Developer Chris McCord introduces FLAME, a serverless approach with Phoenix framework, revolutionizing elastic compute. They delve into its unique scaling, Kubernetes option, and cross-language compatibility. The podcast also explores Elixir's evolution, LiveView Native beta, and machine learning in Elixir apps.
Flame simplifies scaling app functions elastically on ephemeral infrastructure without durability concerns.
Flame offers granular elasticity for specific app functions, simplifying concurrency and job queues.
Flame enables efficient execution of tasks without persistence, excelling in real-time user interactions.
Deep dives
Efficiently Scaling Ephemeral Tasks with Flame
Flame revolutionizes the idea of elastically scaling app functions by running the whole app on ephemeral infrastructure. This allows tasks like generating thumbnails from videos to be processed only when needed, without the need for durability or tracking the transient artifacts generated. Tasks that are crucial only in the user's presence, like live video broadcasts or real-time video processing, become seamless and efficient with Flame, eliminating the need for unnecessary persistence and scalability concerns beyond the user interaction.
Granular Elasticity and Simplified Workflows
Flame offers a granular approach to elasticity, enabling developers to scale specific functions of their app independently and efficiently. By abstracting away the complexity of concurrency and durable job queues, Flame simplifies workflows for tasks like video processing, machine learning operations, or live broadcasts, ensuring that computations are executed only when needed and discarded immediately after completion, optimizing resource usage and enhancing real-time user interactions.
Distinct Patterns and Use Cases for Flame
Flame presents a unique pattern for ephemeral execution, distinct from durable job queues like Open, focusing on tasks that require immediate processing without the need for persistence. With use cases ranging from real-time video processing to live broadcasts, Flame excels in scenarios where users only require transient results during their interaction with the application, streamlining processes and eliminating the overhead of managing and storing unnecessary artifacts.
Efficiency and Cost Savings in Ephemeral Computing
Flame's ephemeral computing model offers efficiency and cost savings by executing tasks on demand and discarding transient results once the user interaction ends. This approach, exemplified by tasks such as live broadcasts and on-the-fly video processing, optimizes resource utilization and streamlines workflows by eliminating the need for continuous compute resources, ensuring that computations are triggered and completed only as required, enhancing overall performance and user experience.
Eliminating Background Jobs with Flame for Real-Time Tasks
Flame introduces a fascinating shift in perspective by enabling real-time processing without the need for traditional background job queues. This approach proves exceptionally beneficial for tasks that require immediate action, such as live video transcription or on-the-fly PDF generation. By leveraging Flame, developers can seamlessly execute CPU-intensive operations like PDF generation instantly without relying on job queues, highlighting the efficiency and effectiveness of handling critical tasks in real-time.
Process Placement and Distributed Supervision in Elixir with Flame
Flame unveils a novel concept of process placement in Elixir, allowing for dynamic supervision and delegation of tasks to different server nodes elastically. This framework empowers developers to distribute supervised processes across servers, enhancing scalability and fault tolerance. Unique to Elixir, this process placement mechanism enables seamless communication and message passing between processes across distributed environments, showcasing the potential for enhanced stateful applications with efficient resource allocation.
In this week's episode, we ignite the exciting world of Elixir with Chris McCord's announcement of FLAME, showcasing a revolutionary approach to serverless with the Phoenix framework. Chris joins us to unravel the inspiration behind FLAME - Fleeting Lambda Application for Modular Execution and its promise to streamline the developer experience, significantly simplifying elastic compute. We discuss why this isn't just another job queue solution and explore how it effortlessly scales. We cover how other backends can be implemented and learn there's even a Kubernetes option! The FLAME pattern can be implemented in other languages and frameworks too. To avoid FOMO, tune in and ride the wave of Elixir's evolution with us.
