diff --git a/Project.toml b/Project.toml
index 19811f6c8..259ba6a13 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
 name = "FluxTraining"
 uuid = "7bf95e4d-ca32-48da-9824-f0dc5310474f"
 authors = ["lorenzoh <lorenz.ohly@gmail.com>"]
-version = "0.3.2"
+version = "0.3.3"
 
 [deps]
 BSON = "fbb218c0-5317-5bc6-957e-2ee96dd4b1f0"
diff --git a/src/FluxTraining.jl b/src/FluxTraining.jl
index 3224cb6b2..19221f24b 100644
--- a/src/FluxTraining.jl
+++ b/src/FluxTraining.jl
@@ -55,6 +55,7 @@ include("./callbacks/earlystopping.jl")
 include("./callbacks/custom.jl")
 include("./callbacks/metrics.jl")
 include("./callbacks/recorder.jl")
+include("./callbacks/trace.jl")
 include("./callbacks/sanitycheck.jl")
 
 # hyperparameter scheduling
@@ -88,12 +89,14 @@ export AbstractCallback,
     ProgressPrinter,
     Metrics,
     MetricsPrinter,
+    Traces,
     TrainingPhase,
     ValidationPhase,
     Schedule,
     Scheduler,
     LogMetrics,
     SmoothLoss,
+    LogTraces,
     LogHistograms,
     LogHyperParams,
     LogVisualization,
diff --git a/src/callbacks/logging/logger.jl b/src/callbacks/logging/logger.jl
index 3a5bab392..d5bcd2f85 100644
--- a/src/callbacks/logging/logger.jl
+++ b/src/callbacks/logging/logger.jl
@@ -33,6 +33,43 @@ function log_to(backends::Tuple, loggable, name, i; group = ())
     end
 end
 
+"""
+    LogTraces(backends...) <: Callback
+
+Callback that logs step traces to one or more [`LoggerBackend`](#)s.
+
+See also [`LoggerBackend`](#), [`Loggables.Loggable`](#), [`log_to`](#),
+[`TensorBoardBackend`](#)
+
+Example:
+
+```julia
+logcb = LogTraces(TensorBoardBackend("tblogs"))
+tracer = Traces((trace = learner -> learner.step.loss^2,), TrainingPhase)
+Learner(model, lossfn; callbacks=[tracer, logcb])
+```
+"""
+struct LogTraces <: Callback
+    backends::Tuple
+    LogTraces(backends...) = new(backends)
+end
+
+stateaccess(::LogTraces) = (cbstate = (history = Read(), tracehistory = Read()),)
+
+function on(::StepEnd, phase, logger::LogTraces, learner)
+    history = learner.cbstate.history[phase]
+    traces = learner.cbstate.tracehistory[phase]
+    for trace in keys(traces)
+        val = last(last(traces, trace))
+        log_to(
+            logger.backends,
+            Loggables.Value(val),
+            string(trace),
+            history.steps,
+            group = ("Step", string(typeof(phase)), "Traces"))
+    end
+end
+
 
 """
     LogMetrics(backends...) <: Callback
diff --git a/src/callbacks/trace.jl b/src/callbacks/trace.jl
new file mode 100644
index 000000000..464f70e65
--- /dev/null
+++ b/src/callbacks/trace.jl
@@ -0,0 +1,53 @@
+"""
+    Traces(preprocess[, phase])
+
+Record a trace during `phase` by apply each pre-processing function in
+`preprocess` to the [`Learner`](#) to produce a trace value.
+The trace is recorded at the end of each learning step.
+
+See [`LogTraces`](#) for logging of the trace values.
+```julia
+cb = Traces((loss2 = learner -> learner.step.loss^2,
+             avg_gnorm = learner -> mean(map((_, g) -> norm(g), pairs(learner.step.grads))))
+            TrainingPhase)
+```
+"""
+struct Traces{P<:Phase} <: Callback
+    preprocess::NamedTuple
+end
+
+function Traces(preprocess::NamedTuple, P::Type{<:Phase} = Phase)
+    return Traces{P}(preprocess)
+end
+
+stateaccess(::Traces) = (cbstate = (history = Read(), tracehistory = Write()),
+                         step = Read())
+
+function init!(traces::Traces, learner)
+    length(traces.preprocess) == length(unique(keys(traces.preprocess))) ||
+        error("Multiple traces have the same name!")
+    if !haskey(learner.cbstate, :tracehistory)
+        learner.cbstate.tracehistory = DefaultDict{Phase,MVHistory}(() -> MVHistory())
+    end
+end
+
+function on(::StepEnd, phase::P, traces::Traces{P}, learner) where {P<:Phase}
+    step = learner.cbstate.history[phase].steps
+    history = learner.cbstate.tracehistory[phase]
+    for (trace_name, f) in pairs(traces.preprocess)
+        val = f(learner)
+        push!(history, trace_name, step, val)
+    end
+end
+
+@testset "Traces" begin
+    cb = Traces((keya = learner -> sum(learner.step.ys),
+                 keyb = learner -> sum(learner.step.ŷs)),
+                ValidationPhase)
+    learner = testlearner(Recorder(), cb)
+    @test_nowarn fit!(learner, 1)
+    @test :keya ∈ keys(learner.cbstate.tracehistory[ValidationPhase()])
+    @test :keyb ∈ keys(learner.cbstate.tracehistory[ValidationPhase()])
+    @test :keya ∉ keys(learner.cbstate.tracehistory[TrainingPhase()])
+    @test :keyb ∉ keys(learner.cbstate.tracehistory[TrainingPhase()])
+end