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Answer: Implement a cache mechanism such as Memcached or Redis to minimize datastore reads.
Implementing a cache mechanism like Memcached or Redis is the correct approach. It directly reduces datastore reads, thereby lowering latency during peak hours. Automatic scaling is not an option for the local development server, manual scaling is inefficient due to the need for constant monitoring, and restarting the service via cron jobs does not address the root cause of latency issues.
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As a DevOps Engineer, you're tasked with optimizing a service on Google App Engine's local development server to ensure it responds within 500 ms, especially during peak hours when latency increases. What strategy should you implement for performance optimization?
A
Configure a cron job to restart the service every 15 minutes to ensure efficiency.
B
Enable automatic scaling, setting minimum and maximum instances with appropriate latency targets.
C
Implement a cache mechanism such as Memcached or Redis to minimize datastore reads.
D
Use manual scaling to adjust instance numbers during peak and off-peak hours.
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