Collecting Device Metrics

There are many system health vitals that are useful to track aside from crashes and reboots. The options are numerous but you can expand the toggle to get a few examples.
  • RTOS related statistics
    • Amount of time spent in each RTOS task per unit time. This can help you understand if one task is starving the system
    • Heap high water marks
    • Stack high water marks
  • Time MCU was in different states
    • Stop, Sleep, Run Mode
    • Time each peripherals were active
  • Battery life drop per unit time.
  • Transport specific metrics (LTE, WiFI, BLE, LoRa, etc)
    • Amount of time transport was connected
    • Amount of connection attempts
  • Number of bytes being over transport per unit time.

In the Memfault UI, you can configure Alerts based on these metrics as well as explore metrics collected for any device.

Here is an example where the time bluetooth was connected, the amount of bytes sent and the battery life were tracked. In Memfault's UI, the data that gets collected from each device over time, is visualized in customizable graphs:


The Memfault SDK includes a "metrics" component that makes it easy to collect this type on information on an embedded device. In the sections below we will walk through how to integrate the component and get started using it!

Integration Steps

Prerequisite: This guide assumes you have already completed the minimal port of the Memfault SDK to collect coredumps. If you have not, check out the getting started guides that are available for the GCC, IAR, or ARM MDK Compiler.

1. Add Metrics source files to Build System

If you are using the makefiles/ or cmake/Memfault.cmake to automatically collect sources, there is no work to do!

If you are using another build system, you just need to add the following file to the build system:


You need to add this include path as well:


2. Create "memfault_metrics_heartbeat_config.def" and define a metric

In this guide we'll use the default file name for the metrics definition file (memfault_trace_reason_user_config.def) and assume its located at $PROJECT_ROOT/config.

In this file you will define all the metrics you would like to track using the MEMFAULT_METRICS_KEY_DEFINE macro. In this guide we will walk through a simple example of tracking the high water mark of the stack for a "Main Task" in our application and the number of bytes sent out over a bluetooth connection.

// File $PROJECT_ROOT/config/memfault_metrics_heartbeat_config.def
MEMFAULT_METRICS_KEY_DEFINE(MainTaskStackHwm, kMemfaultMetricType_Unsigned)
MEMFAULT_METRICS_KEY_DEFINE(BtBytesSent, kMemfaultMetricType_Unsigned)

You will also need to make sure the file is in yourinclude path list. Expand the instructions below for instructions on how to set this define based on the compiler you are using:

GCC Compiler

With GCC you will need to add a new CFLAG and update your include path. Here's an example of how the addition would look if you are using Make as your build system

# [ ... other parts of build system ... ]

ARM IAR Compiler

With IAR, right click on your project and select "Options". You will need to add the include directory where the memfault_metrics_heartbeat_config.def is located:

ARM MDK Compiler

With the ARM MDK you can right click on the Project and select "Options". You will then need to navigate to the C/C++ tab and add config to the "Include Paths" list.

3. Initialize event storage

All events generated in the Memfault SDK are stored and transmitted using a compressed format (CBOR). As they await to be sent from the Memfault data packetizer, they are stored in the "event storage" core component which can be initialized as follows:

#include "memfault/core/event_storage.h"
// [...]
int main(void) {
// [... other initialization code ...]
// NOTE: memfault_metrics_heartbeat_compute_worst_case_storage_size()
// can be used to determine max storage size needed for one event
static uint8_t s_event_storage[100];
const sMemfaultEventStorageImpl *evt_storage =
memfault_events_storage_boot(s_event_storage, sizeof(s_event_storage));

4. Implement metrics timer platform dependency

The metrics subsystem requires one "timer" to control when data is aggregated into a "heartbeat". When the heartbeat subsystem is booted, a dependency function memfault_platform_metrics_timer_boot will be called to set up this timer. Most RTOSs have a software timer implementation that can be directly mapped to the API or a hardware timer can be used as well. The expectation is that callback will be invoked every period_sec (which by default is once / hour).

#include "memfault/metrics/platform/timer.h"
// [...]
bool memfault_platform_metrics_timer_boot(uint32_t period_sec,
MemfaultPlatformTimerCallback callback) {
// [... platform specific code to setup timer ...]
return true; // indicates setup was successful

5. Implement time since boot platform dependency

The heartbeat metrics subsystem supports a timer type (kMemfaultMetricType_Timer) which can be used to easily track durations (i.e. time spent in MCU stop mode) as well as overall system uptime. To support this, the memfault_platform_get_time_since_boot_ms() function needs to be implemented. Typically this information is derived from either a system's Real Time Clock (RTC) or the SysTick counter used by an RTOS.

#include "memfault/core/platform/core.h"
// [...]
uint64_t memfault_platform_get_time_since_boot_ms(void) {
// TODO: Compute current time since boot in milliseconds and return
// the result

6. Initialize Heartbeat Module

To start the metrics subsystem, you just need to call the memfault_metrics_boot API when the system restarts and pass it the evt_storage context we set up in step 2. After this call a heartbeat will be serialized to event storage at the rate specified (default is once / hour).

#include "memfault/metrics/metrics.h"
// [...]
int memfault_subsystem_boot(void) {
// [...]
int rv = memfault_metrics_boot(evt_storage);
// NOTE: a non-zero value indicates a configuration error took place

7. Start setting metric values

There's a set of APIs in memfault/metrics/metrics.h which can be used to easily update heartbeats as events take place. The updates occur in RAM so there is negligible overhead introduced. Here's an example:

#include "memfault/metrics/metrics.h"
// [ ... ]
void bluetooth_driver_send_bytes(const void *data, size_t data_len) {
memfault_metrics_heartbeat_add(MEMFAULT_METRICS_KEY(BtBytesSent), data_len);
// [ ... code to send bluetooth data ... ]

8. [Optional] Implement memfault_metrics_heartbeat_collect_data

memfault_metrics_heartbeat_collect_data will always be called at the very beginning of heartbeat serialization. By default this is a weak empty function but you will want to implement it if there's data you want to put in the heartbeat stored in other parts of the system. The MainTaskStackHwm we are tracking is a good example for why we would want to implement this:

#include "memfault/metrics/platform/overrides.h"
// [...]
void memfault_metrics_heartbeat_collect_data(void) {
// NOTE: When using FreeRTOS we can just call
// "uxTaskGetStackHighWaterMark(s_main_task_tcb)"
const uint32_t stack_high_water_mark = // TODO: code to get high water mark
MEMFAULT_METRICS_KEY(MainTaskStackHwm), stack_high_water_mark);

9. Publish heartbeat information to the Memfault cloud

Extensive details about how data from the Memfault SDK makes it to the cloud can be found here. In short, all data is published via the same "chunk" REST endpoint.

#include "memfault/core/data_packetizer.h"
// [...]
bool try_send_memfault_data(void) {
// buffer to copy chunk data into
uint8_t buf[USER_CHUNK_SIZE];
size_t buf_len = sizeof(buf);
bool data_available = memfault_packetizer_get_chunk(buf, &buf_len);
if (!data_available) {
return false; // no more data to send
// send payload collected to chunks/ endpoint
user_transport_send_chunk_data(buf, buf_len);
return true;
void send_memfault_data(void) {
// [... user specific logic deciding when & how much data to send
while (try_send_memfault_data()) { }

10. [Optional] Initial Setup & Debug APIs

While integrating the heartbeat metrics subsystem or adding new metrics, there are a few easy ways you can debug and test the new code. Notably:

  • memfault_metrics_heartbeat_debug_trigger can be called at any time to trigger a heartbeat serialization (so you don't have to wait for the entire interval to get data to flush)
  • memfault_metrics_heartbeat_debug_print can be called to dump the current value of all the metrics being tracked