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Answer: Introduce a second cluster to your existing instance with multi-cluster routing. Set up a live-traffic app profile for your regular workload and a batch-analytics profile for the analytical workload.
The optimal solution involves adding a second cluster with multi-cluster routing and configuring distinct app profiles for live and analytical workloads. This approach offers several advantages: - **Multi-cluster routing** enhances read performance and scalability by distributing read traffic across clusters, minimizing the impact on your live application. - **App profiles** allow precise control over traffic routing, enabling the isolation of analytical queries from live traffic. - The **second cluster** provides the necessary capacity to handle both workloads efficiently. Alternatives are less suitable for various reasons: - **Exporting to GCS** introduces latency, requires consistency maintenance, and can be costly for frequent operations. - **Doubling the cluster size** may lead to overprovisioning and doesn't isolate traffic effectively. - **Single-cluster routing** lacks the scalability and isolation benefits of multi-cluster routing. This strategy ensures high performance, scalability, and cost-efficiency while maintaining the reliability of your real-time application.
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You are managing a real-time application on Google Cloud Bigtable that handles a mix of read and write operations under heavy load. A new requirement has emerged to perform hourly analytical computations across the entire database. Your primary goal is to ensure the reliability of your production application while accommodating the analytical workload. Which approach should you take?
A
Increase the size of your current cluster and run the analytics workload on the expanded cluster.
B
Introduce a second cluster to your existing instance with multi-cluster routing. Set up a live-traffic app profile for your regular workload and a batch-analytics profile for the analytical workload.
C
Transfer a copy of the Bigtable data to Google Cloud Storage (GCS) and execute the hourly analytical job on the exported data.
D
Add a second cluster to your existing instance with single-cluster routing. Configure a live-traffic app profile for your regular workload and a batch-analytics profile for the analytical workload.