Serverless Computing Problems
Serverless Computing has revolutionized the IT front and transformed the definition and application of the internet. However, every technology is not foolproof and has its own set of drawbacks and problems. Serverless Computing is no different.
Here are prime reasons which are causing significant stagnation in the Serverless Computing domain:
Control and Monitoring
The fundamental fact is that third parties provide serverless computing, and we have to use third-party APIs to facilitate the tasks and functions. We are building on a platform provided by someone else.
In the case of non-serverless, there is a more significant degree of control and autonomy over the stack, ranging from software, queues, databases to authentication systems.
It is a trade-off between system control and providing business value. Foregoing extensive control can cause system downtime, unwanted API upgrades, functional loss, or sudden limits.
Consequently, real-time monitoring is very complex in serverless computing owing to a lack of control, standard tools, and the need to monitor not only the execution of codes but also integrations between different services to facilitate the completion of an end-to-end request.
Serverless Computing suffers from substandard configurations, posing an impending threat of data loss, breach and security. If permissions are not explicit, then a function of the service may be entitled to more access than required and allow a loophole. Another aspect is that a security mechanism inside a cloud cannot be transferred outside the cloud. Additional focus on safe connections and data encryption is paramount while connecting to third-party APIs. Lack of access overprovisioning, de-provisioning, and operations pose a substantial risk to governance, compliance, and data quality, and security management.
Even the easiest applications tend to have a complex architecture paradigm. The systems’ functioning is in your hands, and it is possible to encounter deployment-related bugs, which cannot be solved using IDE. End-to-end visibility at all times is critical, and testing serverless applications is a nightmare, owing to its distributive nature.
Lack of resources and expertise lead to extensive troubleshooting, slow data migrations, and hordes of problems while storing data on the cloud and clubbing cloud-based apps and legacy systems, especially in a hybrid cloud model.
Serverless computing indeed helps to reduce costs. However, its on-demand and scalable characteristics make it tricky to formulate a budget that could last months or deplete over weeks due to heavy usage. A cloud service can turn expensive if your organization does not comprehend the fluctuating demands, prices, and hidden costs.
Serverless Computing also has cold start costs, which leads to compounded invocation latency. Managing a hybrid cloud model also poses the difficulty of heavy expenditure on a dedicated cloud team and loss of time, efforts, and money if the provider faces an outage. Ad-hoc planning and resources can turn the cost-effective boon into an exorbitant bane.
Serverless Computing is still evolving and will face numerous problems. However, the essence is to pin these problems and work towards comprehensive, economical, and broad solutions to make its advantages and features outrun its drawbacks.
Other useful articles:
- What is Serverless Computing And How It Works
- How to Write a Serverless Code
- Serverless Computing Examples
- Serverless vs. Kubernetes
- Serverless vs. Microservices
- Serverless vs. PaaS
- Components of Serverless Computing Model
- Current Trends of Serverless Computing
- Front End and Back End Services
- Pros and Cons of Serverless Computing
- Serverless Computing Problems