ApacheKafka
nodejs-pubsub
ApacheKafka | nodejs-pubsub | |
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104 | 24 | |
28 | 512 | |
- | 0.4% | |
0.0 | 8.4 | |
5 months ago | 1 day ago | |
TypeScript | ||
- | Apache License 2.0 |
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ApacheKafka
- PubNubとIFTTTによるSMS通知システム
- PubNub 및 IFTTT를 사용한 SMS 알림 시스템
- Système de notification par SMS avec PubNub et IFTTT
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Wie man Ereignisse von PubNub zu RabbitMQ streamt
Senden an Kafka (d. h. Senden der Daten an Apache Kafka)
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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 machine's temperature exceeds a certain threshold, a streaming platform can instantly trigger an alert and engineers do timely maintenance.
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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.
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🦿🛴Smarcity garbage reporting automation w/ ollama
*Push data *(original source image, GPS, timestamp) in a common place (Apache Kafka,...)
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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.
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Easy Guide to Integrating Kafka: Practical Solutions for Managing Blob Data
Apache Kafka is a distributed streaming platform to share data between applications and services in real-time.
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Go concurrency simplified. Part 4: Post office as a data pipeline
also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc.
nodejs-pubsub
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Event-Driven Architecture 101
Secondly, Go is incredibly easy to learn and in my opinion, maintain. This means that if you're a growing company and expect to onboard new teams and team members, having Go as a basis for your systems should mean that new engineers can get up to speed quickly. Below is a small sample application that can connect to Google PubSub, subscribe to a topic, send an event and then clean up. In total, its 82 lines of code including liberal line breaks. Even if you have never written or read a line of Go before, I hope you'll agree that it's quite clear and readable:
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Kafka alternatives
Pub/Sub
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Top 6 message queues for distributed architectures
Google Cloud Pub/Sub is a fully-managed, globally scalable and secure queue provided by Google Cloud for asynchronous processing messages. Cloud Pub/Sub has many of the same advantages and disadvantages as SQS due to also being cloud hosted. It has a free and paid tier.
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Job Scheduling on Google Cloud Platform
Cloud Pub/Sub: A global messaging service for event-driven architectures
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Messaging Patterns 101: A Comprehensive Guide for Software Developers
Google Cloud Pub/Sub (*https://cloud.google.com/pubsub*)
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Effortlessly Scale Your Applications with FaaS: Learn How Functions as a Service Can Help You Grow and Thrive
Google Cloud Functions is a FaaS offering from Google Cloud Platform (GCP). It allows developers to run their code in response to events, such as changes in a database or the arrival of a message in a Pub/Sub topic. Like AWS Lambda, Google Cloud Functions can be used to build a variety of applications, including serverless websites, data processing pipelines, and real-time data streams.
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Mixing GCloud and F#
that gets triggered when a Pub/Sub topic is fired (from the webhook function)
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What is the best data storage solution for high-frequency (near real-time) updates
Maybe Pub/Sub from GCP?
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Kafka on GKE cluster security guidelines
I'm curious - given your limited knowledge, is there a reason you're looking to self host this in your own cluster rather than using a managed service like https://cloud.google.com/find-a-partner/partner/confluent-inc?redirect= or just native Google PubSub https://cloud.google.com/pubsub/ ?
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Moving to Google Cloud managed services, from a FinOps point of view
Pub/Sub, the GCP managed service for message queuing, has two levels of services on standard and one Lite. Standard is the high availability version of it and Lite could be a zonal or regional service with infrastructure managed by the client. Obviously, the model pricing will be very different with a x10 between Standard and zonal Lite. However, the model pricing is the same is based on throughput for message publishing, message storage costs and egress for message distribution. Here, we totally break the similarity with a VM model (except on storage). Everything is drived on volumetry and performance of inbound and outbound messages.
What are some alternatives?
dramatiq - A fast and reliable background task processing library for Python 3.
twitch - Interact with Twitch's API, chat and subscribe to events via PubSub and EventSub.
outbox-inbox-patterns - Repository to support the article "Building a Knowledge Base Service With Neo4j, Kafka, and the Outbox Pattern"
mitt - 🥊 Tiny 200 byte functional event emitter / pubsub.
Jenkins - Jenkins automation server
svelte-persisted-store - A Svelte store that persists to localStorage
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
istio - Connect, secure, control, and observe services.
NATS - High-Performance server for NATS.io, the cloud and edge native messaging system.
Grafana - The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
MySQL - MySQL Server, the world's most popular open source database, and MySQL Cluster, a real-time, open source transactional database.