Question 1

How do I build a microservice with Flogo?

Accepted Answer

Use the CLI to create an app with triggers like REST, define actions in JSON DSL or Go API, and build a lightweight binary. The README provides a Go example for a simple REST API with logging and response handling.

Question 2

Flogo vs Node.js for serverless functions?

Accepted Answer

Flogo produces ultra-light binaries (sub-10MB) vs Node.js's larger runtime, making it better for edge devices and cold starts, but Node.js has a vast npm ecosystem. Flogo is ideal when footprint and Go efficiency are priorities over third-party library breadth.

Question 3

Can Flogo process real-time data from Kafka?

Accepted Answer

Yes, Flogo includes Kafka triggers in the contrib repository to consume events, which can be dispatched to actions like streams for aggregation or flows for integration, enabling real-time pipelines without heavy infrastructure.

Question 4

What are the limitations of Flogo streams?

Accepted Answer

Streams are in-memory and non-persistent, so data is lost on app restart, and windowed aggregations are limited to time or event-based windows without built-in fault tolerance. It's best for pre-processing or lightweight analytics.

Question 5

How to deploy a Flogo app to AWS Lambda?

Accepted Answer

Build your app as a binary using the CLI, then package it with a Lambda runtime client or use custom runtimes. The deployment flexibility allows it, but you'll need to handle AWS-specific configuration and triggers manually.

Question 6

Does Flogo support machine learning integration?

Accepted Answer

Yes, it has a native activity for TensorFlow SavedModel inferencing, mentioned in the highlights, allowing you to incorporate ML models into event-driven apps for tasks like real-time predictions on edge data.

flogo

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