Apache Kafka
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Encore Cloud automates infrastructure and DevOps, letting you ship 3x faster with 90% less DevOps work, using your own cloud on AWS & GCP. โ Get enterprise-grade infrastructure without the complexity and DevOps overhead โ Enable safe AI-assisted development with built-in guardrails โ Gain full visibility across your stack with built-in Service Catalog, API documentation, and tracing
Key Features:
Production-Ready AI Assisted Development: Encore's parser validates all generated code to ensure it correctly implements service and API definitions, infrastructure integrations, etc.
No boilerplate: Encore drastically reduces the boilerplate needed to set up a production ready backend application. Define backend services, API endpoints, and call APIs with a single line of Go code.
Distributed Tracing: Encore instruments your application for excellent observability. Automatically captures information about API calls, goroutines, HTTP requests, database queries, and more. Automatically works for local development as well as in production.
Infrastructure Automation: Encore automatically provisions and manages your cloud infrastructure. Works with all the major cloud providers and you deploy to your own account (AWS/Azure/GCP).
Simple Secrets: Easily store and securely use secrets and API keys. Never worry about how to store and get access to secret values again.
Service Catalog and Automatic API Documentation: Encore parses your source code to understand the schemas for all your APIs and automatically generate interactive API Documentation.
Apache Kafka Encore.devBased on our record, Apache Kafka should be more popular than Encore.dev. It has been mentiond 155 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Kafka is a distributed streaming platform used to build real-time data pipelines and streaming applications. It allows producers to send messages to topics, which are then consumed by various consumers, making it ideal for event-driven architectures. - Source: dev.to / 2 months ago
Apache Kafka is the most widely used distributed event streaming platform and the standard transport layer for event-driven reconciliation architectures. - Source: dev.to / 3 months ago
For message-queue-based pipelines: RabbitMQ has native DLQ support through dead letter exchanges. Messages that exceed their retry count or their time-to-live are automatically routed to a designated DLQ exchange. Apache Kafka does not have native DLQ semantics, but the standard pattern is to write failed records to a dedicated topic (-dlq by convention) and include the failure metadata in the record headers. - Source: dev.to / 3 months ago
Upsert with timestamp tracking. Keep the upsert approach but track which time windows have been fully processed. On retry, skip windows that are marked complete and reprocess only windows that failed mid-run. The Kafka documentation covers offset management patterns that implement this for stream-based pipelines. - Source: dev.to / 3 months ago
Apache Kafka allows the payment service to publish a transaction event to a topic, without knowing who will consume it. The fraud service, the notification service, and any other interested component can subscribe to that topic independently:. - Source: dev.to / 3 months ago
This is close to what we're doing with [Encore](https://encore.cloud). The framework parses your application code through static analysis at compile time to build a full graph of services, APIs, databases, queues, cron jobs, and their dependencies. It uses that graph to provision infrastructure, generate architecture diagrams, API docs, and wire up observability automatically. The interesting side effect is that... - Source: Hacker News / 6 months ago
If you want to replicate Heroku's git push workflow while owning your infrastructure, Encore Cloud provisions managed resources in your own AWS or GCP account (powered by Encore, an open-source framework with 11k+ GitHub stars). You declare infrastructure as type-safe objects in your TypeScript or Go code, and Encore provisions the corresponding managed services. Everything else is standard TypeScript or Go. - Source: dev.to / 6 months ago
I work at Encore so I'm biased. We've had a bunch of people migrate over from Heroku in the last couple years, especially after they killed the free tier. The main difference from other alternatives is that you don't write any infrastructure config - you just declare what you need in your code (databases, cron jobs, pubsub, etc) and Encore handles provisioning it in your AWS/GCP account (works locally as well... - Source: Hacker News / 6 months ago
Most teams should start with the simplest option that meets their needs, then evolve if necessary. If you're building a backend application and don't want to become an infrastructure expert, Encore is worth trying. If you need maximum flexibility or multi-cloud support, Terraform is the industry standard. - Source: dev.to / 7 months ago
Today, we're launching Encore Cloud 2.0, a big upgrade to our development platform that understands your code and automates the operations layer. - Source: dev.to / 8 months ago
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