The Trends Making Serverless Computing the Next Big Thing in Cloud Computing
Serverless computing is one of the most exciting trends in cloud computing. It gives you the best of the cloud at the best cost efficiency. Web developers and application providers recognize serverless computing as the solution that best meets their needs, and they are inventing entirely new architectures and toolsets to get the most value out of cloud functions. They are striving to build high-performance, modern applications that can serve the most users globally at the lowest cost. Jamstack, multi-cloud architectures, cloud arbitrage, and data security are pushing cloud users to adopt cloud functions as the go-to solution for their applications and workloads.
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As static code, Jamstack applications are usually relatively small to download and very fast to load in visitors’ browsers. Deploying from CDNs or static hosting also gives Jamstack applications extremely flexible global scaling. In addition, CDNs or static web hosting are much cheaper to serve applications than full cloud platforms. Any dynamic data is pulled into the application from remote APIs or web services after the static code is loaded into the visitor’s browser.
Serverless computing (or function-as-a-service) has become one of the most popular options for providing dynamic data and performing complex data operations for Jamstack applications. The pay-what-you-use model of serverless computing is a natural partner for the cost efficiencies of the Jamstack approach. Jamstack developers are implementing RESTful APIs and microservices to power their applications as cloud functions.
While Jamstack may not replace a personal website or blog, it is gaining popularity among larger enterprises, websites, and applications. As of the writing of this piece, one of the most recent large Jamstack applications was the redesigned BBC News web application platform. The BBC News redesigned their entire web presence using a Jamstack-first architecture and AWS Lambda for their backend for dynamic content and data. They found the new application had better loading performance and lower costs compared to their legacy infrastructure using their own data centers. In addition, BBC News found better user engagement and usage performance after the redesign. Adoption and excitement from the enterprise space will drive the development of the Jamstack ecosystem to be better suited for non-enterprise use cases as with other established technologies like Kubernetes or OpenStack.
Multi-cloud architectures use multiple cloud systems or providers to take advantage of the strengths of different providers, to spread the risks to their workloads and infrastructure. Big cloud providers have outages just like the rest of us, despite their big uptime promises, and these outages are often complete losses of service instead of simply degraded performance.
Cloud native technology enables users to spin up infrastructure and workloads rapidly on cloud platforms, and new tools are making this possible across cloud providers. Despite advancements in tooling, however, managing cloud deployments using servers or containers is still relatively complex. A server-based or container-based infrastructure still has several different levels of complexity and configuration that must be addressed as part of a successful deployment.
Serverless computing will be the natural next step for multi-cloud users looking to improve the performance, resilience, and flexibility of their workloads when possible. Not every workload is suitable for serverless architecture without redevelopment, but multi-cloud users will see, like the Jamstack adopters, that cloud functions are much more scalable, flexible, and less prone to failure than traditional servers or containers.
Cloud functions are simpler to deploy than servers, and they can be pre-deployed ahead of when they are needed because they only cost money when they are triggered. Multiple major cloud providers have support for cloud functions, and new providers are adding support for serverless computing in order to stay competitive.
Cloud arbitrage uses automation to deploy compatible workloads to cloud platforms with the cheapest operating cost and the lowest latency. Cloud arbitrage providers closely monitor the cost and latency of multiple cloud providers to determine which platform is offering the lowest cost and the lowest utilization. Workloads are redistributed from cloud providers whose cost or latency increases beyond an acceptable threshold.
Some cloud users take this approach to complete their workloads in the shortest time at the cheapest price. Serverless computing is a natural fit for these needs. Cloud functions are generally cheaper and faster to complete than a traditional server-based workload. They do not require the full resource utilization of a server environment booting up or the time it takes to allocate compute resources. The few seconds or hundreds of milliseconds to start up new cloud resources can have a huge impact on the rapid-fire workloads dispatched using cloud arbitrage tooling.
The high profile security breaches from the last few years showed the importance of good security practices and a strong company culture for protecting user data and privacy. The privacy and safety of data are already becoming one of the top concerns among cloud users and operators. Large traditional cloud computing platforms have struggled to catch up with the changing security landscape of the modern cloud. From misconfigured object storage to out-of-date and vulnerable servers, cloud users struggle to protect their customers from having their personal information led onto the internet.
What if you could perform your work without a server? The security issues facing traditional server-based cloud deployments make serverless computing a more attractive solution to cloud users’ needs. Removing the servers from a cloud deployment would significantly decrease the organization’s attack surface and reduce the risk for misconfiguration. Moving to a serverless architecture can also eliminate time-consuming updates and maintenance for mission-critical 3rd-party software packages and services. Having a simpler configuration for cloud deployments also means there are fewer opportunities to introduce vulnerabilities through human error.
Most importantly for privacy, using a serverless architecture means there are fewer places where customer data can end up or be accessed. Each server in a cloud deployment can become a trap for customer data if the server keeps local logs of activity it performs or if it has to keep customer data in memory or on disk to perform its function. Cloud functions, in contrast, only keep sensitive information for as long as they are running. Once the cloud function has finished its work the memory and any remaining data are deleted along with the cloud function environment. Their logs also generally record to the serverless computing platform’s central logging functionality instead of a local log file.
Low Code and No-Code Applications
Low code and no-code platforms are the next generations of serverless computing. These tools let you build fully functional applications with minimal programming. Low code and no code applications are still relatively new, but they do not require servers. They function much like traditional serverless computing platforms with cloud functions, but instead of writing cloud functions from scratch applications are built out of standard blocks of code. While low code and no-code solutions are not exactly the same thing as normal serverless computing, they do support the same kind of architecture as Jamstack and other approaches that leverage serverless computing.
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