Metrics and dashboards in GCP - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a metric descriptor for a custom metric in Google Cloud Monitoring.

GCP

metric_descriptor = monitoring_v3.MetricDescriptor()
metric_descriptor.type = "custom.googleapis.com/[1]"
metric_descriptor.metric_kind = monitoring_v3.MetricDescriptor.MetricKind.GAUGE
metric_descriptor.value_type = monitoring_v3.MetricDescriptor.ValueType.DOUBLE

Drag options to blanks, or click blank then click option'

Amemory_usage

Bnetwork_latency

Cdisk_io

Dcpu_usage

Attempts:

3 left

💡 Hint

Common Mistakes

Using a metric name without the 'custom.googleapis.com/' prefix.

Choosing a metric name that is not descriptive.

The metric type must be a valid custom metric name. Here, "memory_usage" is used as an example custom metric.

2fill in blank

medium

Complete the code to create a dashboard widget that shows a line chart of CPU utilization.

GCP

widget = {
  "xyChart": {
    "dataSets": [{
      "timeSeriesQuery": {
        "timeSeriesFilter": {
          "filter": "metric.type = \"compute.googleapis.com/instance/cpu/utilization\"",
          "aggregation": {
            "perSeriesAligner": monitoring_v3.Aggregation.Aligner.[1]
          }
        }
      }
    }]
  }
}

Drag options to blanks, or click blank then click option'

AALIGN_MAX

BALIGN_MEAN

CALIGN_MIN

DALIGN_SUM

Attempts:

3 left

💡 Hint

Common Mistakes

Using ALIGN_SUM which sums values and may not represent average usage.

Using ALIGN_MAX or ALIGN_MIN which show extremes, not average.

ALIGN_MEAN calculates the average CPU utilization over the alignment period, which is common for line charts.

3fill in blank

hard

Fix the error in the alerting policy condition filter to monitor high memory usage.

GCP

condition = {
  "conditionThreshold": {
    "filter": "metric.type = \"compute.googleapis.com/instance/memory/usage_bytes\" AND resource.type = [1]",
    "comparison": monitoring_v3.ComparisonType.COMPARISON_GT,
    "thresholdValue": 8000000000,
    "duration": "300s"
  }
}

Drag options to blanks, or click blank then click option'

A"compute_instance"

B"gce-vm"

C"gce_instance"

D"vm_instance"

Attempts:

3 left

💡 Hint

Common Mistakes

Using incorrect resource type strings that cause the filter to fail.

Omitting quotes around the resource type.

The correct resource type for Google Compute Engine VM instances is "gce_instance".

4fill in blank

hard

Fill both blanks to create a dashboard widget that displays a stacked bar chart of network traffic by direction.

GCP

widget = {
  "xyChart": {
    "chartOptions": {
      "mode": monitoring_v3.XyChart.ChartOptions.Mode.[1],
      "chartType": monitoring_v3.XyChart.ChartType.[2]
    },
    "dataSets": [{
      "timeSeriesQuery": {
        "timeSeriesFilter": {
          "filter": "metric.type = \"compute.googleapis.com/instance/network/received_bytes_count\" OR metric.type = \"compute.googleapis.com/instance/network/sent_bytes_count\"",
          "aggregation": {
            "perSeriesAligner": monitoring_v3.Aggregation.Aligner.ALIGN_SUM
          }
        }
      }
    }]
  }
}

Drag options to blanks, or click blank then click option'

ASTACKED

BGROUPED

CLINE

DBAR

Attempts:

3 left

💡 Hint

Common Mistakes

Using LINE mode or chart type which shows lines, not bars.

Using GROUPED mode which shows bars side by side, not stacked.

To show a stacked bar chart, set mode to STACKED and chart type to BAR.

5fill in blank

hard

Fill all three blanks to define an alerting policy that triggers when average CPU utilization exceeds 70% for 5 minutes.

GCP

alert_policy = {
  "conditions": [{
    "conditionThreshold": {
      "filter": "metric.type = \"compute.googleapis.com/instance/cpu/utilization\" AND resource.type = \"[1]\"",
      "comparison": monitoring_v3.ComparisonType.[2],
      "thresholdValue": [3],
      "duration": "300s"
    }
  }]
}

Drag options to blanks, or click blank then click option'

Agce_instance

BCOMPARISON_GT

C0.7

DCOMPARISON_LT

Attempts:

3 left

💡 Hint

Common Mistakes

Using COMPARISON_LT which triggers below threshold.

Using incorrect resource type strings.

Setting threshold value as 70 instead of 0.7.

The resource type is "gce_instance". The comparison is greater than (COMPARISON_GT). The threshold value is 0.7 (70%).