Free e-book: Discover the world of AIoT
E-book: Discover the world of AIoT
NeedCode Logo
needCode's logo
Contact
Contact
Home » CI/CD environment for embedded systems

CI/CD environment for embedded systems

  • Staff Augmentation
Automated Code Development needCode

In a nutshell

This case study showcases the significant project undertaken by a dedicated DevOps engineer at needCode to create an Automatic Code Development System. The primary objective of this internal system was to streamline and optimize the daily work of developers, leading to increased productivity and improved work quality. The engineer actively collaborated in co-creating an automated code build, test, and release system, with a focus on modernizing the existing codebase. The ultimate goal was to support the development team in their day-to-day operations, fostering a culture of efficiency and innovation that would enable the company to grow at an accelerated pace.

Project overview

Project Duration:

03.2022 – ongoing

Team Setup:

1 x DevOps Engineer

Technology:

Docker, Git, GitLab CI/CD, Python

Client Requirements

The client sought to establish a comprehensive CI/CD (Continuous Integration/Continuous Delivery) environment to accommodate multiple embedded products and developers. The envisioned setup aimed to cover the entire development lifecycle, from building code for various platforms to conducting unit tests, system tests on real devices, and integration tests. Additionally, the environment needed to facilitate the generation of customer-facing SDKs.

Project Scope

The project’s scope encompassed the following key aspects:

  • Designing and developing an internal Automatic Code Development System tailored to the specific needs and workflows of the development team.
  • Implementing automation for code building, testing, and releasing processes, significantly reducing manual efforts and minimizing the chances of errors.
  • Co-creating and modernizing the existing codebase to align with industry best practices and ensure scalability and maintainability.
  • Providing ongoing support to the development team, addressing challenges, and optimizing the system for continuous improvement.
  • Collaborating with cross-functional teams to integrate the Automatic Code Development System into the company’s software development lifecycle.

 

Approach

The DevOps engineer adopted a systematic approach to accomplish the project objectives:

  • Conducted in-depth discussions with the development team to identify pain points and bottlenecks in the existing development process.
  • Designed a comprehensive plan for the Automatic Code Development System, aligning it with the team’s requirements and the company’s growth objectives.
  • Utilized cutting-edge technologies and automation tools to build a robust and efficient system for code building, testing, and release.
  • Collaborated with developers to modernize the codebase, optimizing it for better performance, maintainability, and scalability.
  • Provided continuous support, training, and knowledge sharing to ensure seamless adoption and utilization of the system.

Challenges and Goals

This project faced multiple challenges, from dealing with an old framework and complex dependencies to handling extensive code builds and limited testing environments.

  • Legacy Framework: Dealing with an outdated framework that was originally created to meet the company’s specific needs years ago.
  • Project Dependencies: Navigating complex dependencies between various projects, making modular updates or isolated testing challenging.
  • Hardware Constraints: Managing large inter-dependencies on actual hardware platforms where tests were executed, which limited testing scalability.
  • Extensive Codebase: Handling a large amount of code that required lengthy build times and long-running tests, impacting the speed of the CI/CD pipeline.
  • Resource Limitations: Operating within the confines of a limited number of test environments, which created bottlenecks in the testing process due to the high volume of tests.

Business Impact

The implementation of the Automatic Code Development System resulted in several notable business impacts:

  • Increased Developer Productivity: The streamlined development process and automated workflows allowed developers to focus more on coding and innovation, reducing time spent on manual tasks.
  • Improved Code Quality: The modernization of the codebase and automated testing led to enhanced code quality, reducing the number of defects and improving software reliability.
  • Faster Time-to-Market: The efficient code building and release processes accelerated the time-to-market for new features and products, giving the company a competitive edge.
  • Scalability and Growth: The system’s scalability and seamless integration allowed the company to handle increased workloads and support rapid business growth.

Results and Achievements

The DevOps engineer’s efforts and expertise resulted in significant achievements:

  • Successful development and implementation of the Automatic Code Development System tailored to the development team’s needs.
  • Automation of code building, testing, and release processes, reducing manual efforts and increasing efficiency.
  • Modernization of the codebase, enhancing performance, maintainability, and scalability.
  • Continued support and collaboration with the development team, fostering a culture of innovation and continuous improvement.

Conclusion

The DevOps engineer’s dedication and commitment to creating an Automatic Code Development System had a transformative impact on the company’s development process. By streamlining workflows, automating tasks, and modernizing the codebase, the engineer empowered the development team to work more efficiently, resulting in increased productivity and higher code quality. The successful implementation of the system laid a solid foundation for the company’s growth and competitiveness, positioning it as a leading player in the industry. This case study exemplifies the significance of DevOps practices and automation in driving business success and fostering a culture of continuous improvement within organizations.

Key points

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Aenean eleifend blandit iaculis. Cras massa neque, sagittis quis molestie quis, congue vitae lorem. Nullam neque sapien, condimentum vel odio a, placerat tincidunt massa. Fusce ac euismod quam. Nullam commodo luctus mi quis molestie. Fusce fringilla, elit ut fermentum tristique, elit leo vestibulum arcu, vitae iaculis nisl nibh eget libero. Vivamus sit amet aliquet eros, at laoreet purus. Aenean placerat, nulla a iaculis hendrerit, turpis quam luctus neque, id viverra turpis mi at magna. Praesent justo lorem, bibendum nec laoreet vehicula, vestibulum consequat erat. Proin sit amet neque urna. Donec ut mattis nulla. Ut blandit imperdiet nisi, at semper felis consequat eget. Donec faucibus ac nisi eget elementum. Mauris at malesuada magna. Ut sed tortor ipsum.

Etiam mattis est non placerat venenatis. Etiam sed diam a elit scelerisque accumsan. Sed lobortis fringilla leo, ut consequat elit euismod sed. Mauris tellus nisi, dignissim et nibh at, pulvinar hendrerit neque. Curabitur vel posuere tortor, at vulputate augue. Praesent felis odio, consectetur id sollicitudin sed, finibus at nulla. Duis ante lectus, pulvinar quis mattis ut, eleifend in tellus. Vivamus metus diam, lobortis sed enim nec, facilisis finibus risus. Vestibulum non metus lacinia, facilisis risus vel, feugiat diam. Duis facilisis, ante nec accumsan semper, ante purus congue lectus, sed sollicitudin nulla massa ut lectus.

Nulla facilisi. Integer convallis felis vitae libero egestas, convallis auctor nulla euismod. Integer at elit sollicitudin, sagittis augue et, suscipit turpis. Mauris semper purus eget justo posuere, sit amet imperdiet enim vehicula. Suspendisse imperdiet tellus nulla, ac pellentesque erat elementum eget. Pellentesque habitant morbi tristique senectus et netus et malesuada fames ac turpis egestas. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Maecenas sollicitudin auctor turpis quis vulputate.

Duis pharetra tellus purus, sed porta risus rhoncus vitae. Vivamus ac nisl quis leo vulputate pretium. Donec scelerisque, velit eget tempor bibendum, enim nisi dignissim diam, ac dignissim sem sem eget dui. In hac habitasse platea dictumst. Nam congue commodo elit, id tempus lorem malesuada a. Vestibulum id vestibulum nisi. Donec congue at ante vel aliquet. Etiam tempus risus quis malesuada imperdiet. Vestibulum ut nunc egestas, porttitor enim sit amet, convallis felis. Duis at ultricies lorem.

Do you need Smart Innovations?

Book a free discovery call and let's unlock new possibilities
Contact us

Also interesting

More case studies

Let's work on your next project together

Book a demo and discovery call with our CEO
to get a look at:
IoT Strategic Roadmap
Smart Product Development & Optimization
Cybersecurity & Consulting
Staff Augmentation
Bartek Kling
Bartek Kling
CEO
Book a discovery call
Needcode's logo
ISO 9001_2015
ISO - IEC 9001_2022
Services
IoT Strategic Roadmap Smart Product Development Smart Product Optimization Cybersecurity & compliance Staff Augmentation AI in IoT
UWB Sniffer Case studies About Blog Contact
Clutch logo
© 2025 needCode. All rights reserved.
Privacy Policy Cookies

Manufacturing

Modern manufacturing machines are typically equipped with IoT sensors that capture performance data. AIoT technology analyzes this sensor data, and based on vibration patterns, the AI predicts the machine's behavior and recommends actions to maintain optimal performance. This approach is highly effective for predictive maintenance, promoting safer working environments, continuous operation, longer equipment lifespan, and less downtime. Additionally, AIoT enhances quality control on production lines.

For example, Sentinel, a monitoring system used in pharmaceutical production by IMA Pharma, employs AI to evaluate sensor data along the production line. The AI detects and improves underperforming components, ensuring efficient machine operation and maintaining high standards in drug manufacturing.

Logistics & supply chain

IoT devices - from fleet vehicles and autonomous warehouse robots to scanners and beacons - generate large amounts of data in this industry. When combined with AI, this data can be leveraged for tracking, analytics, predictive maintenance, autonomous driving, and more, offering greater visibility into logistics operations and enhancing vendor partnerships.

Example: Amazon employs over 750,000 autonomous mobile robots to assist warehouse staff with heavy lifting, delivery, and package handling tasks. Other examples include AI-powered IoT devices such as cameras, RFID sensors, and beacons that help monitor goods' movement and track products within warehouses and during transportation. AI algorithms can also estimate arrival times and forecast delays by analyzing traffic conditions.

Retail

IoT sensors monitor movement and customer flow within a building, while AI algorithms analyze this data to offer insights into traffic patterns and product preferences. This information enhances understanding of customer behavior, helps prevent stockouts, and improves customer analytics to drive sales. Furthermore, AIoT enables retailers to deliver personalized shopping experiences by leveraging geographical data and individual shopping preferences.

For instance, IoT sensors track movement and customer flow, and AI algorithms process this information to reveal insights into traffic patterns and product preferences. This ultimately leads to better customer understanding, stockout prevention, and enhanced sales analytics.

Agriculture

Recent research by Continental reveals that over 27% of surveyed farmers utilize drones for aerial land analysis. These devices capture images of crops as they are and transmit them to a dashboard for further assessment. However, AI can enhance this process even further.

For example, AIoT-powered drones can photograph crops at various growth stages, assess plant health, detect diseases, and recommend optimal harvesting strategies to maximize yield. Additionally, these drones can be employed for targeted crop treatments, irrigation monitoring and management, soil health analysis, and more.

Smart Cities

Smart cities represent another domain where AIoT applications can enhance citizens' well-being, facilitate urban infrastructure planning, and guide future city development. In addition to traffic management, IoT devices equipped with AI can monitor energy consumption patterns, forecast demand fluctuations, and dynamically optimize energy distribution. AI-powered surveillance cameras and sensors can identify suspicious activities, monitor crowd density, and alert authorities to potential security threats in real-time, improving public safety and security.

For example, an AIoT solution has been implemented in Barcelona to manage water and energy sustainably. The city has installed IoT sensors across its water supply system to gather water pressure, flow rate, and quality data. AI algorithms analyze this information to identify leaks and optimize water usage. Similarly, smart grids have been introduced to leverage AI to predict demand and distribute energy efficiently, minimizing waste and emissions. As a result, these initiatives have enabled the city to reduce water waste by 25%, increase renewable energy usage by 17%, and lower greenhouse gas emissions by 19%.

Healthcare

Integrating AI and IoT in healthcare enables hospitals to deliver remote patient care more efficiently while reducing the burden on facilities. Additionally, AI can be used in clinical trials to preprocess data collected from sensors across extensive target and control groups.

For example, intelligent wearable technologies enable doctors to monitor patients remotely. In real-time, sensors collect vital signs such as heart rate, blood pressure, and glucose levels. AI algorithms then analyze this data, assisting doctors in detecting issues early, developing personalized treatment plans, and enhancing patient outcomes.

Smart Homes

The smart home ecosystem encompasses smart thermostats, locks, security cameras, energy management systems, heating, lighting, and entertainment systems. AI algorithms analyze data from these devices to deliver context-specific recommendations tailored to each user. This enables homeowners to use utilities more efficiently, create a personalized living space, and achieve sustainability goals.

For example, LifeSmart offers a comprehensive suite of AI-powered IoT tools for smart homes, connecting new and existing intelligent appliances and allowing customers to manage them via their smartphones. Additionally, they provide an AI builder framework for deploying AI on smart devices, edge gateways, and the cloud, enabling AI algorithms to process data and user behavior autonomously.

Maintenance (Post-Release Support)

When your product is successfully launched and available on the market we provide ongoing support and maintenance services to ensure your product remains competitive and reliable. This includes prompt resolution of any reported issues through bug fixes and updates.

We continuously enhance product features based on user feedback and market insights, optimizing performance and user experience.

Our team monitors product performance metrics to identify areas for improvement and proactively addresses potential issues. This phase aims to sustain product competitiveness, ensure customer satisfaction, and support long-term success in the market.

Commercialization (From MVP to Product

Our software team focuses on completing the full product feature range, enhancing the user interface and experience, and handling all corner cases. We prepare product software across the whole lifecycle by providing all necessary procedures, such as manufacturing support and firmware upgrade.

We also finalize the product's hardware design to ensure robustness, scalability and cost-effectiveness.

This includes rigorous testing procedures to validate product performance, reliability, and security. We manage all necessary certifications and regulatory compliance requirements to ensure the product meets industry standards and legal obligations.

By the end of this phase, your product is fully prepared for mass production and commercial deployment, with all documentation and certifications in place.

Prototyping (From POC to MVP)

Our development team focuses on implementing core product features and use cases to create a functional Minimum Viable Product (MVP). We advance to refining the hardware design, moving from initial concepts to detailed PCB design allowing us to assemble first prototypes. Updated documentation from the Design phase ensures alignment with current project status. A basic test framework is established to conduct preliminary validation tests.

This prepares the product for real-world demonstrations to stakeholders, customers, and potential investors.

This phase is critical for validating market readiness and functionality before proceeding to full-scale production.

Design (From Idea to POC)

We meticulously select the optimal technology stack and hardware components based on your smart product idea with detailed use cases and feature requirements (Market Requirements Document / Business Requirements Document). Our team conducts thorough assessments of costs, performance metrics, power consumption, and resource requirements.

Deliverables include a comprehensive Product Requirements Document (PRD), detailed Software Architecture plans, an Initial Test Plan outlining validation strategies, Regulatory Compliance Analysis to ensure adherence to relevant standards, and a Proof of Concept (POC) prototype implemented on breakout boards.

This phase aims to validate the technical feasibility of your concept and establish a solid foundation for further development.

If you lack a validated idea and MRD/BRD, consider utilizing our IoT Strategic Roadmap service to gain insights into target markets, user needs, and desired functionality. Having a structured plan in the form of an IoT Strategic Roadmap before development begins is crucial to mitigate complications in subsequent product development phases.