Platform engineering has emerged as the latest industry buzzword in IT operations, revolutionizing the way organizations approach infrastructure management. Without warning, the buzzword’s meaning teeters on the brink of obsolescence, vulnerable to being hollowed out by yet another company peddling a “platform engineering” solution. As the concept of edge computing has evolved, it’s become clear that the term encompasses a broad spectrum of applications, ranging from simple caching mechanisms within cloud provider data centers to mobile devices and even unattended data collection nodes in remote locations? DevOps emerged as a collaborative approach, regardless of individual preferences. Tradition? Job title? A specialised group inside IT?
Platform engineering doesn’t require that to happen. IT operations at scale are far too critical to disappear without a chance. Camille Fournier’s upcoming eBook observes that the term “platform engineering” often connotes a range of responsibilities, from managing operational documentation on a wiki to creating data visualizations in dashboards, exposing application programming interfaces (APIs), and orchestrating containerized workloads using Kubernetes. The following all have some bearing on platform engineering: infrastructure, scalability, and security. However none of them platform engineering. When viewed individually, each piece appears to capture a distinct aspect of the narrative, much like separate individuals grasping hold of different parts – a tusk, a tail, or a leg – yet collectively they fail to convey a comprehensive picture of the story.
Platform engineering enables organisations to create leverage by orchestrating digital infrastructure, being operated to efficiently supply goods and services, and by empowering seamless interactions on delivering exceptional merchandise and personal experiences.
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It sounds as though the summary, however, is each exactly and useful. Platform engineers frequently discuss “a product strategy” – viewing the platform as a product and treating software program developers – its customers – as potential buyers, designing it to meet their needs and expectations. There has been considerable debate surrounding the notion that DevOps has led to a decline in job opportunities, with some even speculating about a brief “NoOps” movement. However, as Charity Majors highlighted at PlatformCon 2023, the reality of operations engineering is that it has become astonishingly sophisticated. The era when setting up “operations” simply entailed provisioning a handful of servers with Apache and MySQL is now a distant memory. While cloud providers have assumed responsibility for infrastructure setup, including racking and stacking, as well as configuring software, their scope has expanded to encompass multiple suppliers, each requiring tailored configurations. Modern applications’ purposes have evolved significantly: today, we manage complex systems comprising numerous microservices that operate independently across thousands of cloud instances. As purposes have become increasingly sophisticated, so too have operations. The days of whispering arcane syntax to coax servers into submission are long gone. This approach isn’t consistent; this approach isn’t sustainable; this approach isn’t reliable. Regrettably, this has led to a peculiar limitation: modern software solutions are often inaccessible unless controlled by their original creators.
Software program engineers should focus on developing innovative applications that leverage their expertise, rather than simply writing code. They’re not required to develop expertise in specific areas like hosted Kubernetes, IAM protocols, monitoring tools, or other tasks that have become integral to their workflow. A novel suite of conceptual frameworks is required, empowering both builders and operations professionals to ascend to a higher plane of performance.
As the conversation delves into the heart of platform engineering, it’s crucial to grasp the concept of abstraction – removing the intricacies that can overwhelm developers. As technology continues to evolve at an exponential pace in the 21st century, developing software programs will require a strategic blend of innovation, collaboration, and adaptability. We’ll focus on leveraging cutting-edge tools and methodologies to create scalable, maintainable, and user-centric solutions that seamlessly integrate with emerging technologies like artificial intelligence, blockchain, and the Internet of Things (IoT). Can improved tooling simplify construction workflows by overcoming productivity hurdles? Let’s empower operations workers to focus on delivering high-quality services rather than worrying about metrics like service-level agreements (SLAs) and uptime. Can operations teams proficiently manage complex technical concepts like load balancing, business continuity, and failovers – typically leveraged by developers through carefully crafted abstraction layers? Platform engineering’s perpetual conundrum is its own Achilles’ heel. Why must builders unnecessarily complicate their projects, diverting attention from actual construction?
The allure of platform engineering lies in the notion of “one-click deployment”: craft your utility and effortlessly activate it via a seamless process that seamlessly navigates testing, integration, and deployment, all with just one intuitive click. Life is far from being that simple. Deployments themselves are inherently complex, involving considerations such as canary releases, A/B testing, and rollbacks, to name just a few.
In reality, however, lies a tangible truth, with genuine achievements hidden beneath its surface. Facebook traditionally demands that newly onboarded employees publish something on the company’s website within their first day of employment. While concepts like “platform engineering” and “developer platforms” may be relatively modern, this historical example demonstrates that the idea of simplifying software deployment through abstraction is not novel.
Kevin Scott, then a LinkedIn expert and now Microsoft’s Chief Technology Officer, recounted how the corporation found itself embroiled in a massive development quagmire after its initial public offering (IPO)? Given the company’s history as a fast-growing startup with a legacy of solving problems on the fly, it proved extremely challenging to introduce innovative solutions: a complex web of disparate procedures and accumulated technical liabilities had evolved over time, hindering the introduction of new options. While “Automate all of the issues” may have been a bold and captivating phrase initially, it unfortunately harbors a significant drawback in reality. LinkedIn halted its new user growth to focus on building a stable infrastructure for software deployment. After several months and numerous career sacrifices, including those of Scott’s, the project ultimately achieved success. Since LinkedIn’s early days, the platform has evolved significantly in terms of its release cadence, shifting from introducing new features on a monthly basis – assuming there was even that much time between them – to now being able to deploy multiple updates daily.
What captivates readers about this narrative is its remarkable anachronism: despite recounting events years after the fact, Scott eschews contemporary terminology like “platform engineering,” never referencing concepts such as developer expertise or internal developer platforms. Despite the uncertainty surrounding LinkedIn’s IPO, it is undeniable that the company’s group had successfully engineered a robust platform, which likely contributed significantly to its survival and ultimate profitability.
Walmart’s narrative parallels that of its retail peers. As deployment progressed daily, unforeseen problems emerged in instrumentation, protocols, and workflow. The issues previously addressed by the DevOps team were subsequently escalated to the platform group for further consideration. As in the instances previously mentioned, this task took place during the 2010s. Walmart’s narrative, akin to Scott’s LinkedIn story, eschews the terminology commonly linked to platform engineering.
The as-a-service model was an early manifestation of platform engineering’s legacy. Launched in 2007, Heroku revolutionized application deployment by introducing the concept of single-click setup, particularly for smaller-scale projects. With Heroku, you’re able to develop without worrying about cloud intricacies and minimal knowledge of connecting databases to your application is required. Almost everything was meticulously attended to, ensuring your complete satisfaction. While Heroku didn’t quite reach its full potential, it still provided a glimpse into the possibilities that cloud computing could offer to web developers.
While all these examples highlight the significance of platform engineering, they do not necessarily indicate that the concept itself is novel? The concept of “platform engineering” represents the natural progression of established practices such as DevOps, infrastructure-as-code, and automation of routine maintenance tasks. In the software industry, individuals whether building programs or performing operational tasks have consistently developed tools to streamline their work processes. By recognizing the importance of platform engineering, the development of tools and abstractions is elevated from a casual, ad-hoc approach to a rigorously formal process, acknowledging that crafting instruments and creating abstractions for complex procedures is indeed an engineering discipline rather than simply coding or hacking. LinkedIn’s major drawback wasn’t a scarcity of tooling. For decades, unregulated innovation and ad-hoc solutions had flourished, eventually yielding a tangled web of fragmented systems and stifling advancement. The company’s solution was successfully crafting a robust and harmonized infrastructure by expertly designing its tooling, thereby fostering a seamless and synchronized platform.
According to Steven Vaughan-Nichols, the notion that DevOps is consistently delivering may be misguided: only 14% of companies can successfully deploy software to production within a single day, while just 9% can efficiently roll out multiple instances daily. While it’s undeniable that many organizations claim to have adopted DevOps, CI/CD, and similar concepts, the reality is that some of these entities merely rebrand existing practices without making any significant changes to their traditions. While it’s undeniable that software deployment has become increasingly complex, it’s also clear that undisciplined device development can result in a significant accumulation of technical debt, as LinkedIn itself discovered. While architectural styles such as microservices effectively break down large monolithic applications into smaller, more manageable components, they also introduce the challenge of correctly configuring and deploying these individual services, creating a potential new focal point for technical debt accumulation.
The list of concerns that platform engineering must resolve for software developers grows lengthy quickly. The solution streamlines processes by seamlessly integrating everything from developer laptops to supply chain repositories and cloud-based deployments, revolutionizing manufacturing operations. As you search for more, you’ll find even more responsibilities trying to simplify your life. Inadequate configuration of identity, access, and authentication protocols frequently leads to a multitude of security vulnerabilities. The complexity of Identity and Access Management (IAM) systems can lead to errors, particularly when dealing with multiple users, roles, and permissions. To simplify IAM and reduce errors, consider the following strategies:
By implementing role-based access control (RBAC), you can streamline permission management by defining roles based on job functions or responsibilities. This approach ensures that users are assigned the necessary permissions without having to manually configure individual user settings.
Another technique is to use attribute-based access control (ABAC). With ABAC, access decisions are made based on a user’s attributes, such as department, job function, or location. This method allows for more granular permission management and can reduce errors by ensuring that users only have access to resources they need.
Additionally, consider automating IAM tasks whenever possible. Automation can help prevent human error and reduce the administrative burden associated with managing complex permissions.
By implementing these strategies, you can simplify your IAM system and reduce errors, making it easier to manage user access and maintain a secure environment. At its inception, AWS astonished us with its seamless ability to deploy virtual infrastructures and manage data storage. Provisioning a complex service that leverages numerous available providers and operates across thousands of instances, both in the cloud and on-premises, is far from straightforward. Improper setup can lead to a logistical nightmare, hindering both efficiency and scalability. Can the burden of ensuring that infrastructure is properly provisioned for optimal performance and scalability be significantly reduced? Deployment involves more than just pushing code to a server or fleet of servers; it encompasses A/B testing, rollback capabilities, and other critical components. Can such complexities be distilled for streamlined operations? Any effective deployment necessitates careful consideration of scalability, as software programs that fail to account for a corporation’s current and anticipated needs are doomed to struggle? Can a platform effectively integrate strategies to streamline and enhance its capacity for growth? In the 2020s, ensuring failover and enterprise continuity during outages, minimizing costs by optimizing server fleet scale, and maintaining regulatory compliance have become paramount considerations, a far cry from our limited understanding of these critical factors just two decades ago. Can’t builders just let someone else worry about failover and treat it as a platform capability rather than their problem to solve?
In the realm of platform engineering, a crucial takeaway lies not in the term “platform,” but rather in the concept of “engineering” itself. To ascend the abstraction ladder successfully, stable engineering practices are essential, as advocated by Yevgeniy Brikman. However what does that imply?
Platform engineering consistently emphasizes treating developers as customers. When you consider (or learn) about this phenomenon, you might experience a sense of unease or strangeness. Are you suggesting that everyone in the organization is a prospect, including engineers, or should the term “prospects” be reserved for potential customers? The crucial paradigmatic shift lies in repositioning software developers from being viewed as mere labor assets to valuable prospects. When Camille Fournier discusses “a product strategy for growing internal platforms,” she underscores the imperative that a platform engineering group must adopt a customer-centric approach, empathetically grasping what their users’ pain points are, and then devising effective solutions to address those needs.
Platform engineering encounters the same pitfalls as other types of product development. For effective design, it’s crucial to put the customer at the forefront, building a solution that meets their needs and preferences, rather than solely focusing on the technical aspects of the product. While techno-solutionism posits that every problem can be solved with cutting-edge technology, this ideology often devolves into hasty adoption of trendy concepts rather than their actual feasibility. Frequently, this approach forces external perspectives onto a situation, imposing one party’s ideas on others without considering their unique needs and concerns? It’s poor engineering. Effective engineering demands sitting in the buyer’s shoes, immersing oneself in their daily responsibilities to genuinely comprehend their needs. Domain-Driven Design (DDD) is an invaluable tool for unearthing customers’ requirements; by emphasizing in-depth analysis, DDD highlights the importance of recognizing that distinct teams within a corporation may have divergent necessities. A corporation may comprise numerous bounded contexts, each with distinct requirements, necessitating careful consideration when designing a developer platform. One-size-fits-all options often fail. It’s also a misconception to assume that a developer platform should resolve all of a builder’s problems. While attending at an 80% level is acceptable, the traditional 80/20 principle remains a guiding standard, emphasizing the importance of prioritizing high-impact tasks.
Platform engineering is inherently opinion-based: platform engineers must formulate opinions on how software development workflows should be managed. While it’s crucial to comprehend the limitations of “opinionated software,” David Heinemeier Hansson (DHH), the pioneer behind Ruby on Rails, coined the term “opinionated software” while developing his vision for a web platform that should provide specific forms of support. Had been DHH’s opinions appropriate? That’s the improper query. While DHH’s influence contributed significantly to Rails’ success, this impact was largely confined to his company, 37signals, in terms of platform engineering. Rail’s success among internet developers wouldn’t have mattered without the endorsement of prominent companies like 37 Signals, regardless of its profitability outside of that circle. If developers within your organization decline to utilize the platform you’ve created, no matter its quality, it can still be considered a failure. If a platform prioritizes rigid guidelines and procedures over genuine customer needs, it’s bound to falter. While developing opinionated software, it is essential to recognize that diverse approaches exist to resolve a given problem, leaving users unfettered freedom to opt out of utilizing the application created. Customers’ opinions are far more crucial than those of the platform engineers. What lies at the heart of reliable website engineering? For Laura Nolan, it’s not just a matter of throwing more servers or software at the problem – rather, it’s about embracing the ancient Greek concept of tetradic thinking. Here, we’ll explore why native, particular, sensible, and experiential data are crucial to building a rock-solid online presence. Platform engineering must carefully consider native data, resisting the urge to simply perpetuate outdated practices – “because we’ve always done it this way.” Instead, actively listening to the platform’s ultimate customers is crucial for developing a coherent product focus.
By recognizing that platform engineering was a means to tame chaos, LinkedIn understood the significance of bringing order to a complex system. As Camille Fournier notes, chaos is always present, emphasizing the importance of acknowledging and preparing for uncertainty. Despite our reluctance to acknowledge it, software development is inherently a chaotic process. When a company purchases another firm that possesses its own developer platform, the acquiring entity gains control over the acquired platform’s existing codebase, intellectual property, and user base. This acquisition can lead to the integration of the platforms, resulting in improved offerings, enhanced functionality, and increased market competitiveness. The acquiring firm may also leverage the acquired platform’s expertise, talent pool, and existing relationships with developers and partners. The quest for harmony between seemingly disparate elements. Can one truly coexist with another without sacrificing essence or integrity? The answer lies in embracing paradox and accepting the beauty of contrasts. When disparate teams within an organization independently craft distinct procedures for addressing challenges, fragmentation and inefficiency often arise. Area-driven design’s concept of “empathy” will help out here? While some degree of unification may be necessary, a comprehensive approach would likely necessitate a substantial investment of resources and time, potentially alienating many stakeholders in the process. When disguising rigid demands as “having an opinion,” software platforms court catastrophe. Platform engineers must craft products that meet their customers’ needs, rather than creating ones they’ll resist. Good engineering relies heavily on effective communication with customers, requiring a willingness to listen and adapt to their needs and preferences. Despite uncertainty about their needs, their fundamental requirement is that a platform engineer works from a fact: their expertise.
Platform engineers should meticulously contemplate “paved paths,” a term frequently encountered in platform engineering literature, commonly referred to as “golden paths.” A paved path is a predetermined route that has been deliberately smoothed, standardized, and simplified through the process of construction or maintenance, rendering it easily accessible and navigable. It’s common practice to prioritize maintenance on the most heavily trafficked routes, which may give the illusion that you’re expending considerable resources and ensuring robust security. Isn’t it better to consider alternative approaches first? Software developers likely possess tools and methodologies to oversee optimal routes, which may differ from one another. Where would platform engineering have the greatest impact? Given the objective of simplifying the complexity, the most crucial hindrances to scaling back are: redundant workflows, ineffective communication channels, and lack of transparency in decision-making. A straightforward solution to simplify construction processes would most effectively reduce the builders’ burden: standardize building designs and materials. In all likelihood, the most effective approach is not to re-invent solutions for problems that have already been addressed, unless it’s absolutely necessary. As an alternative, it might be advantageous to adapt earlier versions into a fresh structure. Time constraints and budget limitations are often the biggest hurdles for builders. This is where we begin.
Now it’s clear that platform engineering is about driving product growth, yet it’s fundamentally different from developing individual products like Excel or GitHub. The approach shouldn’t revolve around developing a single, universally applicable solution that would then need to be adapted to fit the unique needs of various organizations. Each organisation and its constituent groups have their unique contexts. Everyone has their own unique necessities, traditions, and guidelines, which must be respected or carefully redefined if necessary. Engineering is inherently about finding a balance between competing demands, and often the most practical solution involves making compromises, as noted by Neal Ford. The application of domain-driven design in this instance is where the concept of bounded contexts becomes particularly relevant? A seasoned platform engineer must unearth both spoken and unspoken principles and requirements.
And now with AI? Positive. There’s no reason not to integrate AI into engineering platforms. There’s little to no substance here that necessitates AI intervention. Undoubtedly, AI can effectively tackle challenges and predict infrastructure requirements with precision. While AI can potentially aid in code evaluation, the definitive verdict remains with humans. There exist numerous diverse feasible objectives. The greatest value AI will bring lies not in developing straightforward solutions for multiple routes, but rather in the underlying platform’s design process itself? It’s possible that AI could analyse and summarise current practices, potentially counselling higher-level abstractions. While some may be susceptible to the allure of “the way we’ve always done it,” individuals must remain vigilant and informed to stay ahead of the curve. The arduous task of platform engineering lies in understanding and adapting to ever-changing human processes. While automating data gathering and analysis has advanced significantly, grasping the intricacies of complex processes, discerning motivations, and situating events within a broader historical context still necessitates the unique capabilities of the human mind. AI excels in multiple areas, rather than just one thing. As companies continue to push the boundaries of digital transformation, will we witness a surge in the adoption of artificial intelligence (AI) within platform engineering teams? Virtually definitely. While avoiding mere buzzword compliance is crucial, it’s equally important to leverage AI in a thoughtful and strategic manner that aligns with your organization’s goals and values. AI may have a spot. Discover it.
The flip side reveals another narrative altogether? Firms are increasingly investing in building projects that seamlessly integrate artificial intelligence capabilities. While it may seem intuitive that software programs leveraging AI are not vastly distinct from traditional applications, this assumption is misguided. As platform engineering continues to grapple with escalating complexity, the integration of AI-driven utilities holds immense promise for streamlining operations and amplifying efficiency. Can we reconcile the uncertainty of an AI’s unpredictable outputs with traditional notions of dependable supply chains? When evaluating a utility’s health, what it takes to grow may be dwarfed by the time spent addressing CD, which implies that correcting defects or flaws can consume considerable resources. Platform engineers will seek opportunities in testing and analysis of artificial intelligence models. Instruments will need to be developed to monitor and detect potential abuse of utilities, as well as identify instances where they are producing suboptimal results. Fashion trends need constant monitoring to prevent stagnation and enable effective retraining once they’ve become outdated? New options for managing the cost of deploying AI initiatives may emerge. To effectively navigate this intricate landscape, we employ a multi-pronged approach. For platform engineers’ strategic planning, a comprehensive examination of these factors – including scalability, latency, reliability, cost, and security – is crucial. A platform stuck in the past, solely focused on resolving yesterday’s problems, is a hindrance to innovation and progress.
A platform engineer designs, builds, and maintains the underlying technology infrastructure that enables software applications to run efficiently, securely, and at scale. They craft a reliable foundation for data storage, processing, and retrieval; ensure seamless communication between systems; and implement automation to streamline workflows. By streamlining the development environment, they empower developers to focus on building innovative products rather than wrestling with technical challenges. It’s not surprising to note that a platform engineer’s creations are influenced by the circumstances. A comprehensive developer dashboard for seamless deployment and efficient task management could be a valuable addition to streamline workflows. In today’s digital landscape, it’s virtually inconceivable to envision a platform engineering issue that doesn’t involve APIs as a critical component. A DevOps wiki could be a valuable resource, potentially housing information and best practices on implementation strategies, tooling choices, and operational considerations. While setting up a wiki might not necessitate extensive engineering expertise, it can still require some technical know-how to ensure seamless integration with existing systems and workflows. By aggregating an organization’s cumulative expertise and storytelling around task construction, platform engineers can strive for a more comprehensive solution. However, it’s crucial to resist the temptation to oversimplify or label a singular aspect as “platform engineering.” Focusing on a specific area can lead platform engineering teams to get swept up in the latest trend. Did this repeat the historical past of DevOps, which was hindered by its complexities and siloed thinking, leading to a disconnect between development and operations teams? No. While platform engineering may share some similarities with traditional engineering, it’s more accurately described as a distinct discipline that combines expertise from various fields to build and manage scalable, secure, and efficient digital platforms. Engineering ought to heed lessons from the entire development process, commencing with need assessment, grasping software developers’ methodologies, identifying areas where complexity becomes overwhelming, and pinpointing the most pressing avenues for improvement. As such, any proposed solution remains fundamentally incomplete and perpetually in flux, subject to revision and refinement as new information becomes available or fresh perspectives emerge. There will always be new paths to pave, and novel forms of complexity to navigate. Platform engineering is a continuous process.
As a professional in the tech industry, I’m driven by a passion for building innovative solutions that bridge the gap between technology and business. Platform engineering allows me to leverage my skills in software development, architecture, and operations to create scalable and maintainable platforms that enable others to build upon. It’s a challenge that requires me to stay up-to-date with the latest trends, tools, and best practices, which keeps my work exciting and fulfilling. We’ve thoroughly examined the data and conclusively demonstrated that this initiative will yield a substantial ROI by streamlining operations, reducing costs, and enhancing customer satisfaction. It’s essential to emphasize that our proposal aligns with the organization’s overall strategic objectives, ensuring a seamless integration with existing initiatives. What’s your approach to explaining this technology’s value proposition to software program builders who are skeptical about its potential benefits?
While justifying platform engineering may seem intuitive for software developers, there’s no guarantee of a smooth understanding. When collaborating with software program developers, it’s crucial to establish trust by actively listening to their concerns and avoiding imposition of preconceived ideas, allowing for a more effective working relationship. As builders possess a unique understanding of the challenges they encounter, they are well-positioned to capitalize on this insight and reap tangible rewards. Simplifying complex engineering options is crucial for achieving success. When success is evident, deployments should be streamlined, frustration significantly reduced, and productivity metrics trending positively for developers. If a platform engineering solution ultimately becomes just another obstacle for software developers to navigate, then it has fundamentally fallen short of its intended purpose. Although it may not immediately resolve all concerns, a persuasive approach is necessary for demonstrating the value of a platform to builders.
Ensuring the strategic value of platform engineering initiatives requires a compelling case for administrative stakeholders. What drives the creation of a platform engineering group, and what problems do they aim to solve? What’s the ROI? What is the tangible value of investing in a feature that, despite being technically impressive, fails to drive meaningful returns for our core business?
The primary aspect of the response is straightforward. Platform engineering isn’t something new. Operations has long been a vital linchpin in the evolution of computing, with its role as a value middle dating back to the very inception of computer science. Over the course of computing history, we’ve transitioned from large teams managing single mainframes with limited capabilities to a handful of administrators overseeing thousands of virtual machines and cloud-based infrastructure. Platform engineering has reached a milestone, enabling teams to operate at an even greater scale and complexity. This is a non-recurring expense that requires a significant upfront investment. It’s doing what you’re already doing, but to a greater extent.
When senior administrators misunderstand platform engineering’s value by dismissing its contribution to the product, it is essential to educate them on the fundamental aspects of shipping a software product, thereby dispelling misconceptions about this critical component. Without exception, they should recognize that no product exists without deployment, testing, or provisioning of underlying infrastructure? This infrastructure work significantly enhances the overall performance of our products, ultimately driving their success. In a fast-paced aquatic environment, a product unable to swiftly deploy or one that takes months to do so is essentially useless.
However, without concrete metrics to back it up, that argument lacks persuasive power. Can we overcome the obstacles hindering our progress? Need to boost your software launch speed and efficiency? Doc that. You are cautiously implementing incremental updates to avoid a comprehensive overhaul; this approach enables you to evaluate potential solutions without disrupting the entire system. Doc that. We’re actively seeking ways to shorten the interval between identifying bugs and implementing fixes to minimize the overall impact on our customers. Doc that. Programmers often take for granted that a well-designed software program will justify itself through its functionality and usability. It isn’t. It’s crucial to continuously monitor your organization’s objectives and assess how the platform is impacting their attainment.
KPIs are a great way to measure whether platform engineering is necessary and whether processes are becoming more environmentally sustainable.
Can you demonstrate how platform engineering initiatives have streamlined the process of delivering options and bug fixes to prospects, thereby accelerating time-to-market for your organization’s product? Can a platform engineering effort help companies optimize their usage of cloud providers more efficiently by eliminating duplication and ensuring optimal utilization? Can you quantify the time invested in developing innovative solutions or resolving issues versus maintaining and upgrading existing infrastructure? According to Manuel Pais, a key metric is identifying the proportion of a corporation’s earnings that are directly attributable to the platform. The reliability of that train underscores the critical role the transportation infrastructure plays in supporting the corporation’s operations. Platforms do indeed generate value, yet platform engineers often neglect to quantify that value when discussing it with administrators. As soon as a platform’s value is established, its potential for future growth becomes predictable. A platform is no longer just a fixed expense; instead, it’s a vital strategic asset that offers long-term benefits.
Many organizations already possess a developer platform, which may manifest as a collection of outdated shell scripts, an neglected wiki, or a meticulously crafted suite of tools for seamless integration and deployment. These platforms do not deliver a uniform type of value – they may not deliver any value at all. In reality, no company can sustain itself long-term without leveraging software, and no organization can create innovative software if its development team is bogged down resolving infrastructure problems?
The platform is already there. Regardless of whether the system works in your favour or against you, this is a distinctive inquiry. Engaging with engineering groups as potential customers requires crafting a product that effectively addresses their needs, posing a significant yet crucial challenge. Recognizing customers’ concerns from their own unique perspectives. New abstractions emerge to encapsulate and simplify the intricacies. By doing so, it ultimately enables seamless deployment of software applications on a large scale. That’s platform engineering.
