
The best part of AWS Lambda is that there’s essentially zero server management. Not having to patch OS versions or manage clusters lets our engineering team focus fully on writing and improving code instead of dealing with infrastructure overhead. The event-driven model also feels seamless—triggering functions from S3 uploads, DynamoDB changes, or API Gateway requests simply works as expected. On top of that, the scaling is impressive: whether we see 10 requests or 10,000, Lambda handles the concurrency without us needing to tweak a single scaling policy. Análise coletada por e hospedada no G2.com.
The “Cold Start” issue is still a factor, particularly for functions written in Java or .NET, and it can add slight latency when requests are infrequent. In addition, the 15-minute execution limit means it isn’t a great fit for long-running or heavy data-processing tasks. With these constraints in mind, you really have to be intentional about how you design and architect your workflows so everything stays within the guardrails. Análise coletada por e hospedada no G2.com.
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