How to Follow DevOps Practices in Embedded Systems

DevOps has revolutionized software development and operations by fostering collaboration, automation, and continuous delivery. But how do these principles translate to the world of embedded systems, where software runs on specialized hardware often without cloud connectivity? This blog post explores how to successfully adopt DevOps practices in embedded systems development, the unique challenges faced, and the cutting-edge tools and techniques enabling continuous integration and deployment-even in constrained environments.

Understanding DevOps in Embedded Systems

DevOps is a culture and set of practices that unify software development (Dev) and IT operations (Ops) to shorten development cycles, increase deployment frequency, and deliver reliable software. While widely adopted in cloud and web applications, embedded systems pose distinct challenges:

Hardware dependency: Software tightly coupled with specific hardware platforms.
Limited connectivity: Many embedded devices operate offline or with intermittent network access.
Resource constraints: Limited CPU, memory, and storage compared to general-purpose computers.
Deployment complexity: Firmware updates often require physical access or specialized update mechanisms.

Despite these hurdles, many DevOps principles can and should be applied to embedded systems development to improve quality, speed, and reliability.

Key DevOps Practices Applicable to Embedded Systems

1. Continuous Integration (CI)

Automate the building and testing of embedded software whenever code changes are committed. Use cross-compilation toolchains and hardware simulators or emulators to run automated tests early in the pipeline.

2. Automated Testing

Implement unit tests, integration tests, and hardware-in-the-loop (HIL) testing to validate code against real or simulated hardware. Automated test suites reduce bugs and regressions.

3. Version Control and Branching Strategies

Maintain all source code, build scripts, and configuration files in version control systems like Git. Employ branching models (e.g., GitFlow) to manage feature development, bug fixes, and releases.

4. Infrastructure as Code (IaC)

Use scripts and configuration management tools to automate environment setup for builds and tests, ensuring consistency and repeatability.

5. Continuous Delivery (CD) and Deployment

Automate packaging and deployment of firmware or software images to test devices and eventually production hardware, minimizing manual intervention.

6. Monitoring and Feedback Loops

Collect telemetry and logs from embedded devices in the field to monitor performance and detect issues early, feeding insights back into development.

Market Trends Driving Embedded DevOps Adoption

69% of new projects now use RTOS instead of bare-metal programming
42% reduction in field failures with simulation-first development
57% faster certification through automated compliance testing

Top Embedded Systems Tools and Frameworks for 2025

Choosing the right tools and frameworks is critical for the success of embedded software projects-from automotive ECUs to IoT devices and industrial controllers. In 2025, the embedded development landscape is shaped by increasingly complex systems, real-time constraints, security demands, and the need for scalable DevOps and CI/CD pipelines. Below is an updated, comprehensive list of the most relevant open-source and commercial tools widely adopted by embedded teams today.

Build Automation & IDEs

VS Code + PlatformIO (Open Source)
A lightweight, hardware-agnostic IDE supporting STM32, ESP32, AVR, and more. Features integrated debugging, unit testing, and CI tools.
platformio.org
SEGGER Embedded Studio (Commercial)
Optimized for ARM Cortex-M and RISC-V MCUs, with ultra-fast compile times and integrated J-Link debugging.
segger.com
IAR Embedded Workbench (Commercial)
Industry-standard C/C++ compiler with MISRA and functional safety certifications, widely used in automotive and medical.
iar.com
STM32CubeIDE (Free)
Eclipse-based IDE tailored for STM32 MCUs, with integrated peripheral configuration and AI support.
st.com
Keil MDK (Commercial)
Comprehensive ARM Cortex-M development environment with CMSIS and RTX RTOS support.
keil.com
MPLAB X IDE (Free/Commercial)
Microchip’s IDE for PIC, dsPIC, AVR, and SAM MCUs with strong integration for secure and mixed-signal designs.
microchip.com
Qt Creator (Open Source/Commercial)
Cross-platform IDE with UI design tools, widely used for embedded GUI applications across automotive, IoT, and consumer devices.
qt.io
PyCharm (Open Source/Commercial)
JetBrains IDE for Python development, useful for embedded scripting, automation, and remote development.
jetbrains.com/pycharm

CI/CD Platforms

Jenkins (Open Source)
Extensible automation server with plugins for embedded build, test, and deployment automation.
jenkins.io
GitHub Actions (Cloud/On-prem)
Flexible workflows configurable for embedded cross-compilation, testing, and deployment with self-hosted runners.
github.com/features/actions
CircleCI (Cloud/Commercial)
Cloud-native CI/CD with support for containerized embedded builds and hardware simulator integration.
circleci.com

Hardware Simulators / Emulators

QEMU (Open Source)
Emulates various embedded architectures enabling early software testing without physical hardware.
qemu.org
Renode (Open Source)
SoC-level emulator supporting multi-core and multi-node embedded systems, ideal for CI pipelines.
renode.io
OpenOCD (Open Source)
Debugger and programmer for embedded hardware supporting JTAG/SWD interfaces.
openocd.org
Vendor-Specific Simulators
Provided by MCU vendors like STM32CubeIDE, NXP MCUXpresso, TI Code Composer Studio.

Automated Testing Frameworks

Unity & Ceedling (Open Source)
Lightweight unit testing and test automation frameworks for embedded C projects.
throwtheswitch.org/unity
Google Test (gtest) (Open Source)
Popular C++ testing framework usable in embedded Linux and RTOS environments.
github.com/google/googletest
CppUTest (Open Source)
Unit testing framework for C and C++ designed for embedded environments.
cpputest.github.io
Appium (Open Source)
Cross-platform test automation framework for mobile apps and embedded GUIs, ideal for testing embedded Linux/Android devices and mobile apps interacting with embedded hardware.
appium.io
AltUnityTester (Commercial)
Testing framework for Unity-based embedded HMIs and games, often used alongside Appium for comprehensive UI automation.

Over-the-Air (OTA) Update Frameworks

Mender (Open Source/Commercial)
Secure OTA update manager supporting atomic updates and rollback on embedded Linux devices.
mender.io
Balena (Commercial)
Container-based OTA platform for embedded Linux devices with fleet management.
balena.io
SWUpdate (Open Source)
Flexible Linux-based software update framework supporting dual-bank and A/B updates.
sbabic.github.io/swupdate
Hawkbit (Open Source)
Eclipse project for device management and software updates for IoT and embedded devices.
eclipse.org/hawkbit

Configuration Management & Automation

Ansible (Open Source)
Agentless automation for environment provisioning, build farm setup, and deployment orchestration.
ansible.com
Puppet (Open Source/Commercial)
Configuration management tool to automate embedded build environments and testing infrastructure.
puppet.com
Chef (Open Source/Commercial)
Infrastructure automation platform used for managing embedded development environments.
chef.io
Custom Scripts & Docker
Many teams use Docker containers for reproducible build environments and custom scripts for automation.

Modeling & Code Generation

Simulink Embedded Coder (Commercial)
Model-based design and automatic code generation for real-time embedded applications.
mathworks.com
MATLAB (Commercial)
Numerical computing environment used for algorithm development and simulation in embedded projects.
mathworks.com

Summary Table

Category	Open Source Examples	Commercial Examples
Build Automation & IDEs	PlatformIO + VS Code, PyCharm, Eclipse CDT	SEGGER Embedded Studio, IAR Embedded Workbench, STM32CubeIDE, Keil MDK, MPLAB X, Qt Creator
CI/CD Platforms	Jenkins, GitHub Actions	CircleCI, GitHub Enterprise/Cloud
Hardware Simulators	QEMU, Renode, OpenOCD	Vendor-specific simulators (STM32CubeIDE, NXP MCUXpresso)
Automated Testing	Unity, Ceedling, Google Test, CppUTest, Appium	AltUnityTester, commercial IDE testing tools
OTA Update Frameworks	Mender, SWUpdate, Hawkbit	Balena, Mender Enterprise
Configuration Management	Ansible, Puppet, Chef	Puppet Enterprise, Chef Automate
Modeling & Code Generation	-	Simulink Embedded Coder, MATLAB

Challenges in Automating Embedded System Deployment

Automating deployment in embedded systems is more complex than in cloud-native applications due to:

Hardware Diversity: Multiple hardware variants require tailored builds and deployment strategies.
Network Constraints: Devices may have limited or no connectivity, complicating remote updates.
Safety and Reliability: Firmware updates must be fail-safe to avoid bricking devices, often requiring dual-bank or rollback mechanisms.
Security: Secure boot, signed firmware, and encrypted communication are essential to prevent malicious updates.
Testing on Real Hardware: Automated tests often require physical devices or complex simulators, increasing infrastructure costs.

Essential CI/CD Components for Embedded Systems

Component	Cloud-Native Approach	Embedded Adaptation
Build Server	Cloud-based runners	On-prem servers with cross-compilation toolchains
Testing	Virtual machines	Hardware-in-loop (HIL) rigs + Renode emulation
Artifact Storage	S3 buckets	Local Nexus/Artifactory with binary versioning

Proven Methodology: Controlled Continuous Deployment (CCD)

Phased Rollouts: Deploy to 5% field devices first
Atomic Updates: Dual-bank flash with rollback protection[6]
Telemetry-Driven Validation: Monitor 15+ device health metrics pre-full rollout

Latest Technologies in Embedded System Upgrades

Over-the-Air (OTA) Updates

OTA updates enable remote firmware and software upgrades without physical access, critical for IoT and connected devices. Modern OTA solutions incorporate:

Delta Updates: Only changes are transmitted, reducing bandwidth.
Atomic Updates: Ensures updates are fully applied or rolled back safely.
Security: Firmware signing and encrypted transfer to prevent tampering.

Mobile OS Upgrades in Embedded Devices

Embedded systems running mobile OSes like Android Things or embedded Linux benefit from standardized update frameworks such as A/B system updates, which allow seamless upgrades with fallback options.

Containerization and Virtualization

Emerging trends include lightweight containerization (e.g., Balena Engine) in embedded Linux devices to isolate applications and streamline deployment.

One Practical Example: Tesla’s Embedded DevOps Approach

Tesla’s vehicles are a prime example of embedded systems benefiting from DevOps practices. They use continuous integration pipelines to build and test vehicle firmware, automated OTA updates to deploy new features and fixes, and telemetry monitoring to gather real-world data for rapid iteration. This approach enables Tesla to deliver software improvements frequently and reliably without physical recalls.

For more details, visit Tesla’s software update overview: Tesla Software Updates

Step-by-Step Guide to Implement DevOps in Embedded Systems

Assess Your Current Workflow: Identify manual bottlenecks in build, test, and deployment processes.
Set Up Version Control: Ensure all code and configurations are in Git or similar.
Automate Builds: Use CI tools to compile and link code on every commit.
Integrate Automated Testing: Develop unit and integration tests; run them in CI pipelines.
Simulate Hardware: Use emulators or simulators to test code without physical devices.
Implement OTA Update Mechanisms: Choose or develop a secure OTA framework.
Deploy to Test Devices Automatically: Use CD pipelines to flash test devices.
Monitor Devices in Production: Collect logs and telemetry for continuous feedback.
Iterate and Improve: Use metrics and feedback to refine processes continuously.

Future Outlook and Emerging Trends

AI-Driven Testing: Automated test generation and anomaly detection using AI will enhance quality assurance.
Edge Computing Integration: Embedded devices will increasingly process data locally, requiring DevOps to support distributed architectures.
Standardization of Embedded DevOps Tools: More specialized tools and frameworks tailored for embedded environments will emerge.
Security-First DevOps: With rising cyber threats, embedding security into every stage of the DevOps pipeline will become standard practice.

Summary

Adopting DevOps in embedded systems is not only possible but essential to keep pace with modern software demands. By leveraging continuous integration, automated testing, and secure OTA updates, embedded teams can deliver high-quality software faster and more reliably. While challenges like hardware diversity and connectivity constraints exist, emerging tools and frameworks are making embedded DevOps increasingly practical. Organizations embracing these practices will gain a competitive edge in innovation and customer satisfaction.