Welcome back to our Azure Data Factory Series! Today, we’re diving deep into how to add a second node to the Self-Hosted Integration Runtime (SHIR) for workload sharing and high availability 🖥️💪. Whether you're working with massive datasets or mission-critical processes, ensuring continuous uptime is a must. With this setup, even if one node goes down, your data pipeline will keep running smoothly, preventing downtime. Let’s get started!
🔹 What is Self-Hosted Integration Runtime (SHIR)?
First, let’s revisit what SHIR is. Self-Hosted Integration Runtime (SHIR) enables data movement across on-premises and cloud environments 🌐. Unlike the default Azure Integration Runtime (IR), SHIR gives you the flexibility to connect to on-premises data sources, offering a bridge between your local network and Azure Data Factory.
Key SHIR Features:
On-premises to cloud connectivity 🌍
Custom environment configuration 🔧
Support for data sources behind firewalls 🔐
Ability to scale with additional nodes 🖥️🖥️
🔹 Why Add Multiple Nodes?
So, why should you consider adding another node to your SHIR? With multi-node setup, you can achieve several benefits:
Workload Distribution: Tasks are divided between multiple nodes, improving performance 🏎️.
High Availability: If one node fails, the other will keep things running, preventing downtime ❌.
Resilience: More nodes mean better handling of unexpected failures 💥.
By setting up a second node, we create a reliable infrastructure for mission-critical workloads that ensures uninterrupted operations 💼.
🔹 Prerequisites for Adding a Node
Before we dive into adding a second node, here’s what you’ll need:
Existing SHIR Node: At least one SHIR node should already be set up.
Access to Azure Data Factory: You need administrative access to your Azure portal 🔑.
A Secondary Server or Machine: This machine will act as the second node for SHIR 🌐.
Proper Networking Setup: Ensure that your environment supports communication between the two nodes through your network or firewall settings 🌐🔐.
🔹 Step-by-Step Guide: Adding a Second Node to SHIR 🎯
Now that we’re set, let’s jump into the step-by-step guide for adding a second node:
Step 1: Navigate to the Integration Runtime (IR) Settings
Go to your Azure Data Factory instance, then navigate to the Manage section. Under Connections, select Integration Runtime (IR).
Step 2: Locate Your Existing SHIR
Here, you should see your existing SHIR listed. Click on the SHIR you want to add another node to. 🎯
Step 3: Download and Install SHIR on the New Node
Under the SHIR details, you’ll find an option to download the SHIR installer. Download it and install it on your second server or machine 🖥️. Follow the installation wizard and use the generated authentication key to connect this node to the existing SHIR instance 🔑.
Step 4: Verify Installation and Configuration
Once installed, ensure that the second node is listed under the SHIR settings in Azure Data Factory. Both nodes should be visible and ready to share workloads 🤝.
🔹 Configuring High Availability and Workload Sharing 🔄
With two nodes added, let’s focus on making sure that the workload sharing and high availability features are correctly configured. Here’s what happens under the hood:
Load Balancing: Azure Data Factory will now automatically balance workloads between the two nodes, leading to faster processing and optimized performance ⚡.
Failover: In case one node goes down, the other node takes over, ensuring that your pipelines remain operational without interruptions 🔄.
Bonus Tip: Add More Nodes for Even Greater Scalability! 🚀
For larger workloads or environments requiring ultra-reliable uptime, consider adding even more nodes! The beauty of SHIR is its scalability-you can add as many nodes as you need to meet your performance and availability requirements 🏗️.
🔹 Monitoring SHIR Performance: Keeping an Eye on Health 👁️
Once you’ve set up the multi-node environment, it’s crucial to monitor the performance of each node. Luckily, Azure Data Factory provides built-in monitoring tools. Here’s what you should watch:
Node Health Status: Check the status of each node under the SHIR settings. Both nodes should be marked as Healthy 💚.
Performance Metrics: View detailed CPU usage, memory consumption, and data transfer statistics for each node in the Monitoring section 📊.
Alerts: Set up alerts for when one of the nodes becomes unhealthy or stops responding 🚨. This will give you immediate notifications if something goes wrong.
🔹 Don’t Forget to Subscribe and Like! 👍🔔
Thanks for watching! If you found this guide helpful, don’t forget to like this video and subscribe to the channel for more in-depth Azure Data Factory tutorials. Hit the bell icon to get notified whenever we upload new content. Let’s build more reliable, scalable, and high-performing data pipelines together! 🚀
Негізгі бет Ғылым және технология 🏢Azure Data Factory Series: Boosting SHIR Reliability with Multi-Node Setup🏢
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