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The world of software development is constantly evolving, with the latest trend being a focus on platform engineering, which has been named one of the top strategic technology trends in 2023 by Gartner.
This shift has created a buzzing atmosphere in the DevOps space, leading to an increased interest in understanding the nuances between the two concepts and how and when organizations should start exploring implementing them.
To help clear the air, this article delves into the comparison between DevOps and platform engineering. It highlights their similarities, differences, benefits, and the best practices to maximize their potential in an organization.
DevOps is a broad subject that revolves around the efforts to enhance the efficiency and frequency of software releases. This process aims to reduce silos between teams and foster increased collaboration, with the ultimate goal of automating the software life cycle and reducing the feedback loop duration.
A key characteristic of DevOps is its association with various tools that automate the transition of code from a local environment into production. This phase is referred to as continuous integration and continuous delivery (CI/CD). Other elements of the DevOps process are supported by monitoring, incident management, and configuration management tools.
"DevOps is a paradigm shift in the way of working," says a senior solutions architect for a prominent software company. It promotes a shift-left mentality where developers work hand in hand with operations teams, significantly reducing build time. This approach facilitates the rapid and incremental release of new features, replacing the traditional waterfall development cycle.
DevOps strategy is a life cycle approach that aims to streamline the shipment of applications more efficiently. It covers various phases such as build, release, configure, monitor, plan, create, and verify. DevOps is often made possible by containerization and microservices architecture.
Platform engineering aims to implement a self-service internal developer platform with the goal of increasing developer productivity by lowering cognitive load and abstracting away the complexity of the underlying infrastructure.
The characteristics and features of the platform are typically defined by assessing the engineering team's needs when delivering software.
Platform engineering emerged as a solution to the challenges brought up by DevOps, which, despite promoting advanced automation, left organizations grappling with scattered tools and processes.
Platform engineering centralizes control to a platform team rather than leaving it up to individual developers. These teams treat the platform as a product and maintain it by evaluating the needs of developers across an organization, creating internal self-service tools that suit most consumers.
According to the 2023 State of DevOps Report, this self-service approach usually deals with tasks like infrastructure operation, production application monitoring, infrastructure deployment, security and compliance, and production application monitoring.
These initiatives may also involve other capabilities, such as abstracting Kubernetes, handling secrets management, or orchestrating containers.
Platform engineering provides several benefits, including:
Platform engineering isn't a substitute for DevOps. Instead, it should be considered as an enhancement to DevOps as it takes DevOps processes and makes them more reusable and self-service. Both approaches leverage automation and serve the similar and often intersecting purposes.
Let's take a look at the differences between the two approaches. DevOps focuses primarily on shifting responsibility and enabling developers to oversee the lifecycle of their applications from beginning to end. With the emergence of sprawl and shadow IT emerge, the has shifted back toward increased centralization and governance with platform engineering.
Platform engineering is often a project that is developed internally. In order to fully use platform engineering, it is essential for the engineering team to keep in mind some of the best practices.
The DevOps philosophy is straightforward: "You build it, you run it." This approach was first described by Amazon's CTO Werner Vogels in 2006. Instead of adhering to the traditional "throw it over the wall" to operations model, Amazon's developers deployed and ran their applications and services end-to-end. This marked the birth of DevOps.
Different DevOps metrics have been developed throughout time by thought leaders for enterprises to use in gauging the effectiveness of their DevOps setup. Lead time, deployment frequency, change failure rate, and mean time to recovery (MTTR) are some of these indicators. These metrics have been used to compare performance across engineering organizations to determine which practices impact their success the most.
For some, DevOps generated improved levels of productivity and efficiency. However, for many organizations, DevOps adoption did not meet their high expectations.
Site Reliability Engineering (SRE), a concept popularized by Google, shares some similarities with DevOps. According to Benjamin Treynor Sloss, a site reliability engineer is responsible for the "availability, latency, performance, efficiency, change management, monitoring, emergency response, and capacity planning of their service(s)." They use service-level objectives (SLOs) and error budgets to set shared expectations for performance and balance reliability with innovation.
However, adopting SRE improperly can lead to several issues, especially for organizations that lack the same resources or talent as Google. Hiring SREs may be difficult and expensive, and many businesses don't succeed in finding SREs with the necessary level of expertise for their setup. Consequently, some operations teams take on these responsibilities, leading to more issues.
Platform engineering has emerged as a solution to the challenges posed by DevOps and SRE.
For software engineering firms operating in the cloud-native age, it entails creating and constructing toolchains and procedures that allow developer self-service capabilities.
Platform engineers provide a comprehensive solution, sometimes referred to as a "internal developer platform," that addresses all operational requirements over the course of an application's life cycle.
The teams who create internal developer platforms are important because they maximize the efficiency of their organizations. The extent of DevOps evolution is strongly correlated with the utilization of internal development platforms.
The platform-as-a-product method of platform engineering includes user research, product roadmap development, frequent feedback gathering, iteration, platform launch, and internal developer marketing. This method aids platform teams in avoiding issues like turning the platform into a glorified help desk, not obtaining enough internal support for the platform, creating tools that developers don't want to use, etc.
While both DevOps and platform engineering aim to streamline the development and deployment of software, they differ in their approach, mindset, selection of tools, and focus.
Automation is a fundamental aspect of both DevOps and platform engineering. In the case of DevOps, automation removes a lot of manual work from humans' jobs, facilitates faster deployment of updates to production, and creates more effective feedback loops between teams.
Platform engineering expands the overall scope of an organization's automation by automating tasks like infrastructure deployment as part of the software delivery process. This allows developers to concentrate on their core work instead of building their tools and processes.
At the same time, an internal developer platform reduces the amount of low-level tickets, like setting up new environments or deployments, that a DevOps engineer has to deal with on a daily basis.
Starting with platform engineering could seem a daunting task, given the complexities involved in designing and setting up a comprehensive platform. There are two primary routes to consider: building your own Internal Developer Platform (IDP) or adopting a pre-built platform. Both options come with their own set of benefits and challenges.
In the early days of platform engineering, organizations were almost forced to build their own platform teams to construct their platforms from scratch.
This approach meant constructing bespoke tools and solutions tailored to specific company needs. It was an arduous, time-consuming process with a high risk of missing the mark in terms of necessary features and usability. This was largely due to a lack of established best practices regarding platform engineering architecture.
Building your own IDP can come with a sense of control and customization, as it allows an organization to tailor-make a platform that meets its unique requirements. This route can be ideal for highly specialized organizations with very specific needs that off-the-shelf solutions might not fulfill.
However, this approach comes with high costs in terms of time, money, and resources. It involves the recruitment and ongoing support of an entire platform team, which can significantly increase overhead.
The landscape, however, has shifted dramatically. The advent of robust, flexible, and comprehensive pre-built platforms has disrupted the traditional paradigm of 'build-it-yourself'.
Platforms like mogenius offer powerful, feature-rich tools that provide a strong foundation for an organization's platform efforts while being a fraction of the cost of constructing and maintaining your own platform.
Pre-built platforms have been tried and tested, evolving based on feedback from various organizations, thus incorporating best practices from across the industry.
Furthermore, these platforms offer scalability, can be adapted to bespoke requirements, and are continuously updated to stay in line with the latest technological advancements and industry trends.
Pre-built platforms allow organization's to leverage the power of platform engineering without the heavy lifting.
In conclusion, while DevOps and platform engineering share a common goal of improving software development and deployment, they differ in their approach, mindset, and focus. Understanding these differences can help organizations make informed decisions about which strategy to adopt to meet their specific needs
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