We use Microsoft Azure for hosting websites. It provides comprehensive control over our infrastructure and services.
Azure is easy to use and visualize.
It should improve database performance and make the platform more user-friendly. Additionally, providing more tools for seamless migration from AWS to Azure would be beneficial. Performance testing should ensure that systems remain reliable and transactions do not drop unexpectedly.
It should be thoroughly testet before release. Additionally, in Kubernetes, detailed documentation should be included, especially for STO.
I have been using Microsoft Azure for five years.
Microsoft Azure is highly scalable. It enhance the application's performance by managing increased demand efficiently. For instance, if around one thousand requests per second are coming in, Azure can handle this load seamlessly. Its scalability ensures consistent performance even under heavy traffic.
If you have an issue with Microsoft Azure, they will help me resolve it.
We use Terraform to deploy and configure our infrastructure on Microsoft Azure, following a hub-and-spoke model for networking.
It is a continuous process. Mostly, it takes about one and a half months for approval and around one month for deployment. Based on customer requirements or new needs, we continuously update the resources within the Azure infrastructure.
If I create a Terraform script, it significantly reduces the need for support. Typically, just two or three people are needed to manage it.
Azure is a strong competitor to AWS. AWS has a competitive pricing strategy, but Azure offers unique benefits. Azure provides credits, which can reduce costs for a certain period. For example, you might receive yearly credits, resulting in zero infrastructure investment for that year.
In comparison to AWS, Azure is user-friendly and has lower cost. Azure also provides good performance over time.
In Kubernetes, what we are using offers different features, which is good. We are enabling more drivers and integrations, which is beneficial. Regarding virtual machines, they also perform very well.
We are using cognitive services include the Face API.
We have built a comprehensive AI search feature, specifically Cognitive Search, and implemented it in our application.
If a product is supposed to include certain features, it performs as expected. The support team ensures it is a reliable product, without parts that don't work. Products are thoroughly tested to ensure quality. However, in Azure, maintaining new products can be challenging and requires significant work. AWS fixes these issues more efficiently.
Some startups choose Azure because they may not have much funding. These startups find Azure services beneficial and cost-effective.
Overall, I rate the solution an eight out of ten.