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Iteration Leads To Powerful Results in Design.

“You can only make it once but you can make it better as many times as you need”

Clients rarely arrive at a design firm with a detailed project roadmap in hand. Instead, they have a hazy idea of what they require – make it pop, bring a wow factor, make it look good, and so on. In such cases, the designer’s main challenge is to get into the clients’ heads and create things exactly how they want the product to look, even if the clients themselves lack understanding.

The best way to ensure your design is a perfect fit is to work in iterations. This allows us to create a solution that satisfies the client and meets the needs of the customer.

Iteration Leads To Powerful Results in Design

Iteration, the most fundamental concept in design

In its most basic form, iteration is simply a series of steps that you repeat, tweaking and improving your product each time. With every repetition, iteration aims to move a little bit closer to the optimal situation. As designers, we are always looking to improve on the current design approach and this is where an iterative design process comes in handy.

​​You can think of the iterative design process as a continuous cycle of prototyping, testing, and making adjustments and refinements – it is an ongoing, incremental process leading to the best possible outcome.

The 1997 version of Apple.com
The 1997 version of Apple.com
The 2022 version of Apple.com
The 2022 version of Apple.com

It’s fascinating to observe how the product gradually changed the appearance of its own homepage, going from its ugly beginnings to its current minimalism to align with the current design trends and in response to user feedback.

The do’s and don’ts of design Iteration

  1. Do: Fail Faster
    Embrace trial and error to learn what not to do even when you miss the mark by adopting a “fail faster” mentality. Since failure is unavoidable, it is best to deal with it as soon as possible while still taking note of what can be learned.
  1. Do: Be Flexible
    Design methodologies still allow for some flexibility even though they have strict guidelines to help us express our creative freedom without devoting too much time to each iteration. In the end, we must choose which opportunities to prioritize first, when to iterate or test more, and how many concurrent design iteration processes should be running at once.

    These choices are largely based on intuition and experience, utilizing any data and research that may be available.
  2. Do: Work Asynchronously
    Utilizing all resources (tools, teammates, etc.), complete tasks as quickly as possible by allowing other designers to work on unrelated aspects of the product in parallel and developers to start putting validated solutions into practice. By doing both of these, product turnaround times will be drastically reduced.
  1. Do: Collaborate and Listen
    Which issue ought to be resolved? What version is the best? Is the testable prototype ready? What do all of these comments mean? We are confident in our ability to respond to these questions because of the unique expertise and new perspective that our teamwork partners have to offer.
Iteration in Design
  1. Don’t: Try to Solve Everything
    Avoid attempting to solve new problems once the issue we’re solving during the design iteration process has been selected. Even though it’s common to find areas that can be improved (during testing or through observation), make a note of them since they might make excellent starting points for subsequent iterations.

    We cannot measure the effect that design iterations are having on key metrics if we allow scope creep to occur.

Benefits of Iteration in Design

  1. It Saves Resources
    Because iterative design processes frequently give us user feedback (or stakeholder feedback, at the very least), which drives us forward at a steady pace, they almost always save the most time.

    Positive feedback can help us know when we’re heading in the right direction, and negative feedback can help us know when we’re heading in the wrong direction, so we’re always moving forward and never really wasting any precious time.

    Without any feedback, we run the risk of racing to the finish line only to fall short, wasting a lot of time and bandwidth. Design iteration is also the most economical choice because time is money.
  1. It Facilitates Collaboration
    Healthy collaboration is facilitated by an iterative design process because it gives stakeholders the chance to provide feedback and even share their own ideas. This gives us information that we wouldn’t have learned on our own because we can only see things from our own point of view.
  1. It Addresses Real User Needs
    Designers have a tendency to work alone if they don’t follow a methodical iteration process (especially one that includes collaboration). Being siloed makes us overly introspective, which causes us to jump to conclusions and engage in counterproductive perfectionist tendencies.

    But using an iterative design process makes sure we remain focused on user needs and make choices based on their input. Additionally, prioritizing the next best design improvement method rather than concentrating on haphazard ones helps us.
  1. Facilitates Regular Updates
    Instead of just dumping the end result on stakeholders and keeping them in the dark until then, an iterative design process allows us to regularly update them on the status of the project.

    It means that developers can start even while the design is still in progress, which is especially advantageous for developers.

In Conclusion

Designers can quickly create and test ideas thanks to the iterative design. Those that show promise can be quickly iterated until they take enough shape to be developed, while those that don’t show promise can be abandoned right away.

The 90’s version of arngren.com
The 90’s version of arngren.com

Here’s an example of what happens when we don’t iterate – this 90s website is still around.

So do it, then do it again!

About the Author: Unnathi is a UI/UX designer, currently working at Mantra Labs. She is passionate about research and has expertise in building digital systems that provide engaging experiences. 

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Platform Engineering: Accelerating Development and Deployment

The software development landscape is evolving rapidly, demanding unprecedented levels of speed, quality, and efficiency. To keep pace, organizations are turning to platform engineering. This innovative approach empowers development teams by providing a self-service platform that automates and streamlines infrastructure provisioning, deployment pipelines, and security. By bridging the gap between development and operations, platform engineering fosters standardization, and collaboration, accelerates time-to-market, and ensures the delivery of secure and high-quality software products. Let’s dive into how platform engineering can revolutionize your software delivery lifecycle.

The Rise of Platform Engineering

The rise of DevOps marked a significant shift in software development, bringing together development and operations teams for faster and more reliable deployments. As the complexity of applications and infrastructure grew, DevOps teams often found themselves overwhelmed with managing both code and infrastructure.

Platform engineering offers a solution by creating a dedicated team focused on building and maintaining a self-service platform for application development. By standardizing tools and processes, it reduces cognitive overload, improves efficiency, and accelerates time-to-market.  

Platform engineers are the architects of the developer experience. They curate a set of tools and best practices, such as Kubernetes, Jenkins, Terraform, and cloud platforms, to create a self-service environment. This empowers developers to innovate while ensuring adherence to security and compliance standards.

Role of DevOps and Cloud Engineers

Platform engineering reshapes the traditional development landscape. While platform teams focus on building and managing self-service infrastructure, application teams handle the development of software. To bridge this gap and optimize workflows, DevOps engineers become essential on both sides.

Platform and cloud engineering are distinct but complementary disciplines. Cloud engineers are the architects of cloud infrastructure, managing services, migrations, and cost optimization. On the other hand, platform engineers build upon this foundation, crafting internal developer platforms that abstract away cloud complexity.

Key Features of Platform Engineering:

Let’s dissect the core features that make platform engineering a game-changer for software development:

Abstraction and User-Friendly Platforms: 

An internal developer platform (IDP) is a one-stop shop for developers. This platform provides a user-friendly interface that abstracts away the complexities of the underlying infrastructure. Developers can focus on their core strength – building great applications – instead of wrestling with arcane tools. 

But it gets better. Platform engineering empowers teams through self-service capabilities.This not only reduces dependency on other teams but also accelerates workflows and boosts overall developer productivity.

Collaboration and Standardization

Close collaboration with application teams helps identify bottlenecks and smooth integration and fosters a trust-based environment where communication flows freely.

Standardization takes center stage here. Equipping teams with a consistent set of tools for automation, deployment, and secret management ensures consistency and security. 

Identifying the Current State

Before building a platform, it’s crucial to understand the existing technology landscape used by product teams. This involves performing a thorough audit of the tools currently in use, analyzing how teams leverage them, and identifying gaps where new solutions are needed. This ensures the platform we build addresses real-world needs effectively.

Security

Platform engineering prioritizes security by implementing mechanisms for managing secrets such as encrypted storage solutions. The platform adheres to industry best practices, including regular security audits, continuous vulnerability monitoring, and enforcing strict access controls. This relentless vigilance ensures all tools and processes are secure and compliant.

The Platform Engineer’s Toolkit For Building Better Software Delivery Pipelines

Platform engineering is all about streamlining and automating critical processes to empower your development teams. But how exactly does it achieve this? Let’s explore the essential tools that platform engineers rely on:

Building Automation Powerhouses:

Infrastructure as Code (IaC):

CI/CD Pipelines:

Tools like Jenkins and GitLab CI/CD are essential for automating testing and deployment processes, ensuring applications are built, tested, and delivered with speed and reliability.

Maintaining Observability:

Monitoring and Alerting:

Prometheus and Grafana is a powerful duo that provides comprehensive monitoring capabilities. Prometheus scrapes applications for valuable metrics, while Grafana transforms this data into easy-to-understand visualizations for troubleshooting and performance analysis.

All-in-one Monitoring Solutions:

Tools like New Relic and Datadog offer a broader feature set, including application performance monitoring (APM), log management, and real-time analytics. These platforms help teams to identify and resolve issues before they impact users proactively.

Site Reliability Tools To Ensure High Availability and Scalability:

Container Orchestration:

Kubernetes orchestrates and manages container deployments, guaranteeing high availability and seamless scaling for your applications.

Log Management and Analysis:

The ELK Stack (Elasticsearch, Logstash, Kibana) is the go-to tool for log aggregation and analysis. It provides valuable insights into system behavior and performance, allowing teams to maintain consistent and reliable operations.

Managing Infrastructure

Secret Management:

HashiCorp Vault protects secretes, centralizes, and manages sensitive data like passwords and API keys, ensuring security and compliance within your infrastructure.

Cloud Resource Management:

Tools like AWS CloudFormation and Azure Resource Manager streamline cloud deployments. They automate the creation and management of cloud resources, keeping your infrastructure scalable, secure, and easy to manage. These tools collectively ensure that platform engineering can handle automation scripts, monitor applications, maintain site reliability, and manage infrastructure smoothly.

The Future is AI-Powered:

The platform engineering landscape is constantly evolving, and AI is rapidly transforming how we build and manage software delivery pipelines. The tools like Terraform, Kubecost, Jenkins X, and New Relic AI facilitate AI capabilities like:

  • Enhance security
  • Predict infrastructure requirements
  • Optimize resource security 
  • Predictive maintenance
  • Optimize monitoring process and cost

Conclusion

Platform engineering is becoming the cornerstone of modern software development. Gartner estimates that by 2026, 80% of development companies will have internal platform services and teams to improve development efficiency. This surge underscores the critical role platform engineering plays in accelerating software delivery and gaining a competitive edge.

With a strong foundation in platform engineering, organizations can achieve greater agility, scalability, and efficiency in the ever-changing software landscape. Are you ready to embark on your platform engineering journey?

Building a robust platform requires careful planning, collaboration, and a deep understanding of your team’s needs. At Mantra Labs, we can help you accelerate your software delivery. Connect with us to know more. 

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