Function scaling behavior in Azure - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to specify the trigger type for an Azure Function.

Azure

public static void Run([[1]Trigger] string myQueueItem, ILogger log) {
    log.LogInformation($"Processing: {myQueueItem}");
}

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AHttp

BBlob

CTimer

DQueue

Attempts:

3 left

💡 Hint

Common Mistakes

Using HttpTrigger when the function is triggered by a queue message.

Using BlobTrigger which is for blob storage events.

The Azure Function is triggered by a message in a queue, so the correct trigger attribute is QueueTrigger.

2fill in blank

medium

Complete the code to set the maximum number of function instances in host.json.

Azure

{
  "version": "2.0",
  "functionTimeout": "00:05:00",
  "concurrency": {
    "dynamicConcurrencyEnabled": true,
    "[1]": 5
  }
}

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AmaxFunctionInstances

BmaxDegreeOfParallelism

CmaxInstances

DmaxConcurrentRequests

Attempts:

3 left

💡 Hint

Common Mistakes

Using maxDegreeOfParallelism which controls threads, not instances.

Using maxConcurrentRequests which is unrelated to scaling instances.

The maxInstances setting controls the maximum number of function instances that can run concurrently.

3fill in blank

hard

Fix the error in the Azure Function scale controller setting.

Azure

{
  "version": "2.0",
  "extensions": {
    "queues": {
      "batchSize": 16,
      "maxDequeueCount": [1]
    }
  }
}

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A5

B"5"

C-1

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using a string value instead of an integer.

Setting maxDequeueCount to zero or negative numbers.

The maxDequeueCount must be a positive integer. Using 5 is correct. Strings or negative numbers cause errors.

4fill in blank

hard

Fill both blanks to configure the function app to scale based on CPU and memory thresholds.

Azure

{
  "scaling": {
    "rules": [
      {
        "metricTrigger": {
          "metricName": "[1]",
          "threshold": 70
        },
        "scaleAction": {
          "direction": "Increase",
          "type": "ChangeCount",
          "value": "1"
        }
      },
      {
        "metricTrigger": {
          "metricName": "[2]",
          "threshold": 80
        },
        "scaleAction": {
          "direction": "Increase",
          "type": "ChangeCount",
          "value": "1"
        }
      }
    ]
  }
}

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ACpuPercentage

BMemoryPercentage

CDiskQueueLength

DHttpQueueLength

Attempts:

3 left

💡 Hint

Common Mistakes

Using disk or HTTP queue metrics which are unrelated to CPU/memory scaling.

Mixing up the metric names.

The function app scales when CPU usage exceeds 70% and memory usage exceeds 80%, so the metric names are CpuPercentage and MemoryPercentage.

5fill in blank

hard

Fill all three blanks to define a scale rule that decreases instances when the queue length is low.

Azure

{
  "rules": [
    {
      "metricTrigger": {
        "metricName": "[1]",
        "threshold": [2],
        "timeAggregation": "Average"
      },
      "scaleAction": {
        "direction": "[3]",
        "type": "ChangeCount",
        "value": "1",
        "cooldown": "PT5M"
      }
    }
  ]
}

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AQueueLength

B10

CDecrease

DIncrease

Attempts:

3 left

💡 Hint

Common Mistakes

Using Increase instead of Decrease for scaling down.

Using a threshold that is too high or unrelated metric names.

The scale rule triggers when the QueueLength metric average is below 10, causing the function app to Decrease instances.