Serverless cloud computing empowers your developers to dedicate their time and efforts to writing the best application code possible.
It’s beneficial for your organization to understand what serverless computing is, as well as the pros and cons of the cloud model, in order to determine if it’s the right fit for your organization’s needs.
Serverless computing, things to know:
- What is serverless computing?
- Examples of serverless computing
- What are the advantages of serverless computing?
- What are the drawbacks of serverless computing?
- What makes serverless computing different from other cloud models?
- Knative and Serverless Kubernetes
- Future trends of serverless computing
What is serverless computing?
Serverless computing is a cloud-native development model that enables developers to build and run applications without needing to manage or provision servers. Serverless, also known as Functions as a Service (FaaS), allows the business to pay for “on-demand” services triggered by events and be charged only for the time the service runs.
Examples of serverless computing:
AWS Lambda, Google Cloud Functions, Microsoft Azure Functions, and IBM Cloud Code Engine are the most popular examples of serverless computing platform and services, offered by leading cloud providers. Each of these serverless services involves a cloud provider provisioning the required resources. Developers do not see or interact with the servers in any capacity.
What are the advantages of serverless computing?
There are several advantages of serverless computing including improved developer productivity, reduced operational costs, easier scalability, faster time-to-market, and empowering DevOps adoption.
- Improved developer productivity: By offloading traditional tasks of provisioning and managing servers, your developers are given more time to focus on developing application code.
- Reduced operational costs: Serverless models reduce costs by allowing you to pay for your cloud-based compute time as needed and “on-demand,” instead of constantly running and managing your own servers.
- Scalability: In serverless, the vendor handles all of the scaling on demand, removing the burden from IT to scale up their infrastructure.
- DevOps adoption: Serverless computing helps empower DevOps adoption by reducing the need for developers to explicitly communicate the infrastructure they need provisioned by operations.
- Faster time-to-market: With serverless architecture, developers can add and modify code bit by bit instead of needing to roll out bug fixes and new features in a complicated deploy process. This can significantly improve turnaround rates and reduce time-to-market.
What are the drawbacks of serverless computing?
Some negative drawbacks to consider with serverless computing include limited flexibility and customization, potential for vendor lock-in, increased start and scaling times and some concerns with security and privacy of data.
- Limited flexibility and customization: Some cloud providers have strict requirements and constraints on how teams can design and architect their components, which ultimately affects how customized and flexible your systems can be.
- Vendor lock-in: Giving up control of aspects of your IT stack can make you vulnerable to vendor lock-in. This makes it difficult to switch to a different cloud provider in the future without experiencing technical incompatibilities and high refactoring costs.
- Startup and scaling times: Startup and scaling times need to be considered as part of the overall design to be minimized to lessen end-user impacts.
- Security and privacy: Leveraging a cloud provider requires handing over your sensitive data to an external company and trusting a third-party vendor to deal with the security of that data.
What makes serverless computing different from other cloud models?
Cloud deployment types deal with where cloud servers are located and who manages them. Whereas with FaaS (serverless), the cloud providers manage and provision the required resources and the developers do not interact with the servers, the other common deployment types – IaaS, PaaS, and SaaS – each involve a different party managing the servers.
- Infrastructure as a Service (IaaS): IaaS involves leased IT infrastructure – including storage, operating systems, networks, and servers and virtual machines – from a cloud provider.
- Platform as a Service (PaaS): With PaaS, the provider focuses on software maintenance, resource procurement, and managing the underlying infrastructure of storage, databases, and servers. It allows organizations to focus on the development, testing, deployment, and management of their applications.
- FaaS (Functions as a Service): Serverless frees the business from much of the last remnants of infrastructure administration of PaaS.
- Software as a Service (SaaS): With SaaS, the cloud provider runs and manages the product, ensuring that the subscriber does not have to be concerned with how the service or infrastructure is managed or maintained. SaaS essentially works as a rental agreement, in which a business subscribes to a software application that it accesses over the internet.
What is Knative and Serverless Kubernetes?
Kubernetes is an open-source container orchestration platform used for automating software deployment, management, and scaling. This automation significantly simplifies development of container-based applications.
Kubernetes cannot run serverless apps without specialized software that integrates it with a cloud provider’s serverless platform.
Knative acts as an open-source extension to Kubernetes, providing a serverless framework and enabling any container to run as a serverless workload on a cloud platform that runs Kubernetes. Knative can run in any platform that runs Kubernetes.
With Knative, your developers create a service by packaging code as a container image and handing it to the system. Knative starts and stops instances automatically, so your code only runs when it needs to.
Developers just need to build a container as usual with Kubernetes and then leverage Knative to do the rest of the work, running the container as a serverless workload.
Future Trends of Serverless Computing
Within the past couple of years, we have started to see the long tail of service providers offer fully serverless applications. Providers like Linode, Cloudflare, and DigitalOcean, which used to only offer virtual machines, now offer fully serverless and containerized compute opportunities.
AIM’s technology experts project that this shift is going to reveal itself in a couple of interesting ways.
The first way will be an increasing adoption of serverless, and a greater understanding of application architecture that is designed for a fully serverless solution.
The second way will be second- and third-tier players increasing in popularity and adoption. AWS, Azure, and Google Cloud Platform (GCP) are not going to shrink, but it’s likely their overall market share will shrink because there are more players in the space.
Second- and third-tier provider options will compete on price by offering less robust services than AWS, Azure, and GCP. Organizations that don’t need that robustness will be able to enjoy the advantage of lower cloud costs.
How Can AIM Consulting Take Your Cloud to the Next Level?
AIM Consulting’s experts can help you navigate the investments you should be making in cloud technologies, migrate to cloud platforms, plan for business continuity and disaster recovery, and leverage cloud-based automation tools like AWS Pipeline for CI/CD.
Our flexible engagement model allows us to deliver from strategy to implementation to maintenance in ways that make the most sense for you and your business.
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