What is Serverless Computing?
Serverless computing is a cloud computing execution model where the cloud provider dynamically manages the allocation and provisioning of servers. Developers no longer have to worry about managing or operating servers or backend infrastructure. Instead, they simply deploy code, and the cloud provider handles the details of scaling and administration of the servers that run the code. This automated server management allows developers to focus solely on writing code. Serverless computing brings immense benefits like no server provisioning, automatic scaling, pay per use billing and faster time to market. However, as with any new technology, it also poses some challenges that must be addressed for successful adoption.
In this blog post, we will do a deep dive into the major challenges of Serverless Computing.
1. Vendor Dependence
One of the biggest challenges of serverless computing is vendor dependence. Most serverless offerings today come from the major cloud providers like AWS, Microsoft Azure, and Google Cloud. By adopting serverless, you become locked into a single vendor’s ecosystem. This can make it difficult to migrate or integrate services across different providers. There are also risks associated with relying too heavily on a single vendor. If there are performance issues or an outage, your applications may be severely impacted.
2. Monitoring and Debugging
The ephemeral nature of serverless functions makes monitoring and debugging tricky. With traditional servers, companies can monitor metrics and logs to optimize performance. But with serverless, these insights are harder to obtain since functions dynamically scale and execute only as needed. Vendors provide some monitoring tools, but they may lack deeper insights. More advanced debugging can require running functions locally which takes away some serverless benefits.
3. Cold Starts
Cold starts refer to the latency associated with launching a new function instance. They occur when a function has not been invoked recently and needs to start up again. Cold start latencies can vary from a few hundred milliseconds to several seconds. For time sensitive applications, long cold starts could negatively impact customers. While cold starts can be reduced through proper optimization and configuration, they remain an inherent challenge with serverless.
4. Testing and Deployments
The deployment methodology for serverless functions differs from traditional architectures. Teams must get used to deploying individual functions versus larger applications. Automated testing and CI/CD pipelines become more complex across dynamically scaling functions. While serverless removes server management, it does not eliminate the need to test and refine code before deploying it into production.
5. Training and Expertise
Serverless represents a fundamentally new way of building apps for many developers. It requires training developers on not just new services, but also a new “serverless mindset”. Many optimizations like reducing cold starts rely on developers taking a functions-first approach. Due to its relative newness, there is also less abundant documentation and expertise around serverless. It may require hiring staff with serverless skills or investing in extensive training.
Serverless computing enables developers to build and deploy apps without managing servers. But as we explored, it also brings along new challenges around vendor dependence, monitoring, debugging, cold starts, testing, and training. Companies looking to leverage serverless should ensure they have plans to address these challenges before wholesale adoption. With the right strategy, serverless can deliver automation, cost savings, and faster innovation without the headaches.