def generate_latency_plot()

in right_size_your_sagemaker_endpoints/load_test_helper.py [0:0]

• 18 lines of code
• 4 McCabe index (conditional complexity)

def generate_latency_plot(endpoints, results_folder):
    """
    Generate latency plots for a given list of endpoints
    
    Given a list of endpoints, this function plots the minimum, 
    maximum and average latency in a box plot.
    
    Inputs:
    endpoints: list of endpoint names
    results_folder: path where load test results are saved
    
    Output:
    Boxplot of latencies per instance type
    """
    latency_dict= {}

    # for each endpoint get latency from the load test results
    for ep in endpoints:
        prefix = f"test_{ep}"
        df = pd.read_csv(f"{results_folder}/{prefix}/{prefix}_stats.csv")

        min_latency = round(df.tail(1)['Min Response Time'].values[0] / 1000, 1)
        avg_latency = round(df.tail(1)['Average Response Time'].values[0] / 1000, 1)
        max_latency = round(df.tail(1)['Max Response Time'].values[0] / 1000, 1)

        latency_dict.update({
            ep.split("-", 1)[1].replace("-", "."): [min_latency,
                                                    avg_latency,
                                                    max_latency]
        })

    # generate a data frame of the results and plot a box plot
    results = pd.DataFrame(latency_dict)
    res_plot = results.plot(legend=True, figsize=(12, 7), kind='box',
                title="Request Latency Across Instance Types",
                xlabel="Instance Type",
                ylabel="Latency in Seconds")