After scalability and availability: Why predictability is the new standard for modern systems
Blog post from Aerospike
The late 1990s dot-com bubble marked a transformative period in technology, characterized by rapid internet commercialization and speculative ventures, leading to significant advancements in computing architecture. This era necessitated a shift from monolithic to distributed systems to address scalability and availability as online systems demanded more processing power. Fast forward to the current era, artificial intelligence (AI) is driving another technological shift, focusing on predictability as a new challenge in system stability. The AI era introduces complex internal operations that multiply exponentially from single user interactions, necessitating systems that maintain performance despite variable workloads. Traditional optimization strategies are less effective as AI workloads become unpredictable, requiring systems to be inherently designed for consistent performance. Aerospike exemplifies a system built for this new paradigm, emphasizing tightly bounded latency and deterministic behavior under fluctuating conditions, outperforming competitors like ScyllaDB in maintaining stable latency despite workload variations.
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