You can’t possibly find any medium or large business today that doesn’t deploy cloud services in one form or another. Be it through infrastructure, software, or platform as a service, each of them has their own set of benefits to offer. We are here to talk about the latter.
Consider you have an application to host online. You can do it in one out of two ways- 1. Build it using your preferred set of tools and technologies and host it on any cloud; 2. Build the application on cloud itself using tools provided by them and host it there. While an in-depth comparison between the two approaches isn’t in the scope of this article, we can at least tell you this- if you take the second route, your application will have much better performance and scalability.
But these invaluable benefits bring with them their own set of challenges as well. As cloud applications are architecturally different from the traditional procedures of software development, the challenges they pose are also quite different than developers are generally accustomed to. Here are the most prominent ones:
The foremost concern before the cloud application developers is to ensure that the application remains online for the maximum possible time. The fact that even the most resourceful tech companies stop short of 99.9% and can’t guarantee cent percent availability is a testimony to how important yet daunting this challenge is.
So, while there is no way to solve this problem, AWS has features like Autoscaling and LoadBalancing, and Azure Autoscale from Azure that mitigates its effect to a large extent.
It is the ability of the application to sustain even if something goes wrong. Cloud applications generally run a single instance on many different servers simultaneously- which always comes with a chance of inconsistency and subsequent crashing.
To make applications more resilient most of the cloud service providers including AWS, Azure, and Google Cloud Platform, operate global infrastructure with independent availability zones.
As data is stored at different locations, managing the optimum level of consistency and redundancy remains a major challenge. If the redundancy is too low, there is always a risk of an outage but higher redundancy is simply a wastage of resources.
RDS and DynamoDB are the tools deployed by AWS for data management while Azure uses StoreSimple, Cold Store, and SQL Server.
Management and Monitoring
Real-time analytics is one of the key features that makes cloud applications appealing for businesses. But its implementation poses many different challenges in terms of exposing runtime information and required tools to appropriately monitor them.
AWS uses CloudTrail, CloudWatch, and VPC Flow logs for the purpose while Azure Monitor is a tool that aggregates all of these features on Azure platform.
This, of course, goes without saying. But the reason we are still mentioning is that security, unlike others, is a multi-pronged problem that encompasses many different dimensions within it. From the application to data to identity to the overall network, each of those components requires their own layer of security for the unique vulnerabilities they face.
AWS for instance, has KMS for data security, VPC, Security Groups, and Network ACLs for network security, and AWS Directory Service and IAM for identity management.
Cloud servers often lose coupling between various components and services. the messages are often asynchronous and that too without order and idempotency.
Scalability and Performance
Cloud systems have to be responsive and they must be able to perform in the same way even with increased load.
No, it’s not that cloud application development doesn’t face any other challenges. It’s just that these 7 require the most efforts and attention. On a similar note, if you pay closer attention, you will notice that none of these challenges are really atomic but are deeply intertwined. For instance, the more resilient an application is, the higher its availability it will have. That better data is managed, the better application’s performance and security will be. The point being, instead of tackling each of these challenges separately either at the architectural, implemental, or functional level, a more feasible way would take a holistic view keeping all components in the loop.