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Cloud Serverless

List the competing alternatives in 1. AWS Serverless, 2. Azure Serverless, 3. GCP Serverless, 4. IBM Cloud Serverless, 6. IBM z Mainframe Serverless, 7. Oracle Cloud Serverless, 8. Kubernetes Serverless, 9. VMWare Cloud Serverless / Tanzu Serverless, 10. Alibaba Cloud Serverless, 11. DigitalOcean Serverless, 12. Huawei Cloud Serverless, 13. Tencent Cloud Serverless, 14. On-Premises Data Center Serverless using Open Source Cloud / Private Cloud Technologies. When you make a numbered list, precede the number with an asterisk and a space. Put a section heading for each paragraph. You MUST put double square brackets around ALL computer buzzwords, product names, or jargon or technical words. Answer in MediaWiki syntax.

Here's a comprehensive list of serverless computing alternatives offered by various cloud platforms, including on-premises solutions that leverage open-source or private cloud technologies for serverless capabilities.

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• AWS Lambda: A serverless compute service that lets you run code without provisioning or managing servers.
• Amazon API Gateway: Allows you to create, publish, maintain, monitor, and secure APIs at any scale.

• Azure Functions: Enables you to run event-driven code without having to explicitly provision or manage infrastructure.
• Azure Logic Apps: Helps you automate workflows, integrate apps, data, services, and systems.

• Google Cloud Functions: A lightweight, event-based, asynchronous compute solution that allows you to create small, single-purpose functions.
• Google App Engine: A fully managed, serverless platform for building highly scalable web applications and APIs.

• IBM Cloud Functions: Based on Apache OpenWhisk, it provides an event-driven compute service for executing code in response to events or direct invocations.

• Oracle Cloud Functions: A managed, multi-tenant, scalable, on-demand, compute environment that runs code in response to events or direct invocations.

• Knative: An open-source Kubernetes-based platform to build, deploy, and manage modern serverless workloads.

• While VMWare traditionally focuses on virtualization, with VMware Tanzu, it steps into the Kubernetes ecosystem, potentially paving the way for serverless capabilities on Kubernetes clusters.

• Alibaba Cloud Function Compute: A fully-managed event-driven compute service that allows you to build applications without thinking about servers.

• As of my last update, DigitalOcean hadn't announced a native serverless compute service, but its cloud computing platform supports deploying applications that can benefit from serverless architectures.

• Huawei Cloud FunctionGraph: A fully managed, event-driven compute service that helps you focus on your code without managing servers.

• Tencent Cloud Serverless Cloud Function (SCF): An event-driven, fully managed computing service that enables you to focus on writing and uploading code without managing servers.

• On-premises environments can leverage open-source projects like OpenFaaS, Kubeless, and Fission for serverless computing capabilities, running on top of Kubernetes for orchestrating containerized applications.

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This list showcases the diverse range of serverless computing options available across major cloud providers and technologies, enabling organizations to deploy applications without the hassle of managing servers, focusing solely on writing code that scales automatically and efficiently.

Cloud Serverless Best Practices

Summarize this topic in 20 paragraphs. Put a section heading for each paragraph. You MUST put double square brackets around ALL computer buzzwords, product names, or jargon or technical words. Answer in MediaWiki syntax.

Implementing best practices for serverless computing can significantly enhance the efficiency, reliability, and security of your serverless applications. Here’s a structured guide on optimizing serverless architecture.

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Understanding and implementing best practices in serverless computing is crucial for leveraging the full potential of cloud serverless architectures, ensuring applications are scalable, cost-effective, and secure.

Design your functions to be stateless, allowing them to scale horizontally without relying on any particular instance of a function.

Keep your function execution time as short as possible to reduce latency and costs. Profile and optimize your code to remove any unnecessary processing.

Utilize asynchronous invocation for functions that don't require immediate responses, improving system throughput and efficiency.

Design robust error handling within your functions, including retries and dead letter queues, to manage transient and persistent errors gracefully.

Apply the principle of least privilege by granting minimal permissions needed for your functions to execute, reducing the potential impact of security breaches.

Optimize dependencies and the size of your deployment package to reduce cold start times, ensuring faster function execution, especially for critical applications.

Use caching for frequently accessed data within your serverless applications to minimize database hits and improve response times.

Architect your serverless applications to handle variable workloads efficiently, utilizing the auto-scaling capabilities of serverless platforms.

Implement comprehensive monitoring and logging to track the performance and health of your serverless applications, facilitating easier debugging and optimization.

Deploy API gateways in front of your serverless functions to manage access, monitor traffic, and offload authentication.

Carefully manage dependencies to keep your functions lightweight and to reduce the time taken to start and execute your functions.

Break down large, monolithic functions into smaller, composable functions to improve maintainability, scalability, and deployment flexibility.

Version your serverless functions and configurations for better manageability and to support rollback in case of issues.

Store configuration and secrets in environment variables, not in function code, to enhance security and simplify configuration changes.

Continuously review your serverless architecture against evolving best practices and application requirements to ensure optimal performance.

Ensure your serverless functions are idempotent where possible, especially for operations that may be retried, to prevent unintended side effects.

Use custom domains with your serverless applications to provide a branded and professional user experience.

Be mindful of the pricing model of serverless services and design your applications to minimize unnecessary executions, data transfers, and storage.

Adhering to these cloud serverless best practices will help organizations build efficient, secure, and highly scalable serverless applications. Continuous evaluation and adjustment of these practices are key to maximizing the benefits of serverless computing. ```

These guidelines provide a roadmap for building and managing serverless applications in the cloud, focusing on performance, security, and cost optimization to fully leverage the serverless model's advantages.

Snippet from Wikipedia: Serverless computing

Serverless computing is a cloud computing execution model in which the cloud provider allocates machine resources on demand, taking care of the servers on behalf of their customers. Serverless is a misnomer in the sense that servers are still used by cloud service providers to execute code for developers. However, developers of serverless applications are not concerned with capacity planning, configuration, management, maintenance, fault tolerance, or scaling of containers, virtual machines, or physical servers. When an app is not in use, there are no computing resources allocated to the app. Pricing is based on the actual amount of resources consumed by an application. It can be a form of utility computing.

Serverless computing can simplify the process of deploying code into production. It does not entirely remove the complexity, but mainly shifts it from the operations team to development team. And the more fine grained the application, the harder it is to manage it.

Serverless code can be used in conjunction with code deployed in traditional styles, such as microservices or monoliths. Alternatively, applications can be written to be purely serverless and use no provisioned servers at all. This should not be confused with computing or networking models that do not require an actual server to function, such as peer-to-peer (P2P).

One proposed definition for serverless computing that encompasses these ideas is that serverless computing is a "cloud computing paradigm encompassing a class of cloud computing platforms that allow one to develop, deploy, and run applications (or components thereof) in the cloud without allocating and managing virtualized servers and resources or being concerned about other operational aspects. The responsibility for operational aspects, such as fault tolerance or the elastic scaling of computing, storage, and communication resources to match varying application demands, is offloaded to the cloud provider. Providers apply utilization-based billing: they charge cloud users with fine granularity, in proportion to the resources that applications actually consume from the cloud infrastructure, such as computing time, memory, and storage space."

According to Yan Cui, serverless should be adopted only when it helps to deliver customer value faster. And while adopting, organizations should take small steps and de-risk along the way.

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Research:

• Cloud Serverless on DuckDuckGo
• Cloud Serverless on Google.com
• Cloud Serverless on AWS Docs
• Cloud Serverless on O'Reilly
• Cloud Serverless on GitHub
• Cloud Serverless on Kubernetes.io
• Cloud Serverless on Azure Docs
• Cloud Serverless on GCP Docs
• Cloud Serverless on IBM Docs
• Cloud Serverless on Red Hat Docs
• Cloud Serverless on Oracle Docs
• Cloud Serverless on Reddit
• Cloud Serverless on StackOverflow
• Cloud Serverless on YouTube

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