def plot_function_execution_time(data, plot_dir):
cgroups = create_requestgroups(data)
fn_calls = group_by(cgroups, lambda c: c.function)
function_durations = {}
for function, calls in fn_calls.items():
if function not in ("artillery", None):
function_durations[function] = [
c.start_time for c in calls if c.start_time is not None
]
fig = plot_kdeplot(function_durations,
ylabel="Invocation Count",
title="KDE of function invocations",
log_scaling=True)
plot_path = str(plot_dir / "function_invocations.png")
print(f"Plotting to {plot_path}")
fig.savefig(plot_path)
def plot_function_coldstarts(data, plot_dir):
cld_groups = [d for d in data if isinstance(d, ColdstartLog)]
fn_calls = group_by(cld_groups, lambda c: c.function)
function_coldstarts = {}
for function, calls in fn_calls.items():
function_coldstarts[function] = [
c.timestamp for c in calls if c.timestamp is not None
]
fig = plot_kdeplot(function_coldstarts,
ylabel="Coldstart Count",
title="KDE of function coldstarts",
log_scaling=True)
plot_path = str(plot_dir / "function_coldstarts.png")
print(f"Plotting to {plot_path}")
fig.savefig(plot_path)
def plot_function_execution_time(data, plot_dir):
cgroups = create_requestgroups(data)
fn_calls = group_by(cgroups, lambda c: c.function)
function_durations = {}
for function, calls in fn_calls.items():
if function not in ("artillery", None):
function_durations[function] = [
timedelta_to_ms(c.duration) for c in calls
if c.duration is not None
]
fig = plot_boxplot(
function_durations,
ylabel="Execution Time (ms)",
title="Comparison of total execution time in current deployment.",
log_scaling=True)
plot_path = str(plot_dir / "boxplot_function_execution_time.png")
print(f"Plotting to {plot_path}")
fig.savefig(plot_path)
def apply_agraph_style(A, graph, filters, style):
cluster_style = style["cluster_style"]
node_vals = nx.get_node_attributes(graph, "platform")
val_nodes = defaultdict(list)
for node, value in node_vals.items():
if value not in ("artillery", "__caller__"):
val_nodes[value].append(node)
# create subgraphs
for value, nodes in val_nodes.items():
# skip empty providers
if not nodes:
continue
subgraph_name = f"cluster_{value}"
platgroup = A.add_subgraph(nodes,
name=subgraph_name,
label=value,
**cluster_style)
# set border color for included nodes
for node in nodes:
A.get_node(node).attr["color"] = cluster_style.get("fillcolor", "")
# create nested subgraph on function if call graph
if filters["context_id"]:
for name, fnodes in group_by(
nodes, lambda e: get_node_function(graph, e)).items():
platgroup.add_subgraph(fnodes,
name=f"cluster_{name}",
label=name,
**cluster_style)
A.layout(style["layout"])
return A