| API | Description | Use Case |
|---|---|---|
KeyValueStorage | Typed key-value map persisted to NvM backend | Configuration, calibration values, counters, flags |
FileStorage | POSIX-like open/read/write file abstraction | Structured data files, certificates, ML model weights |
Two Storage APIs
Key-Value Storage Usage
#include <ara/per/key_value_storage.h>
// Open KVS declared as portPrototype in Application Design
auto kvsResult = ara::per::OpenKeyValueStorage(
ara::core::InstanceSpecifier{"CalibApp/CalibKVS"});
auto& kvs = kvsResult.Value();
// Read with default fallback
auto offset = kvs.GetValue<float>("sensorOffset")
.ValueOr(0.0f);
// Write and sync to persistent storage
kvs.SetValue("sensorOffset", 0.25f);
kvs.SyncToStorage(); // Must be called explicitly to flush
// Remove a key
kvs.RemoveKey("legacyConfig");
kvs.SyncToStorage();
⚠️ SyncToStorage()
KVS writes are buffered in RAM until SyncToStorage() is called. If power is lost before this call, all unsaved changes are lost. For safety-critical persistent values (odometer, fault counters), call SyncToStorage() immediately after each write.
File Storage Usage
#include <ara/per/file_storage.h>
auto fsResult = ara::per::OpenFileStorage(
ara::core::InstanceSpecifier{"CertApp/CertStorage"});
auto& fs = fsResult.Value();
// Open a logical file (path is relative to storage root)
auto fileResult = fs.OpenFileReadWrite("tls_cert.pem");
auto& file = fileResult.Value();
// Read content
ara::core::Vector<ara::core::Byte> buffer(4096);
auto bytesRead = file.Read(buffer);
// Write
ara::core::String certData = LoadCert();
file.Write(ara::core::Span<const ara::core::Byte>{
reinterpret_cast<const ara::core::Byte*>(certData.data()),
certData.size()});
Redundancy Modes
| Mode | Behaviour | Storage Overhead |
|---|---|---|
NONE | Single copy, no integrity checking | 1x |
REDUNDANT | Two copies with CRC; automatic recovery from secondary if primary corrupt | 2x + CRC overhead |
REDUNDANT_MEDIATED | Three copies; voting algorithm selects majority-consistent copy | 3x + overhead |
💡 littlefs vs ext4
On raw NOR/NAND flash targets, ara::per typically uses littlefs as the backing filesystem — it provides power-safe writes and wear leveling without requiring a filesystem journal. On eMMC-based ECUs, ext4 with journaling is common. The ara::per API is filesystem-agnostic.
Summary
ara::per provides the persistent storage abstraction for Adaptive Applications, replacing Classic's NvM/MemStack. Key-Value Storage handles typed configuration data; File Storage handles raw byte streams. Redundancy modes add integrity protection at the cost of storage overhead.
🔬 Deep Dive — Core Concepts Expanded
This section builds on the foundational concepts covered above with additional technical depth, edge cases, and configuration nuances that separate competent engineers from experts. When working on production ECU projects, the details covered here are the ones most commonly responsible for integration delays and late-phase defects.
Key principles to reinforce:
- Configuration over coding: In AUTOSAR and automotive middleware environments, correctness is largely determined by ARXML configuration, not application code. A correctly implemented algorithm can produce wrong results due to a single misconfigured parameter.
- Traceability as a first-class concern: Every configuration decision should be traceable to a requirement, safety goal, or architecture decision. Undocumented configuration choices are a common source of regression defects when ECUs are updated.
- Cross-module dependencies: In tightly integrated automotive software stacks, changing one module's configuration often requires corresponding updates in dependent modules. Always perform a dependency impact analysis before submitting configuration changes.
🏭 How This Topic Appears in Production Projects
- Project integration phase: The concepts covered in this lesson are most commonly encountered during ECU integration testing — when multiple software components from different teams are combined for the first time. Issues that were invisible in unit tests frequently surface at this stage.
- Supplier/OEM interface: This is a topic that frequently appears in technical discussions between Tier-1 ECU suppliers and OEM system integrators. Engineers who can speak fluently about these details earn credibility and are often brought into critical design review meetings.
- Automotive tool ecosystem: Vector CANoe/CANalyzer, dSPACE tools, and ETAS INCA are the standard tools used to validate and measure the correct behaviour of the systems described in this lesson. Familiarity with these tools alongside the conceptual knowledge dramatically accelerates debugging in real projects.
⚠️ Common Mistakes and How to Avoid Them
- Assuming default configuration is correct: Automotive software tools ship with default configurations that are designed to compile and link, not to meet project-specific requirements. Every configuration parameter needs to be consciously set. 'It compiled' is not the same as 'it is correctly configured'.
- Skipping documentation of configuration rationale: In a 3-year ECU project with team turnover, undocumented configuration choices become tribal knowledge that disappears when engineers leave. Document why a parameter is set to a specific value, not just what it is set to.
- Testing only the happy path: Automotive ECUs must behave correctly under fault conditions, voltage variations, and communication errors. Always test the error handling paths as rigorously as the nominal operation. Many production escapes originate in untested error branches.
- Version mismatches between teams: In a multi-team project, the BSW team, SWC team, and system integration team may use different versions of the same ARXML file. Version management of all ARXML files in a shared repository is mandatory, not optional.
📊 Industry Note
Engineers who master both the theoretical concepts and the practical toolchain skills covered in this course are among the most sought-after professionals in the automotive software industry. The combination of AUTOSAR standards knowledge, safety engineering understanding, and hands-on configuration experience commands premium salaries at OEMs and Tier-1 suppliers globally.