Google Cloud Run VS Apache Kafka

Google Cloud Run Reviews

Apache Kafka Reviews

Google Cloud Run mentions (83)

• A Brief History Of Serverless

  In 2019, Google announced Cloud Run. This was, in essence, a managed Knative. Now, Cloud Run doesn't run on Kubernetes, but it is Knative Serving API compliant. This means that you could take a standard Knative YAML manifest and use it to deploy your containers to Cloud Run with no issue. - Source: dev.to / 9 days ago

• The 2024 Web Hosting Report

  Examples for products in this category are: Google Cloud Run, AWS App Runner, Azure Container Apps. Each has different scalability, cost, and integration trade-offs. - Source: dev.to / 3 months ago

• How to deploy a Django app to Google Cloud Run using Terraform

  Cloud Run is a managed platform that enables you to run container based workloads on top of Google infrastructure. Cloud Run automates many of the above steps and allows you to focus on developing and deploying updates to your application. - Source: dev.to / 5 months ago

• Golden Ticket To Explore Google Cloud

  Serverless computing was also introduced, where the developers focus on their code instead of server configuration.Google offers serverless technologies that include Cloud Functions and Cloud Run.Cloud Functions manages event-driven code and offers a pay-as-you-go service, while Cloud Run allows clients to deploy their containerized microservice applications in a managed environment. - Source: dev.to / 10 months ago

• Ultimate Guide to User Authorization with Identity Platform

  The quickest way is to deploy to Cloud Run. The service will use Dockerfile to build the production image. You can even omit the GOOGLE_APPLICATION_CREDENTIALS env var as these are in GCP’s projects by default. - Source: dev.to / 10 months ago

Apache Kafka mentions (120)

• Empowering Real-Time Data Pipelines: Leveraging Apache Kafka and Rudderstack

  In today’s fast-paced digital landscape, effective data management and analysis are essential for businesses aiming to stay ahead of the curve. Fortunately, modern tools like Apache Kafka and RudderStack have revolutionized the way we handle and derive insights from large datasets. In this blog post, we’ll explore our experience implementing the Kafka Sink Connector to facilitate seamless event data transfer to... - Source: dev.to / 2 months ago

• Choosing Between a Streaming Database and a Stream Processing Framework in Python

  Stream-processing platforms such as Apache Kafka, Apache Pulsar, or Redpanda are specifically engineered to foster event-driven communication in a distributed system and they can be a great choice for developing loosely coupled applications. Stream processing platforms analyze data in motion, offering near-zero latency advantages. For example, consider an alert system for monitoring factory equipment. If a... - Source: dev.to / 3 months ago

• How to Use Reductstore as a Data Sink for Kafka

  Apache Kafka is a distributed streaming platform capable of handling high throughput of data, while ReductStore is a databases for unstructured data optimized for storing and querying along time. - Source: dev.to / 4 months ago

• 🦿🛴Smarcity garbage reporting automation w/ ollama

  *Push data *(original source image, GPS, timestamp) in a common place (Apache Kafka,...). - Source: dev.to / 4 months ago

• How to Build & Deploy Scalable Microservices with NodeJS, TypeScript and Docker || A Comprehesive Guide

  RabbitMQ comes with administrative tools to manage user permissions and broker security and is perfect for low latency message delivery and complex routing. In comparison, Apache Kafka architecture provides secure event streams with Transport Layer Security(TLS) and is best suited for big data use cases requiring the best throughput. - Source: dev.to / 4 months ago