Serverless computing has transformed the world of cloud computing over the past decade. This technology allows developers to build and run applications without the need for server provisioning or backend infrastructure management. While initially used mainly for Function-as-a-Service (FaaS), serverless has now expanded to support large-scale, compute-intensive workloads, such as container-based architectures and batch jobs.
As we approach KubeCon 2023, several trends are emerging in the serverless space. MongoDB, a leading provider of database solutions, also shares their insights on this transformative technology.
Serverless prioritizes developers
With the evolving role of developers and increasing demands, organizations need to adopt technologies that simplify and enhance the developer experience. Serverless offers improved developer efficiency by providing pre-made integrations that enable quick utilization of application functionality and accelerated market deployment. This technology allows developers to focus more on coding and less on infrastructure management.
IBM has taken serverless to the next level with its unified serverless platform, IBM Cloud Code Engine. This platform offers a single deployment experience for running containers, deploying source code, and submitting larger batch workloads. It provides a common API and user experience, simplifying development and leveraging a pay-per-use consumption model.
Serverless reduces vendor lock-in
IT professionals seek technologies that provide flexibility and avoid vendor lock-in. Although some serverless solutions are proprietary, there is a growing number of serverless options built on open-source technologies like Kubernetes, Istio, knative, and packet. These open-source solutions allow for more portable workloads, reducing the risks associated with vendor lock-in. IBM emphasizes the importance of collaborating with an ecosystem of partners, even if they are competitors, to eliminate complexities and promote flexibility.
Serverless supports compute-intensive workloads
Enterprises are rapidly adopting compute-intensive technologies, such as High-Performance Computing (HPC) and AI. However, the costs and skills required for these solutions often hinder adoption. Serverless technology addresses these challenges by managing infrastructure and allowing rapid enablement and pay-per-use models. It empowers HPC users and AI workloads to quickly bring their innovations to market without the burden of infrastructure complexities.
Chris Shum, Director of Product Management at MongoDB, also emphasizes the importance of serverless for building modern applications. He highlights the need for developer-centricity and serverless integration within database solutions to enable developers to focus on innovation rather than database management.
Meet IBM at KubeCon
KubeCon is the perfect opportunity to connect with IBM experts, including the authors of this article. IBM will be hosting several sessions at KubeCon, providing insights into serverless and other innovative technologies.
Learn more about IBM Cloud Code Engine and register for IBM’s sessions at KubeCon.
Frequently Asked Questions (FAQ)
What is serverless technology?
Serverless technology is a cloud computing application development and execution model that allows developers to build and run applications without the need for server provisioning or backend infrastructure management.
How does serverless improve developer efficiency?
Serverless technology simplifies the developer experience by utilizing pre-made integrations that allow quick utilization of application functionality and accelerated market deployment. It allows developers to focus more on coding and less on infrastructure management.
Does serverless technology reduce vendor lock-in?
While some serverless solutions may create vendor lock-in, there are also serverless options built on open-source technologies that promote more portable workloads, reducing the risks associated with vendor lock-in.
What types of workloads does serverless support?
Serverless technology supports compute-intensive workloads such as High-Performance Computing (HPC) and AI. It simplifies infrastructure management, enables rapid enablement, and offers a pay-per-use model, making it beneficial for these types of workloads.
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