Big Industries’ Post

Following the series “Exploring Messaging and Streaming Technologies”, in Part 3, Francine Anestis explores the Key Features, Architecture, Use Cases, Strengths & Weaknesses, Cost and Maturity Level of Azure Event Hubs. In previous blogposts she explored Apache Kafka & Apache Pulsar https://hubs.ly/Q02DxfLG0

Following the series “Exploring Messaging and Streaming Technologies”, in Part 3, Francine Anestis explores the Key Features, Architecture, Use Cases, Strengths & Weaknesses, Cost and Maturity Level of Azure Event Hubs. In previous blogposts she explored Apache Kafka & Apache Pulsar https://hubs.ly/Q02QX2Hj0

Following the series “Exploring Messaging and Streaming Technologies”, in Part 3, Francine Anestis explores the Key Features, Architecture, Use Cases, Strengths & Weaknesses, Cost and Maturity Level of Azure Event Hubs. In previous blogposts she explored Apache Kafka & Apache Pulsar https://hubs.ly/Q02N13xD0

Following the series “Exploring Messaging and Streaming Technologies”, in Part 3, Francine Anestis explores the Key Features, Architecture, Use Cases, Strengths & Weaknesses, Cost and Maturity Level of Azure Event Hubs. In previous blogposts she explored Apache Kafka & Apache Pulsar https://hubs.ly/Q02QX4Yt0

Following the series “Exploring Messaging and Streaming Technologies”, in Part 3, Francine Anestis explores the Key Features, Architecture, Use Cases, Strengths & Weaknesses, Cost and Maturity Level of Azure Event Hubs. In previous blogposts she explored Apache Kafka & Apache Pulsar https://hubs.ly/Q02N0Zg50

Following the series “Exploring Messaging and Streaming Technologies”, in Part 3, Francine Anestis explores the Key Features, Architecture, Use Cases, Strengths & Weaknesses, Cost and Maturity Level of Azure Event Hubs. In previous blogposts she explored Apache Kafka & Apache Pulsar https://hubs.ly/Q02Dxj-50

🚀 Scaling Kubernetes with #KEDA: The Power of Event-Driven Autoscaling 🚀 When it comes to scaling workloads in Kubernetes, KEDA (Kubernetes Event-Driven Autoscaling) is a game-changer. It brings event-driven capabilities to Kubernetes, enabling automatic scaling of applications based on custom metrics and external event sources. 📈⚡ With KEDA, you can seamlessly scale workloads in response to various triggers like message queues, databases, or custom metrics – not just CPU or memory usage. This makes it perfect for handling bursty traffic, event-based workloads, and asynchronous processing tasks. 🎯 Key Benefits of KEDA: • ⚡ Event-driven Scaling: Scale based on real-time events and custom metrics. • 🔄 Fine-Grained Control: Scale to and from zero for truly serverless deployments. • 🛠️ Wide Integration: Supports multiple event sources, including RabbitMQ, Kafka, Azure Functions, and more. 🔧 Popular Use Cases: Serverless computing, IoT event processing, asynchronous background tasks, and real-time data processing. If you’re working with Kubernetes and need efficient scaling for your workloads, KEDA is definitely worth exploring! #Kubernetes #KEDA #CloudNative #DevOps #EventDrivenArchitecture #Autoscaling #Serverless #ContainerOrchestration #TechTrends

For all the serverless enthusiasts out there, check out this new pattern I recently added on ServerlessLand showcasing the seamless integration of creating an IoT rule with an SNS action that delivers messages to an SQS queue in terraform 🚀🌐 https://lnkd.in/gci3e4xM #ServerlessLand #iot #iotintegration #SNS #patterns #Serverless #AWS #eventdrivenarchitecture #sqs #terraform