Microsoft Azure- Great as PaaS, baby as IaaS
April 30, 2021

Microsoft Azure- Great as PaaS, baby as IaaS

Apurv Doshi | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User

Overall Satisfaction with Microsoft Azure

We use Microsoft Azure for cognitive services like natural language processing, computer vision, and machine learning services for built-in open-[source] frameworks like Tensorflow, MXNet, Keras, etc. It is used based on customers' needs, as we are in the service industry. It helps with scaling, security, and reliability.
  • Azure simply provides end to end life cycle. Starting from the development to automated deployment, you will find [a] bunch of options. Custom hook-points allow [integration] on-premise resources as well.
  • Excellent documentation around all the services make it really easy for any novice. Overall support by [the] community and Azure Technical team is exceptional.
  • BOT Services, Computer Vision services, ML frameworks provide excellent results as compare to similar services provided by other giants in the same space.
  • Azure data services provide excellent support to ingest data from different sources, ETL, and consumption of data for BI purpose.
  • The reliability of hardware is low as [compared] to AWS. Sometimes processes of allocation, deallocation of resources take quite a long time without having any intimation. If the instances are costly, such delay in stopping incurs extra cost.
  • Overall cost is much higher for ML and BI Services. Basic storage and compute cost is also bit more as compare to AWS.
  • Azure can surely do better with overall DevOps support. Cloud formation needs [a] lot more maturity and features.
  • Azure is truly PaaS. It provides the platform with the best possible configuration around many services. However many services require improvement.
  • Automation templates are not much flexible. So for [doable] assets (which you want to up at the time of demo), you need to do [a] lot of work in prior. Sometimes it creates [a] negative impact on ROI.
  • We find it extremely useful and agile when you want to do quick prototyping or development on [the] scale for cognitive services. Truly worth of investment.

Do you think Microsoft Azure delivers good value for the price?


Are you happy with Microsoft Azure's feature set?


Did Microsoft Azure live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Microsoft Azure go as expected?


Would you buy Microsoft Azure again?


The answer depends upon the kind of [use case]. If the use-case is simply around the need of IaaS then Azure is not the right choice. However, if the use-cases are around BOT services, Natural Language Processing, Computer Vision, Machine Learning[,] and Business Analytics then Azure is the first choice. Also[,] kind of eco-system the enterprise [has] on the premise to run their daily operations have the highest bearing to choose for the cloud partner.

Microsoft Azure Feature Ratings

Service-level Agreement (SLA) uptime
Dynamic scaling
Elastic load balancing
Pre-configured templates
Monitoring tools
Operating system support
Security controls

Microsoft Azure Support

Most of the time one can easily receive the technical resolution from dev forums. We required dedicated customer support once only in two years and we have received timely and in-prompt support. We found [the] support team helpful and expert around the requested area.

Using Microsoft Azure

As Microsoft Azure is [doing a] really good with PaaS. The need of a market is to have [a] combo of PaaS and IaaS. While AWS is making [an] exceptionally well blend of both of them, Azure needs to work more on DevOps and Automation stuff. Apart from that, I would recommend Azure as a great platform for cloud services as scale.