Dashboards (Grafana) in Microservices - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to specify the data source type in a Grafana dashboard JSON.

Microservices

{
  "datasources": [
    {
      "name": "MyDataSource",
      "type": "[1]"
    }
  ]
}

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

Amysql

Bprometheus

Cmongodb

Dredis

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing a database type like mysql or mongodb instead of a metrics data source.

The correct data source type for monitoring microservices metrics in Grafana is prometheus.

2fill in blank

medium

Complete the code to set the panel type to display a time series graph in Grafana.

Microservices

{
  "panels": [
    {
      "type": "[1]",
      "title": "Service Latency"
    }
  ]
}

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

Astat

Btable

Ctext

Dgraph

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'table' or 'text' which do not show time series graphs.

The graph panel type is used to show time series data like latency over time.

3fill in blank

hard

Fix the error in the query expression to select the average response time metric.

Microservices

{
  "targets": [
    {
      "expr": "avg([1])"
    }
  ]
}

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

Aavg_response_time

BresponseTime

Cresponse_time_seconds

Dlatency_ms

Attempts:

3 left

💡 Hint

Common Mistakes

Using camelCase or incorrect metric names that Prometheus does not recognize.

The Prometheus metric for response time is usually named response_time_seconds in seconds.

4fill in blank

hard

Fill both blanks to create a dashboard variable that filters by service name using a regex.

Microservices

{
  "templating": {
    "list": [
      {
        "name": "service",
        "query": "label_values([1], service)",
        "regex": "/[2]/"
      }
    ]
  }
}

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

Aup

Bhttp_requests_total

C^auth.*

D.*prod$

Attempts:

3 left

💡 Hint

Common Mistakes

Using an incorrect metric name or wrong regex pattern.

The variable queries the http_requests_total metric and filters services starting with auth.

5fill in blank

hard

Fill all three blanks to define a panel that shows the 95th percentile latency for a service.

Microservices

{
  "panels": [
    {
      "title": "95th Percentile Latency",
      "type": "graph",
      "targets": [
        {
          "expr": "histogram_quantile([1], sum(rate([2][5m])) by (le, [3]))"
        }
      ]
    }
  ]
}

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

A0.95

Brequest_latency_seconds_bucket

Cservice

Dinstance

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong quantile values or incorrect metric names.

Grouping by instance instead of service.

The histogram_quantile(0.95, ...) function calculates the 95th percentile latency using the request_latency_seconds_bucket metric grouped by service.