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Platform engineering is emerging as a potential next step in the DevOps evolution journey. DevOps has been a game-changer for many companies as it focuses on balancing a synergy between software development, operations, and IT teams working in tandem to bring value to the customer. However, many of us are not aware that the core of DevOps actually rests strongly on product engineering, which implies the increasing release of new programs and their reliability.
DevOps was an effective way to address the communication and cooperation gap between development and operations teams. It introduced practices and tools for continuously integrating and deploying applications and their updates. It also changed how software is built, tested, and released to the market, making the process faster and more reliable.
However, as organizations grow and use microservices, containers, and cloud-native architectures, the challenges of managing and maintaining infrastructures and platforms have also grown. That’s where platform engineering comes in. Companies embrace this approach to navigate away the underlying complexities of infrastructure, self-service platforms, and reusable building blocks.
Platform Engineering helps developers write code and deliver maximum customer value to customers by handling everything from provisioning to managing the platforms and services required for seamless application development and operation.
How integration of DevOps and Platform Engineering accelerates software delivery excellence
Pursuant to the high relevance of platform engineering in DevOps, infrastructure provisioning is speeded up, automation is boosted, and CI/CD pipelines are optimized. It has also been noted that entities embracing platform engineering can build more flexible, reliable, and dependable delivery environments for their platforms. When cross-functional teams are equipped with strong platforms and automation tools, they are neatly aligned to unleash prodigious velocity and cadence while delivering customer value.
Let’s understand how Platform engineering acts as a catalyst and turbocharges DevOps below.
Infrastructure as Code (IaC) and automation:
- Platform engineering leverages Infrastructure as Code (IaC) principles to automate the provisioning and management of infrastructure resources.
- By codifying infrastructure configurations, teams can ensure consistency, repeatability, and scalability across environments.
- IaC tools such as Terraform, Ansible, or Kubernetes Operators enable teams to define infrastructure blueprints and deploy them programmatically.
- Automation reduces manual overhead, accelerates deployment cycles, and minimizes the risk of configuration drift, laying the foundation for efficient DevOps practices.
CI/CD pipeline optimization and continuous feedback:
- Continuous Integration/Continuous Delivery (CI/CD) pipelines are the backbone of DevOps, enabling automated testing, deployment, and delivery of code changes.
- Platform engineering focuses on optimizing CI/CD pipelines to minimize cycle times, improve reliability, and facilitate rapid feedback loops.
- Automated testing, including unit tests, integration tests, and end-to-end tests, is integrated into CI/CD pipelines to ensure the quality of code changes.
- Continuous monitoring and feedback mechanisms provide visibility into pipeline performance, enabling teams to identify bottlenecks and optimize workflows iteratively.
Scalability, resilience, and observability:
- Platform engineering emphasizes the design of scalable, resilient, and observable architectures that can withstand dynamic workloads and evolving business requirements.
- Infrastructure scaling capabilities, such as auto-scaling and horizontal scaling, are integrated into platform designs to accommodate fluctuating demand.
- Resilience engineering principles, including fault tolerance and graceful degradation, are implemented to minimize service disruptions and enhance system reliability.
- Comprehensive observability tools and practices enable real-time monitoring, logging, and tracing of system behavior, facilitating proactive issue detection and resolution.
Is Platform Engineering marking the next evolution of DevOps?
Platform Engineering stands out as the next evolution due to the complexity of modern software systems where engineers work with many microservices, containers, and cloud-native technologies. This complexity is managed by Platform Engineering since it must offer the environment and the tools that enable the handling of these many ingredients in the right way. This complexity calls for enhancing and upgrading the capabilities of traditional DevOps practices to meet the advanced level that is required.
Moreover, with the growing usage of cloud services and the elastic structure, scalability and redundancy have become the two major factors organizations should consider. These challenges are resolved by Platform Engineering since it aims at creating architecture that will be elastic to accommodate the variation of the workloads while at the same time robust to failure. Being able to incorporate principles like fault tolerance and observability, platform engineers then make sure that such systems will sustain their high availability and performance under different scenarios.
Platform Engineering is in sync with the fundamentals of the cloud-native architecture to operate at scale, remain highly available, and be adaptable, among others. With the help of various cloud-native principles like using Kubernetes, Docker, and serverless architectures, platform engineers are able to create software platforms that are purely cloud-based and easy to scale.
How will Platform Engineering accelerate DevOps?
Platform engineering is centered around utilizing systems and working on efficiencies and optimisations. That means platform teams enable the business to leverage assets to serve customers more effectively and efficiently, gain competitive advantage, and mitigate exposures that could result in negative consequences such as the loss of consumer trust.
To help their organizations get the most out of their DevOps platform, platform engineers can outsource and apply monitoring instruments in the DevOps environment to determine when and what issues are leading to bottlenecks, and subsequently solve those problems. Make sure that the teams are not lacking some of the things that are offering in the platform such as vulnerability scanning and access management to enhance their working processes
Also, extensions for CI or other custom scripts in the platform may be more closely aligned with the organization’s requirements. Next, identify the best practices to implement and then verify that the implementation of those practices is being adhered to. Establish and configure the platform templates for making new pipelines to be used as a baseline so that developers are not required to make new pipelines from scratch.
For example, build in pipeline efficiencies of custom code related to the infrastructure of the organization or of the particular kind of app. Set up the rules that would regulate the security and compliance bodies to dictate when the scans should be performed or if they should be executed at a particular stage or upon invoking a pipeline for a branch.
What are the steps a company must follow to prepare for the shift to Platform Engineering?
- Step 1: Assess current state and evaluate the existing DevOps practices along with infrastructure, and tooling. This is crucial to identify strengths, weaknesses, and improvement areas. Also, the in-depth SWOT analysis helps an organization to understand the current level of automation, scalability, and resilience in the software delivery journey.
- Step 2: Educate the core teams i.e. software development and operations through regular training sessions and expand their knowledge horizons on the Platform Engineering principles and practices. Such learning and training initiatives help companies encourage a culture of learning and ensure that teams are well-equipped with the necessary skillsets and knowledge required to succeed in this new paradigm.
- Step 3: Establish Clear Objectives and Goals: Define clear objectives and goals for the transition to Platform Engineering, aligning them with the overall business strategy and objectives. Set measurable targets for improving automation, scalability, reliability, and developer productivity.
- Step 4: Invest in Infrastructure as Code (IaC): Invest in IaC tools and practices to automate the provisioning, configuration, and management of infrastructure resources. Adopt tools like Terraform, Ansible, or Kubernetes Operators to define infrastructure configurations as code and enable consistent and repeatable deployments.
- Step 5: Build Self-Service Platforms: Develop self-service platforms that empower development teams to provision resources, deploy applications, and manage environments autonomously. Provide developers with predefined templates, APIs, and tooling to streamline the development and deployment process.
- Step 6: Optimize CI/CD Pipelines: Optimize CI/CD pipelines to minimize cycle times, improve reliability, and facilitate rapid feedback loops. Integrate automated testing, performance monitoring, and release orchestration into CI/CD pipelines to ensure the quality and stability of software releases.
- Step 7: Cultivate a Culture of Collaboration: Foster a culture of collaboration, ownership, and continuous improvement across development, operations, and other relevant teams. Encourage cross-functional collaboration and communication to break down silos and drive alignment towards common goals.
- Step 8: Emphasize Scalability and Resilience: Prioritize the design of scalable, resilient, and observable architectures that can adapt to evolving business requirements and dynamic workloads. Incorporate principles such as fault tolerance, auto-scaling, and observability into platform designs to ensure high availability and performance.
- Step 9: Implement Feedback Loops: Implement feedback loops and mechanisms for collecting, analyzing, and acting upon feedback from stakeholders, users, and automated monitoring systems. Use feedback to identify areas for improvement and drive iterative refinements to platform engineering practices.
- Step 10: Measure and Iterate: Establish key performance indicators (KPIs) and metrics to track the progress and impact of the shift to Platform Engineering. Continuously measure and iterate on platform engineering practices to drive ongoing improvements and ensure alignment with business objectives.
By following these steps, companies can effectively prepare for the shift to Platform Engineering, enabling them to achieve greater agility, efficiency, and innovation in their software delivery processes.
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