Application Providers Can Automate Software Development
Applications working on the SaaS model (application as a service), for example, Bitrix24, Skype for Business, and others are united by two standard features:
- They are constantly updated, so the high speed of bringing updates to the market (time to market) becomes an essential factor in competitiveness;
- They are sensitive to failures: if the SaaS goes down, a lot of dissatisfied users, a lot of publicity, to the point that they write about it in the news.
SaaS development is between two fires: you need to add new features faster than competitors while fixing bugs instantly and preventing a service crash.
The cloud infrastructure allows you to automate code testing, application assembly from components, and delivery of updates to users. A large company, some conditional Apple, with a strong IT expertise and technical base, can afford to build its infrastructure and hire employees to administer servers, networks, virtual environments, databases, containers, and other low-level elements. But if we take ordinary companies developing SaaS, this option is not possible for them.
PaaS solutions (platform as a service) will be precious for development: in the cloud, you can get ready-made and configured containers, machine learning systems, databases, and more. A small startup can take them like building blocks and build an automated development infrastructure in the cloud. According to Gartner, about 50% of cloud providers’ tools can only be obtained in the cloud and nowhere else.
E-commerce And Retail Receive Fault Tolerance Of Online Stores During Sales Peaks
The load on online stores and other retail services is often unpredictable. During the year, seasonal changes and unexpected peaks and falls in sales. In addition, surges in buying activity always occur during sales periods – sometimes, they go better than expected, and some “Black Friday” can quickly bring down the site. In 2018, websites were disrupted at Walmart, Lululemon, and Ulta. And the J.Crew brand lost $775,000 in five hours of downtime.
Building an infrastructure that can withstand peak loads is difficult and expensive in your own data center. We need to purchase additional servers in case of surges in sales. Such equipment will work only during hot periods, but it will have to be serviced during downtime – this is another item on the list of expenses. In addition, additional servers do not guarantee that the infrastructure will not collapse – you need to predict what load is expected during sales and promotions accurately, and this is not always possible.
In the cloud, automatic scaling is a tool for solving the problem. Cloud services can distribute user requests to different data centers. At the same time, the capacity of virtual resources that the company rents from the provider will automatically increase and decrease depending on the load. That is, during the sale, the ability can increase many times over so that the store can process all requests without problems. And at other times, capacity is reduced, and the company does not overpay for resources it does not use.
