one other a leg, however none of them have an image of the entire. Camille gives a holistic definition of platform engineering: “a product approach to developing internal platforms that create leverage by abstracting away complexity, being operated to provide reliable and scalable foundations, and by enabling application engineers to focus on delivering great products and user experiences.” (Emphasis Camille’s.)
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That sounds summary, nevertheless it’s each exact and useful. “A product approach” is a theme that comes up repeatedly in discussions of platform engineering: treating the platform as a product and software program builders—the customers of the platform—as prospects, and constructing with the client’s wants in thoughts. There’s been numerous speak concerning the loss of life of DevOps; there was even a short NoOps motion. But as Charity Majors identified at PlatformCon 2023, the fact of operations engineering is that it has turn out to be fantastically complicated. The time when “operations” meant racking a couple of servers and putting in Apache and MySQL is lengthy gone. While cloud suppliers have taken over the racking, stacking, and software program set up, they now supply scores of providers, every of which must be configured appropriately. Applications have grown extra complicated too: we now have fleets of microservices working asynchronously throughout lots of or 1000’s of cloud situations. And as purposes have turn out to be extra complicated, so has operations. It’s been years since operations meant mumbling magical incantations into server consoles. That’s not repeatable; that’s not scalable; that’s not dependable. Unfortunately, we’ve ended up with a unique downside: fashionable software program methods can solely be operated by the builders who created them.
The downside is that software program engineers need to do what software program engineers do finest, and that’s write cool new purposes. They don’t need to turn out to be consultants within the particulars of hosted Kubernetes, complicated guidelines for id, authentication, and entry administration (IAM), monitoring and observability, or any of the opposite duties which have turn out to be a part of their workspace. What’s wanted is a brand new set of abstractions that permits each builders and operations employees to maneuver to a better stage.
That will get to the guts of platform engineering: abstracting away complexity (in Camille’s phrases) or making builders more practical (in Charity’s). How can we develop software program within the twenty first century? Can improved tooling make builders more practical by working round productiveness roadblocks? Can we let operations employees fear about points like service-level agreements (SLAs) and uptime? Can operations employees care for complicated points like load balancing, enterprise continuity, and failover, which the purposes builders use by way of a set of well-designed abstractions? That’s the problem of platform engineering. Developers have sufficient complexity to fret about with out taking up operations.
The fantasy of platform engineering is “one-click deployment”: write your utility and click on on a “deployment” merchandise in your management panel, and the appliance strikes easily and painlessly by way of testing, integration, and deployment. Life is sort of by no means that easy. Deployment itself isn’t a easy idea, what with canary deployments, A/B testing, rollbacks, and so forth.
But there’s a actuality, and behind that actuality are some actual successes. Facebook used to speak about requiring new hires to deploy one thing to its website on their first day at work. This predates “platform engineering,” “developer platforms,” and all of that, nevertheless it clearly reveals that abstractions that simplify software program deployment in a fancy setting aren’t new.
Writing about his expertise at LinkedIn in 2011, Kevin Scott (now CTO of Microsoft) describes how the corporate discovered itself in an enormous developmental mess simply because it went public. It was virtually unattainable to deploy new options: a number of years as a startup that was transferring quick and breaking issues had resulted in a tangled internet of conflicting processes and technical debt. “Automate all the things” was a robust slogan—however as enticing as that sounds, it has a really actual draw back. LinkedIn took the daring step of halting new growth for so long as it took to construct a constant platform for deploying software program. It ended up taking a number of months (and put a number of careers on the road, together with Scott’s), nevertheless it was finally successful. LinkedIn went from releasing new options as soon as a month, if that, to having the ability to launch a number of occasions a day.
What’s notably attention-grabbing about this story is that, writing a number of years after the very fact, Scott makes use of not one of the language that we now affiliate with “platform engineering.” He doesn’t speak about developer expertise, inside developer platform, or any of that. But what his group clearly achieved was platform engineering of the best order—and that most likely saved LinkedIn as a result of, regardless of its extremely profitable IPO, an online startup that may’t deploy is lifeless within the water.
Walmart has an analogous story about bettering its DevOps and CI/CD practices. Daily deployment uncovered issues in instruments, procedures, and processes. These issues had been addressed by a DevOps group and had been forwarded to a platform group. Like the occasions recounted above, the work passed off within the 2010s. Also like Scott’s LinkedIn story, Walmart’s narrative doesn’t use the language that we now affiliate with platform engineering.
The Heroku platform as a service is one other instance of platform engineering’s prehistory. Heroku, which made its debut in 2007, made single-click deployment a actuality, at the very least for easy purposes. When programming with Heroku, you didn’t must know something concerning the cloud and little or no about tips on how to wire the database to your utility. Almost every thing was taken care of for you. While Heroku by no means went fairly far sufficient, it gave internet builders a style of what could be potential.
All of those examples make it clear that platform engineering isn’t something new. What we now name “platform engineering” consolidates practices which have been round for a while; it’s the pure evolution of actions like DevOps, infrastructure as code, and even the scripting of widespread upkeep duties. Whether they’re “software developers” as such or operations employees, folks within the software program trade have all the time constructed instruments to make their jobs simpler. Platform engineering places this tool-building on a extra rigorous and formal foundation: it acknowledges that constructing instruments and creating abstractions for complicated processes is engineering, not hacking. LinkedIn’s downside wasn’t a scarcity of tooling. It was a number of years of wildcat software growth and advert hoc options that ultimately became a mass of seething bits and choked out progress. The resolution was doing a greater job of engineering the corporate’s tooling to construct a constant and coordinated platform.
In “DevOps Isn’t Dead, But It’s Not in Great Health Either,” Steven Vaughan-Nichols argues that DevOps will not be delivering: solely 14% of firms can get software program into manufacturing in a day and solely 9% can deploy a number of occasions per day. To some extent, that is little question as a result of many organizations that declare to have adopted DevOps, CI/CD, and related concepts by no means actually change their practices or their tradition; they rename present practices with out altering something substantial. But it’s additionally true that software program deployment has turn out to be extra complicated and that, as LinkedIn realized, undisciplined software growth can lead to a mountain of technical debt. Architectural types like microservices decompose giant monoliths into smaller providers—however then the right configuration and deployment of these providers turns into a brand new bottleneck, a brand new nucleus round which technical debt can accumulate.
The listing of issues that platform engineering ought to resolve for software program builders will get lengthy shortly. It incorporates every thing from smoothing the trail from the developer’s laptop computer to a supply management repository to deploying software program to the cloud in manufacturing. The extra you look, the extra duties to simplify you’ll discover. Many safety issues consequence from incorrectly configured id, authorization, and entry administration (IAM). Can IAM be simplified in a method that stops errors? When AWS first appeared, we had been all amazed at how easy it was to spin up digital situations and retailer information. But provisioning a service that makes use of dozens of accessible providers and runs throughout 1000’s of situations, some within the cloud and a few on-premises, is much from easy. Getting it improper can result in a nightmare for efficiency and scaling. Can the burden of appropriately provisioning infrastructure be minimized? Deployment isn’t simply pushing one thing to a server or perhaps a fleet of servers; it might embody canary deployments, A/B testing, and rollback capabilities. Can these complicated deployment eventualities be simplified? Any deployment must take scaling under consideration; if software program can’t keep in mind the corporate’s present and near-term wants, it’s in hassle. Can a platform incorporate practices that simplify scalability? Failover and enterprise continuity within the occasion of outages, minimizing price by optimizing the scale of the server fleet, regulatory compliance—these are all points which can be necessary within the 2020s and that, if we’re being trustworthy, we actually didn’t assume a lot about 20 years in the past. Do builders want to fret about failover, or can or not it’s a part of the platform?
The key phrase in platform engineering isn’t “platform”; it’s “engineering.” Solid engineering is required to maneuver up the abstraction ladder, as Yevgeniy Brikman has stated. But what does that imply?
Definitions of platform engineering ceaselessly speak about treating the developer as a buyer. That can really feel very bizarre whenever you assume (or learn) about it. Your firm already has “customers.” Are your engineers “customers” too? But that shift in mindset from treating software program builders as a labor asset to prospects is essential. Camille Fournier means the identical factor when she writes about “a product approach to developing internal platforms”: a platform engineering group has to take its prospects critically, has to perceive what the purchasers’ issues are, and has to provide you with efficient options to these issues.
Platform engineering has the identical pitfalls as different kinds of product growth. It’s necessary to construct for the client, not for the engineer designing the product. Techno-solutionism—considering that each one issues might be solved by making use of state-of-the-art expertise—normally degenerates into implementing concepts as a result of they’re cool, not as a result of they’re applicable. It virtually all the time imposes options from exterior the issue house, forcing one group’s concepts on prospects with out considering adequately concerning the prospects’ wants. It’s poor engineering. Good engineering might require sitting within the buyer’s chair and performing their duties typically sufficient to get a very good really feel for his or her actual necessities. Domain-driven design (DDD) is an efficient software for flushing out prospects’ wants; DDD stresses doing in-depth analysis to grasp product necessities and doesn’t assume that each group inside a corporation has the identical necessities. An group could also be represented by quite a few bounded contexts, every of which has its personal necessities and every of which must be thought-about in engineering a developer platform. One-size-fits-all options normally fail. It’s additionally a mistake to imagine {that a} developer platform ought to resolve the entire builders’ issues. Getting to 80% could also be all you are able to do; the previous 80/20 rule continues to be a very good rule of thumb.
Platform engineering is essentially opinionated: platform engineers must develop concepts about how software program growth workflows must be dealt with. But it’s additionally necessary to grasp the bounds of “opinionated software.” David Heinemeier Hansson (DHH) popularized the thought of “opinionated software” with Ruby on Rails, which carried out his concepts about what sorts of assist an online platform ought to present. Were DHH’s opinions right? That’s the improper query. DHH’s opinions allowed Rails to thrive, however that’s solely platform engineering throughout the context of DHH’s firm, 37 Signals. Rails’ success amongst internet builders would have meant little if it wasn’t accepted by 37 Signals–no matter how profitable it was exterior. Likewise, if the software program builders at your organization select to not use the platform you develop, it has failed–irrespective of how good your opinions could also be. If the platform imposes guidelines and procedures that aren’t pure to the platform’s customers, it’ll fail. Opinionated software program has to acknowledge that there are numerous methods to unravel an issue and that customers are all the time free to reject the software program that you just construct. The customers’ opinions are extra necessary than the platform engineers’. Writing about website reliability engineering, Laura Nolan discusses the significance of the Greek idea metis: native, particular, sensible, and experiential information. Platform engineering should take that native information under consideration–with out getting caught by “we’ve always done it that way.” Listening to the platform’s eventual customers is vital; that’s the way you develop a coherent product focus.
Platform engineering is essentially an try and impose some form of order on a chaotic state of affairs—that’s the lesson LinkedIn realized. But it’s additionally necessary to acknowledge, as Camille Fournier stated in dialog, that there’s all the time chaos. We might not wish to admit it, however software program growth is inherently a chaotic course of. What occurs when one firm acquires one other firm that has its personal developer platform? How do you reconcile the 2, or must you even attempt? What occurs when totally different teams in an organization develop totally different processes for managing their issues? Domain-driven design’s idea of “bounded context” may also help right here. Some unification might be needed, however full unification would virtually definitely require an enormous expense of effort and time, along with alienating numerous builders. Imposing construction beneath the guise of “being opinionated” is a path to failure for a software program platform. Platform engineers must develop a product that their customers need, not one which their customers will struggle. Again, good engineering requires listening to the purchasers. They might not know what they want, however their expertise is the bottom fact {that a} platform engineer has to work from.
Platform engineers additionally want to think twice about “paved paths.” The time period “paved paths” (typically known as “golden paths”) reveals up ceaselessly within the platform engineering literature. A paved path is a course of that has been smoothed out, regularized, made straightforward by the platform. It’s widespread knowledge to pave the best and most ceaselessly used paths first; in any case, this makes it appear like you’re conducting quite a bit and have good protection. But is that this one of the best ways to have a look at the issue? Software builders most likely have already got instruments and processes for managing the best and mostly used paths (which aren’t essentially the identical). The proper query to ask is the place platform engineering could make the largest distinction. Given that the purpose is to cut back the burden of complexity, what processes are the largest downside? What resolution would most cut back the builders’ burden of complexity? The finest method most likely isn’t to reinvent options to issues which have already been solved—that may come later, if it’s needed in any respect. Instead, it might be worthwhile to suit older options into a brand new framework. What issues get in builders’ method? That’s the place to begin.
By now, it must be apparent that, whereas platform engineering is about product growth, it isn’t a few product like Excel or GitHub. It’s not about constructing a one-size-fits-all platform that may be packaged and marketed to totally different organizations. Each firm has its personal context, as does every group inside an organization. Each has its personal necessities, its personal tradition, its personal guidelines, and people should be noticed—or in the event that they should be modified, they should be modified very rigorously. Engineering is all the time about making compromises, and ceaselessly essentially the most applicable resolution is the least worst, as Neal Ford has stated. This is the place domain-driven design, with its understanding of bounded context, might be very useful. A platform engineer should uncover the foundations and necessities that aren’t said, in addition to those which can be.
And now with AI? Sure. There’s no purpose to not incorporate AI into engineering platforms. But there’s little right here that requires AI. It’s possible that AI could possibly be used successfully to investigate a challenge and estimate infrastructure necessities. It’s potential that AI could possibly be used to assist with code assessment—although the ultimate phrase on code assessment must be human. There are many different potential purposes. AI’s greatest worth may not be making options about methods to easy numerous pathways however within the design course of behind the platform. It’s potential that AI might analyze and summarize present practices and counsel higher abstractions. It’s much less possible than people to be caught within the lure of “the way we’ve always done it.” But people have to stay within the loop always. As with software program structure, the arduous work of platform engineering is knowing human processes. Gathering details about processes, understanding the reasoning behind them, and coming to grips with the historical past, the economics, and the politics nonetheless requires human judgment. It’s not one thing that AI is sweet at but. Will we see elevated use of AI in platform engineering? Almost definitely. But no matter you do or don’t do with AI, please don’t do it merely for buzzword compliance. AI could have a spot. Find it.
That’s one facet of the coin. The different facet is that firms are investing in constructing purposes that incorporate AI. It’s straightforward to imagine that software program incorporating AI isn’t a lot totally different from conventional purposes, however that’s a mistake. Platform engineering is all about managing complexity, and incorporating AI in an utility will inevitably improve complexity. Accommodating AI will definitely stress our concepts about steady supply: What does automated testing imply when a mannequin’s output is stochastic, not deterministic? What does CD imply when evaluating an utility’s health might take for much longer than growing it? Platform engineering will want a job in testing and analysis of AI fashions. There will should be instruments to detect when an utility is being abused or delivering inappropriate outcomes. Models should be monitored to allow them to be retrained once they develop stale. And there can be new choices for managing the price of deploying AI purposes. How do you assist handle that complexity? Platform engineers might want to take all of this, and extra, under consideration. A platform that solely solves yesterday’s issues is an obstruction.
So what does a platform engineer engineer? Is it a shock to say that what a platform engineer builds relies on the state of affairs? A developer dashboard for deploying and different duties could be a part of an answer. It’s arduous to think about a platform engineering challenge during which an API isn’t a part of the answer. A DevOps wiki may even be a part of an answer, although standing up a wiki hardly requires engineering. Collecting an organization’s collective knowledge and lore about constructing initiatives may assist platform engineers to work towards a greater resolution. But it’s necessary to not level to any of this stuff and say “This is it—building that is platform engineering.” Focusing on any single factor tends to draw platform engineering groups to the newest fad. Does this repeat the historical past of DevOps, which was hampered by its refusal to outline itself? No. Platform engineering is finally engineering. And that engineering should keep in mind all the course of, beginning with gathering necessities, understanding how software program builders work, studying the place complexity turns into burdensome, and discovering what paths are most in want of paving. It proceeds to constructing an answer—an answer that’s, by definition, by no means completed. There will all the time be new paths to pave, new sorts of complexity to summary. Platform engineering is an ongoing course of.
Why are you doing platform engineering? How do you justify it to senior administration? And how do you justify it to the software program builders that you just’re serving?
We hope that justifying platform engineering to software program builders is simple—however that isn’t assured. You’re most definitely to succeed with software program builders in the event that they really feel like they’ve been listened to and that you just’re not imposing a set of opinions on them. Developers have perception into the issues they face; reap the benefits of it. Engineering options that cut back the burden of complexity are the important thing to success. If you’re succeeding, try to be seeing deployments improve; try to be seeing much less frustration; and you need to see metrics for developer productiveness headed in the fitting route. On the opposite hand, if a platform engineering resolution simply turns into another factor for software program builders to work round, it has failed. It doesn’t want to unravel all issues initially, however a fast minimal viable product will go an extended technique to convincing builders {that a} platform has worth.
Justifying platform engineering to administration is a unique proposition. It’s straightforward to have a look at a platform engineering group and ask, “Why does this exist? What’s the ROI? Why am I paying expensive engineers to create something that doesn’t contribute directly to the product we sell?”
The first a part of the reply is straightforward. Platform engineering isn’t something new. It’s the subsequent stage within the evolution of operations, and operations has been a price heart because the begin of computing. In the lengthy arc of computing historical past, we’ve been evolving from a lot of operators watching over a single laptop (a Sixties mainframe required a big employees and had much less computational capability and storage than a Raspberry Pi) to a small variety of operators answerable for 1000’s of digital machines or situations working within the cloud. Platform engineering completed effectively is the subsequent stage in that evolution, permitting the employees to function even bigger and extra complicated methods. It’s not additive, one thing new that must be carried out and resourced. It’s doing what you’re already doing however higher.
If senior administration thinks that platform engineering doesn’t contribute on to the product, they should be educated in what it means to ship a software program product. They want to grasp that there isn’t any product with out deployment, with out testing, with out provisioning infrastructure. Doing this infrastructure work extra effectively and successfully contributes on to the product. A product that may’t be deployed—or the place deployments take months moderately than hours—is lifeless within the water.
But that argument isn’t actually convincing with out metrics. Go again to the enterprise downside you’re making an attempt to unravel. Do you need to improve the speed at which you launch software program? Document that. Are you making an attempt to make it simpler so as to add options or fixes with no full redeployment? Document that. Are you making an attempt to lower the time between a bug report and a bug repair? Document that. Programmers typically assume that software program is self-justifying. It isn’t. It’s necessary to maintain your eyes on the enterprise objectives and the way the platform is affecting them.
The DORA metrics are a great way to indicate the necessity for higher processes, together with measuring whether or not platform engineering is making processes extra environment friendly. Can you display that platform engineering efforts are enabling you to get options and bug fixes into your organization’s product and out to prospects extra shortly? Can a platform engineering effort assist the corporate use cloud providers extra effectively by avoiding duplication and oversubscription? Can you measure the period of time builders spend on new options or fixes, versus infrastructure duties? In his PlatformCon 24 speak, Manuel Pais suggests measuring the share of the corporate’s earnings that’s supported by the platform. That train reveals how necessary the platform is to the corporate. Platforms do generate worth, however platform engineers ceaselessly don’t take some time to quantify that worth once they speak to administration. Once the worth of the platform, it’s potential to forecast how the platform’s worth will increase over time. A platform is a strategic asset, not only a sunk price.
Most firms have already got a developer platform, whether or not it’s a bunch of previous shell scripts, an unmaintained wiki, or a extremely engineered set of instruments for steady integration and deployment. These platforms don’t all ship the identical form of worth—they might not ship any worth in any respect. The actuality is that no firm can exist for lengthy with out deploying software program, and no firm can develop software program if its developer group is spending all their time chasing down infrastructure issues.
The platform is already there. Whether it’s working for or in opposition to you is a unique query. Treating your engineering groups as prospects and constructing a product that satisfies their wants is difficult, necessary work. It means understanding their issues as they see them. It means arising with new abstractions that disguise complexity. And ultimately, it means making it simpler to deploy software program efficiently at scale. That’s platform engineering.