Given our ability to order pizza with a voice command or play Jeopardy at home simply by talking out loud, the next generation of applications are here and they are voice-enabled. That means developers need to integrate conversation intelligence (CI) into their app in order to provide the best user experience possible.
Because these applications can fluctuate in the amount of backend processing needed at any given time, it’s important that servers can run the application code to scale. Using a serverless paradigm, you can let your cloud provider worry about scaling your conversation intelligence applications and focus on making the best application possible.
In this article, you’ll take a look at how to leverage serverless technologies and make sure your application is always available and ready for your users.
What Is Serverless?
Serverless technology doesn’t mean that there are no servers in use, however, *you* are not responsible for the servers that are being implemented.
By providing a piece of code in the form of a function to your cloud provider, they then allow you to call this function as many times as you want. The cloud provider handles all the provisioning of resources in the background and spins up new instances of your function to run in parallel, if necessary.
With serverless, you can achieve almost infinite scale, while only paying for what you use. This means that the backend infrastructure for your application can fade into the background and become something you think about less, even as your app continues to grow.
CI applications often need to scale unexpectedly. If your product suddenly onboards a huge enterprise customer or gets mentioned in a popular post on Reddit or Twitter, your application can find itself with more minutes of conversation to digest than normal. This is what makes serverless so well-suited for the conversational use case.
Serverless infrastructure scales automatically to handle any load. Your cloud provider will be able to create more serverless workers to parse the increased conversation backlog while minimizing the noticeable impact on your application for all new or existing users.
Serverless and Conversation Intelligence
Serverless is a great fit for CI applications. Let’s take a look at some of the reasons utilizing a serverless infrastructure makes sense.
Highly Scalable
With serverless, you don’t have to worry that you have too little infrastructure provisioned to handle an unexpected demand. For example, if you have a conversation application that parses information from a quarterly meeting, you might be able to predict the times that the application would be under the heaviest load. However, if you provide a consumer-facing application or allow new users to sign up on their own, the load on your application might be less predictable. Using serverless, your infrastructure can adjust to handle the amount of backlog and then scale down once the flood of traffic has been handled.
In addition, if you have a database or some other piece of infrastructure that your application depends on, you will need to ensure that it can handle an increased parallelism and scale.
For applications where you’re doing some language parsing, for instance a lookup of some information on an external resource, scaling up your infrastructure by utilizing a serverless paradigm and running that in parallel will be a huge asset for your business. It will also help reduce the amount of emergency situations caused by infrastructure overload.
Increasing parallelization allows your infrastructure to scale and ensures that all users receive a similar experience, regardless of any increased load your system may be under.
Cost Savings
One of the main benefits of the serverless paradigm is cost savings. Running a traditional server requires you to make sure it’s large enough to handle any potential spikes in load. If those spikes happen rarely, you’re paying for a powerful server even when it’s not being utilized.
With serverless, however, you only pay for the number of times your code is called and the time it runs. This means that you don’t need to worry about over-provisioning your infrastructure and only pay for the infrastructure that is needed.
The flip side to this is if you do have a spike in traffic or usage, your infrastructure costs will spike as well. The increase in traffic means you’ll pay for all the parallel execution and bandwidth that is now being used, which allows your application to process requests and serve data back to users.
You can set limits on the amount of concurrent executions your serverless functions can have in addition to following billing best practices. You benefit by not paying for infrastructure you aren’t using and limit the additional expenses your business can incur.
Processing Information
Most conservation applications process natural language and return a result based on processed input. Because serverless works when the operation that’s being performed is mostly the same over multiple iterations, the operation is stateless and parallelizable, making it a great fit for processing information quickly.
While you could use more traditional infrastructure for something like this, you don’t need your requests to be stateful or persist data. When you have a server that’s constantly running, it’s much easier to persist data between requests or manage incoming requests that require knowledge of other requests that are happening at the same time.
However, you have to keep this infrastructure running 24/7 and ensure that it stays running to reap these benefits. If you don’t need this sort of setup, it’s much easier to parallelize the execution of your functions with serverless. This makes your code run more efficiently and ensures you don’t worry about uptime or maintenance of servers.
Peace of Mind
Severless offers peace of mind because it is not managed by you after the initial setup. This makes it a potentially great fit if you’re adding conversation intelligence as another feature to your application. Because you don’t want to be forced to maintain the infrastructure for something that’s not the main feature of your app, the “set it and forget it” nature of serverless can be quite appealing.
Couple that with the auto-scaling capabilities included in the platform, and you have infrastructure that you don’t have to worry about after the initial setup.
By outsourcing the management of your CI infrastructure to your cloud provider, you can focus the resources of your business on your core application logic and features, making you more productive and ensuring your resources are used in the most effective way.
Conclusion
When deciding on backend infrastructure for your CI application, serverless should be considered. The cost savings and data processing offered with serverless provide a near-infinite potential for scaling up. This means your business can grow without worrying about your data processing capabilities.
Your infrastructure is managed by a cloud provider, meaning you don’t have to think about it once it’s in place. This winning combination can power any conversation intelligence application from its first users all the way up to web scale.
If you’re looking to add conversation intelligence to your application without having to deal with all of the complicated language processing yourself, Symbl.ai may be helpful. Symbl.ai ‘s collection of APIs allows you to build and extend applications with conversation intelligence at scale, which means you’re free to focus on the business logic of your application without having to worry about infrastructure at all.
