diff --git a/utils/plot-startup.py b/utils/plot-startup.py
new file mode 100644
index 0000000..241116d
--- /dev/null
+++ b/utils/plot-startup.py
@@ -0,0 +1,31 @@
+import matplotlib.pyplot as plt
+import seaborn as sns
+import random
+import pandas as pd
+
+# Genera i dati mock
+data = [{"tempo di esecuzione": round(random.gauss(23, 1), 3)} for _ in range(9)]
+df = pd.DataFrame(data)
+
+# Creazione del boxplot con grafico più largo e barra più stretta
+plt.figure(figsize=(10, 6))  # Grafico più largo
+ax = sns.boxplot(y=df["tempo di esecuzione"], width=0.3, flierprops={"marker": "o", "color": "red", "markersize": 8}, color="lightgreen")
+
+# Calcolo della media
+mean_value = df["tempo di esecuzione"].mean()
+
+# Aggiungi il testo della media alla base
+plt.text(0, 0, f'Media: {mean_value:.2f}', ha='center', va='bottom', fontsize=14, fontweight='bold', color="black")
+
+# Imposta i label con font più grande
+plt.ylabel("Downtime (s)", fontsize=14)
+plt.xticks([])  # Rimuove i tick sull'asse X
+plt.yticks(fontsize=12)
+
+# Mostra griglia leggera
+plt.grid(axis='y', linestyle='--', alpha=0.6)
+
+# Salva il plot
+plt.tight_layout()
+plt.savefig("benchmark/boxplot_failover.png")
+plt.show()
diff --git a/plot_compared_metrics.py b/utils/plot_compared_metrics.py
similarity index 79%
rename from plot_compared_metrics.py
rename to utils/plot_compared_metrics.py
index c586af3..092dc89 100644
--- a/plot_compared_metrics.py
+++ b/utils/plot_compared_metrics.py
@@ -28,12 +28,12 @@ def read_metrics(file_path, label):
     return extracted_data
 
 # Paths for the two metric files
-file_path_1 = 'project/metrics.yaml'  # First metrics file
-file_path_2 = 'auga/metrics.yaml'  # Second metrics file
+file_path_1 = 'res/metrics/metrics-parallel-nats.yaml'  # First metrics file
+file_path_2 = 'res/metrics/metrics-sequential.yaml'  # Second metrics file
 
 # Read and combine the data
-data1 = read_metrics(file_path_1, 'Parallel')
-data2 = read_metrics(file_path_2, 'Sequential')
+data1 = read_metrics(file_path_1, 'Esecuzione Parallelizzata')
+data2 = read_metrics(file_path_2, 'Esecuzione Sequenziale')
 
 df = pd.DataFrame(data1 + data2)
 
@@ -71,15 +71,21 @@ def plot_lineplot(metric, filename):
 def plot_barplot(metric, filename):
     subset = df[df['Type'] == metric]
     plt.figure(figsize=(10, 6))
-    sns.barplot(x='Task', y='Time', hue='Source', data=subset, errorbar=('ci', 95))
+    
+    sns.barplot(x='Task', y='Time', hue='Source', data=subset, errorbar=('ci', 95), palette=['salmon', 'skyblue'])
+
+    plt.xlabel('Task', fontsize=14)  # Aumenta la dimensione del font dell'asse X
+    plt.ylabel('Time (seconds)', fontsize=14)  # Aumenta la dimensione del font dell'asse Y
+    plt.xticks(fontsize=12)  # Modifica la dimensione del font dei tick dell'asse X
+    plt.yticks(fontsize=12)  # Modifica la dimensione del font dei tick dell'asse Y
+    plt.legend(title='Source', title_fontsize=14, fontsize=12)  # Modifica il font della legenda
 
-    plt.ylabel('Time (seconds)')
     plt.grid(True, linestyle='--', alpha=0.7)
-    plt.legend(title='Source')
     plt.tight_layout()
     plt.savefig(f'benchmark/{filename}')
     plt.close()
 
+
 # Generate plots for each metric
 metrics = ['Build Time', 'Generation Time', 'Deployment Time', 'Total Time']
 filenames = ['build_time', 'gen_time', 'deploy_time', 'total_time']
diff --git a/plot_metrics.py b/utils/plot_metrics.py
similarity index 100%
rename from plot_metrics.py
rename to utils/plot_metrics.py