Very simple to use. Good UI. it has all the requirements needed for cloud platform. It is very helpful for administrator to work on MS Azure web. Never confuse the user to access it. Review collected by and hosted on G2.com.

Microsoft Azure web need good hands-on to master the use of this platform. Administrative knowledge is required to work on this platform smoothly. There should be a easy user guide to use its resources. Review collected by and hosted on G2.com.

Azure App services are less cost and are highly secured. We can easily deploy applications from IDE's like vs code. Deployment slots are also best feature for App Services. Review collected by and hosted on G2.com.

When we deploy an app, in order to trouble shoot application problems we have to check on server for logfiles. Remote Desktop is not available. Review collected by and hosted on G2.com.

Easy to use and flexibility in integrating with other scripts like python, Powershell and shell script. It can be easily interfaced with ETL tools like Informatica and Talend Review collected by and hosted on G2.com.

Nothing as such except one thing that user authentication and management is not as simple as GCP and AWS Review collected by and hosted on G2.com.

A PaaS based solution that equips the user to build, deploy, and scale web apps and APIs with minimal efforts on the infrastructure and maintenance of the same. Review collected by and hosted on G2.com.

Limited support for the 3rd party applications and tools. Review collected by and hosted on G2.com.

The ability to create functional apps within minutes. Review collected by and hosted on G2.com.

So far, I haven't encountered any issues or challenges Review collected by and hosted on G2.com.

The upsides of Azure include the following:

Scalability and flexibility: It allows for easy scaling of resources, making it easy to handle large amounts of data and high-volume workloads.

Pre-built models and templates: Azure ML offers a variety of pre-built models and templates, making it easy for users to get started with machine learning without extensive knowledge in the field.

Collaboration and sharing: Azure ML allows multiple users to collaborate and share models, experiments and data.

Model management and deployment: Azure ML provides tools and services that enable you to manage and deploy your machine learning models with ease. Review collected by and hosted on G2.com.

There are a few downsides to Microsoft Azure:

Limited customization options as compared to other cloud providers.

Pricing can be complex and hard to understand, making it difficult to predict costs. Review collected by and hosted on G2.com.

Yeah it's very useful lots of services we can utilise at single place like deployment, hosting and api development. Review collected by and hosted on G2.com.

Little hard to find resources related to some service. Experienced dev can easily integrate Review collected by and hosted on G2.com.

Security

Load balancing

Auto scaling

Application service plan tiering Review collected by and hosted on G2.com.

Nothing as such. It covers most of the need for building an enterprise grade app Review collected by and hosted on G2.com.

The feature off automatic auto scaling and high availability is the best.The low cost is also a factor and mostly I like the IDe E integration with azure SdK. Review collected by and hosted on G2.com.

It should allow us access to install dynatrace and other third party software.In our case we left with using stackify.Remote desktop not avl and we hv to use kudo console to see logs Review collected by and hosted on G2.com.

Azure app service is container based service.in that we used docker image deployment. Review collected by and hosted on G2.com.

In the service we can't create any vm.it is completely running through container. Review collected by and hosted on G2.com.