Estimating consumption-based costs
This article shows you how to estimate plan costs for the Consumption and Flex Consumption hosting plans.
Azure Functions currently offers four different hosting plans for your function apps, with each plan having its own pricing model:
| Plan | Description |
|---|---|
| Consumption | You're only charged for the time that your function app runs. This plan includes a free grant on a per subscription basis. |
| Flex Consumption plan | You pay for execution time on the instances on which your functions are running, plus any always ready instances. Instances are dynamically added and removed based on the number of incoming events. Also supports virtual network integration. |
| Premium | Provides you with the same features and scaling mechanism as the Consumption plan, but with enhanced performance and virtual network integration. Cost is based on your chosen pricing tier. To learn more, see Azure Functions Premium plan. |
| Dedicated (App Service) (basic tier or higher) |
When you need to run in dedicated VMs or in isolation, use custom images, or want to use your excess App Service plan capacity. Uses regular App Service plan billing. Cost is based on your chosen pricing tier. |
Important
The Flex Consumption plan is currently in preview.
You should always choose the plan that best supports the feature, performance, and cost requirements for your function executions. To learn more, see Azure Functions scale and hosting.
This article focuses on Consumption and Flex Consumption plans because in these plans billing depends on active periods of executions inside each instance.
Durable Functions can also run in both of these plans. To learn more about the cost considerations when using Durable Functions, see Durable Functions billing.
Consumption-based costs
The way that consumption-based costs are calculated, including free grants, depends on the specific plan. For the most current cost and grant information, see the Azure Functions pricing page.
The execution cost of a single function execution is measured in GB-seconds. Execution cost is calculated by combining its memory usage with its execution time. A function that runs for longer costs more, as does a function that consumes more memory.
Consider a case where the amount of memory used by the function stays constant. In this case, calculating the cost is simple multiplication. For example, say that your function consumed 0.5 GB for 3 seconds. Then the execution cost is 0.5GB * 3s = 1.5 GB-seconds.
Since memory usage changes over time, the calculation is essentially the integral of memory usage over time. The system does this calculation by sampling the memory usage of the process (along with child processes) at regular intervals. As mentioned on the pricing page, memory usage is rounded up to the nearest 128-MB bucket. When your process is using 160 MB, you're charged for 256 MB. The calculation takes into account concurrency, which is multiple concurrent function executions in the same process.
Note
While CPU usage isn't directly considered in execution cost, it can have an impact on the cost when it affects the execution time of the function.
For an HTTP-triggered function, when an error occurs before your function code begins to execute you aren't charged for an execution. This means that 401 responses from the platform due to API key validation or the App Service Authentication / Authorization feature don't count against your execution cost. Similarly, 5xx status code responses aren't counted when they occur in the platform before your function processes the request. A 5xx response generated by the platform after your function code has started to execute is still counted as an execution, even when the error isn't raised from your function code.
Other related costs
When estimating the overall cost of running your functions in any plan, remember that the Functions runtime uses several other Azure services, which are each billed separately. When you estimate pricing for function apps, any triggers and bindings you have that integrate with other Azure services require you to create and pay for those other services.
For functions running in a Consumption plan, the total cost is the execution cost of your functions, plus the cost of bandwidth and other services.
When estimating the overall costs of your function app and related services, use the Azure pricing calculator.
| Related cost | Description |
|---|---|
| Storage account | Each function app requires that you have an associated General Purpose Azure Storage account, which is billed separately. This account is used internally by the Functions runtime, but you can also use it for Storage triggers and bindings. If you don't have a storage account, one is created for you when the function app is created. To learn more, see Storage account requirements. |
| Application Insights | Functions relies on Application Insights to provide a high-performance monitoring experience for your function apps. While not required, you should enable Application Insights integration. A free grant of telemetry data is included every month. To learn more, see the Azure Monitor pricing page. |
| Network bandwidth | You can incur costs for data transfer depending on the direction and scenario of the data movement. To learn more, see Bandwidth pricing details. |
Behaviors affecting execution time
The following behaviors of your functions can affect the execution time:
Triggers and bindings: The time taken to read input from and write output to your function bindings is counted as execution time. For example, when your function uses an output binding to write a message to an Azure storage queue, your execution time includes the time taken to write the message to the queue, which is included in the calculation of the function cost.
Asynchronous execution: The time that your function waits for the results of an async request (
awaitin C#) is counted as execution time. The GB-second calculation is based on the start and end time of the function and the memory usage over that period. What is happening over that time in terms of CPU activity isn't factored into the calculation. You may be able to reduce costs during asynchronous operations by using Durable Functions. You're not billed for time spent at awaits in orchestrator functions.
Viewing cost-related data
In your invoice, you can view the cost-related data of Total Executions - Functions and Execution Time - Functions, along with the actual billed costs. However, this invoice data is a monthly aggregate for a past invoice period.
Function app-level metrics
To better understand the cost impact of your functions, you can use Azure Monitor to view cost-related metrics currently being generated by your function apps.
Use Azure Monitor metrics explorer to view cost-related data for your Consumption plan function apps in a graphical format.
In the Azure portal, navigate to your function app.
In the left panel, scroll down to Monitoring and choose Metrics.
From Metric, choose Function Execution Count and Sum for Aggregation. This adds the sum of the execution counts during chosen period to the chart.
Select Add metric and repeat steps 2-4 to add Function Execution Units to the chart.
The resulting chart contains the totals for both execution metrics in the chosen time range, which in this case is two hours.
As the number of execution units is so much greater than the execution count, the chart just shows execution units.
This chart shows a total of 1.11 billion Function Execution Units consumed in a two-hour period, measured in MB-milliseconds. To convert to GB-seconds, divide by 1024000. In this example, the function app consumed 1110000000 / 1024000 = 1083.98 GB-seconds. You can take this value and multiply by the current price of execution time on the Functions pricing page, which gives you the cost of these two hours, assuming you've already used any free grants of execution time.
Function-level metrics
Function execution units are a combination of execution time and your memory usage, which makes it a difficult metric for understanding memory usage. Memory data isn't a metric currently available through Azure Monitor. However, if you want to optimize the memory usage of your app, can use the performance counter data collected by Application Insights.
If you haven't already done so, enable Application Insights in your function app. With this integration enabled, you can query this telemetry data in the portal.
You can use either Azure Monitor metrics explorer in the Azure portal or REST APIs to get Monitor Metrics data.
Determine memory usage
Under Monitoring, select Logs (Analytics), then copy the following telemetry query and paste it into the query window and select Run. This query returns the total memory usage at each sampled time.
performanceCounters
| where name == "Private Bytes"
| project timestamp, name, value
The results look like the following example:
| timestamp [UTC] | name | value |
|---|---|---|
| 9/12/2019, 1:05:14.947 AM | Private Bytes | 209,932,288 |
| 9/12/2019, 1:06:14.994 AM | Private Bytes | 212,189,184 |
| 9/12/2019, 1:06:30.010 AM | Private Bytes | 231,714,816 |
| 9/12/2019, 1:07:15.040 AM | Private Bytes | 210,591,744 |
| 9/12/2019, 1:12:16.285 AM | Private Bytes | 216,285,184 |
| 9/12/2019, 1:12:31.376 AM | Private Bytes | 235,806,720 |
Determine duration
Azure Monitor tracks metrics at the resource level, which for Functions is the function app. Application Insights integration emits metrics on a per-function basis. Here's an example analytics query to get the average duration of a function:
customMetrics
| where name contains "Duration"
| extend averageDuration = valueSum / valueCount
| summarize averageDurationMilliseconds=avg(averageDuration) by name
| name | averageDurationMilliseconds |
|---|---|
| QueueTrigger AvgDurationMs | 16.087 |
| QueueTrigger MaxDurationMs | 90.249 |
| QueueTrigger MinDurationMs | 8.522 |