Event-based scaling in Azure Functions (2023)

FAQs

How do I improve the performance of my Azure function app? ›

Scale out automatically, even during periods of high load. Azure Functions infrastructure scales CPU and memory resources by adding additional instances of the Functions host, based on the number of incoming trigger events. Event driven. Scale out automatically, even during periods of high load.

3. App Service Plan: With this plan, virtual machines are always running, so you never have to worry about cold starts. This is ideal for long-running operations, or when more predictive scaling and costs are required.

Maximum instances: A single function app only scales out to a maximum of 200 instances. A single instance may process more than one message or request at a time though, so there isn't a set limit on number of concurrent executions. You can specify a lower maximum to throttle scale as required.

Azure Functions are best suited for smaller apps have events that can work independently of other websites. Some of the common azure functions are sending emails, starting backup, order processing, task scheduling such as database cleanup, sending notifications, messages, and IoT data processing.

Vendor-lock is the biggest drawback of this function. It is very difficult to run code deployed in Azure function outside the azure environment. The language used in function app such as java, NodeJS, etc are not specialized but the code to establish a connection between resources is specific to azure.

Two main ways an application can scale include vertical scaling and horizontal scaling. Vertical scaling (scaling up) increases the capacity of a resource, for example, by using a larger virtual machine (VM) size. Horizontal scaling (scaling out) adds new instances of a resource, such as VMs or database replicas.

You scale up by changing the pricing tier of the App Service plan that your app belongs to. Scale out: Increase the number of VM instances that run your app. You can scale out to as many as 30 instances, depending on your pricing tier.

Billing for the Premium plan is based on the number of core seconds and memory allocated across instances. This billing differs from the Consumption plan, which is billed based on per-second resource consumption and executions. There's no execution charge with the Premium plan.

What is the difference between horizontal and vertical scaling in Azure? ›

Horizontal vs vertical scaling

Horizontal scaling is flexible in a cloud situation as it allows you to run a large number of VMs to handle load. In contrast, vertical scaling, keeps the same number of resources constant, but gives them more capacity in terms of memory, CPU speed, disk space and network.

Parallel execution

Each instance of the function app, whether the app runs on the Consumption hosting plan or a regular App Service hosting plan, might process concurrent function invocations in parallel using multiple threads.

If your logic app workflow experiences throttling, which happens when the number of requests exceed the rate at which the destination can handle over a specific amount of time, you get the "HTTP 429 Too many requests" error.

The HTTP 429 status code indicates that the user has sent too many requests in a given amount of time (“rate limiting”). So, for HttpTrigger based function, the host. json will look like this. 230 seconds is the maximum amount of time that an HTTP triggered function can take to respond to a request.

For most . NET developers, C# is the go-to language to solve all. And in most cases, that reflex is probably right. If you're already running C#-based applications on Azure, be it in Service Fabric, containers, or anything else, it's only logical to use the same language for your functions.

Function doesn't limit you and you dont have to allow only one method per function. It is completely feasible to process the different request in the code after entering function.

Azure Functions is a serverless compute service, whereas Azure Logic Apps is a serverless workflow integration platform. Both can create complex orchestrations. An orchestration is a collection of functions, or actions in Azure Logic Apps, that you can run to complete a complex task.

We have two basic ways to achieve scalability, namely increasing system capacity, typically through replication, and performance optimization of system components.

The best solution to most database scalability issues is optimizing SQL queries and implementing indexing strategies. By building articles and authors into a single query, you can dramatically reduce the volume of queries you're running.

Does improving scalability improve performance? ›

Scalability is the ability to handle larger amounts of work when the system is under heavy load by throwing more resources at the problem. This generally means improving performance by buying faster servers or adding more servers.

With Durable Functions you can easily support long-running processes, applying the Async HTTP APIs or Monitoring Patterns. In case you are dealing with functions that require some time to process the payload or request consider running under an App Service Plan, WebJob, or Durable Functions.

Azure Functions is a serverless solution that allows you to write less code, maintain less infrastructure, and save on costs. Instead of worrying about deploying and maintaining servers, the cloud infrastructure provides all the up-to-date resources needed to keep your applications running.

The most common techniques of feature scaling are Normalization and Standardization. Normalization is used when we want to bound our values between two numbers, typically, between [0,1] or [-1,1]. While Standardization transforms the data to have zero mean and a variance of 1, they make our data unitless.

As mentioned, there are two main types of scaling namely; Rating Scales and Attitude Scales. Researcher need to select one scaling method before development of the survey/ questionnaire.

There are two basic types of scalability in cloud computing: vertical and horizontal scaling. With vertical scaling, also known as “scaling up” or “scaling down,” you add or subtract power to an existing cloud server upgrading memory (RAM), storage or processing power (CPU).

To decide between scale-up vs. scale-out for storage, consider factors such as data growth expectations, budget, criticality of systems and existing hardware. Generally, organizations will scale up when they face performance issues and need a short-term fix; they will scale out when flexibility is important.

You have options when you need to scale your applications, but each comes with benefits and drawbacks. Scaling up vertically means adding more compute resources—such as CPU, memory, and disk capacity—to an application pod. On the other hand, applications can scale out horizontally by adding more replica pods.

Microsoft Azure auto-scaling has some definite benefits -

Azure auto-scaling feature scales out the instances impeccably whenever demand increases. You can save money by flaking unnecessary instances automatically. Auto-scaling feature allows you to set alerts and notifications based upon your scaling criteria.

What are the 3 pricing models of Azure? ›

Azure Pricing Models

Microsoft offers three main ways to pay for Azure VMs and other cloud resources: pay as you go, reserved instances, and spot instances.

Buy an Azure savings plan to save money on a variety of compute services. Buy reserved virtual machine instances to save money over pay-as-you-go costs. Optimize virtual machine spend by resizing or shutting down underutilized instances. Use Standard Storage to store Managed Disks snapshots.

json. In a recent update, the Azure Functions team at Microsoft has added a configuration option that enables an Azure Functions App to have the timeout increased. To implement this, the functionTimeout property within the host. json file for an Azure Function App can be set to a timespan duration of 10 minutes.

With vertical scaling (“scaling up”), you're adding more compute power to your existing instances/nodes. In horizontal scaling (“scaling out”), you get the additional capacity in a system by adding more instances to your environment, sharing the processing and memory workload across multiple devices.

Disadvantages of Vertical Scaling:

The hardware costs more because of high-end servers. There is a limit to the amount you can upgrade. You are restricted to a single database vendor, and migration is challenging, or you may need to start over.

Vertical scaling will cost less when the servers are still small. As the servers grow bigger, vertical scaling costs will grow exponentially. At that point, horizontal scaling becomes a cheaper alternative.

As part of your solution, you likely develop and publish multiple functions. These functions are often combined into a single function app, but they can also run in separate function apps.

It's possible for multiple function apps to share the same storage account without any issues. For example, in Visual Studio you can develop multiple apps using the Azure Storage Emulator. In this case, the emulator acts like a single storage account.

Bindings are optional and a function might have one or multiple input and/or output bindings. Triggers and bindings let you avoid hardcoding access to other services. Your function receives data (for example, the content of a queue message) in function parameters.

Average 200-300 connections per second.

How do you handle millions of API requests? ›

To handle 'millions of request' the system must be deployed on multiple web servers behind a load-balancer that would round robin between each. if the system is hitting a datastore, a second level cache(ehcache, memcache,etc.) should be used to reduce load on the datastore.

The simplest way to fix an HTTP 429 error is to wait to send another request. Often, this status code is sent with a “Retry-after” header that specifies a period of time to wait before sending another request. It may specify only a few seconds or minutes.

You should strive to keep the number of HTTP requests under 50. If you can get requests below 25, you're doing amazing. By their nature, HTTP requests are not bad. Your site needs them to function and look good.

There are 4 basic methods, which are also referred to as CRUD operations: POST: Create a resource. GET: Read information from a resource.

This problem is often caused by application level issues, such as: network requests taking a long time. application code or database queries being inefficient. application using high memory/CPU.

Azure Functions can be monitored using Application Insights and Azure Monitor. Though Azure provides such monitoring solutions, users cannot monitor multiple entities with various metrics. Whereas, with Serverless360 monitoring, it is possible to monitor various entities based on metrics at the Application level.

Use the following procedure to view and update the runtime version currently used by a function app. In the Azure portal, browse to your function app. Under Settings, choose Configuration. In the Function runtime settings tab, locate the Runtime version.

In a recent update, the Azure Functions team at Microsoft has added a configuration option that enables an Azure Functions App to have the timeout increased. To implement this, the functionTimeout property within the host. json file for an Azure Function App can be set to a timespan duration of 10 minutes.

Is Azure going away? ›

We're retiring Azure VMs (classic) on September 1, 2023 - Azure Virtual Machines | Microsoft Learn. This browser is no longer supported. Upgrade to Microsoft Edge to take advantage of the latest features, security updates, and technical support.

Network latency: AWS wins again.

Its top-performing machine's 99th percentile network latency was 28% and 37% lower than Azure and GCP, respectively.

You can also monitor the function app itself by using Azure Monitor. To learn more, see Monitoring Azure Functions with Azure Monitor.

Sign in to Azure portal. In the search bar at the topic, type Event Grid Topics, and then select Event Grid Topics from the drop-down list. Select your custom topic from the list of topics. View the metrics for the custom event topic on the Event Grid Topic page.

Function execution count indicates the number of times your function app has executed. This value correlates to the number of times a function runs in your app. FunctionExecutionUnits. Function execution units are a combination of execution time and your memory usage.

Functions in a Consumption plan are limited to 10 minutes for a single execution. In the Premium plan, the run duration defaults to 30 minutes to prevent runaway executions. However, you can modify the host.