Azure Functions vs AWS Lambda - A Comparison of Serverless Computing Platforms
Serverless computing has taken the IT world by storm, providing a new paradigm for application development that abstracts developers from server management and infrastructure scaling. Two of the biggest players in the serverless computing space are Azure Functions and AWS Lambda. In this post, we will compare and contrast the two platforms, looking at different aspects such as pricing, performance, and scalability.
Pricing
For pricing, both Azure Functions and AWS Lambda have free tiers that allow users to experiment with the platforms. After the free tier, the pricing varies based on usage.
AWS Lambda charges per request and per duration. The cost per request is $0.20 per 1 million requests, and the cost per duration is $0.00001667 per GB-second. Azure Functions, on the other hand, charges per execution and per GB of data processed. The cost per execution is $0.20 per 1 million executions, and the cost per GB of data processed is $0.16.
Both platforms offer different pricing models for different types of functions such as compute-intensive, memory-intensive, and I/O-intensive functions.
Performance
Performance is another critical aspect to consider when choosing a serverless computing platform. According to a study by The New Stack, AWS Lambda beats Azure Functions in terms of performance. The study shows that AWS Lambda is almost twice faster when invoking cold functions. However, when comparing warm functions, there is no significant difference.
Scalability
Both Azure Functions and AWS Lambda provide automatic scaling based on the number of requests or events. AWS Lambda can scale up to a maximum of 3,000 requests per second and supports concurrent executions of up to 1,000. Azure Functions can scale up to a maximum of 200 instances per plan and support concurrent executions of up to 1,000.
Conclusion
In conclusion, both Azure Functions and AWS Lambda have their strengths and weaknesses. AWS Lambda is faster when invoking cold functions, while Azure Functions are more cost-effective for memory-intensive and I/O-intensive functions. Both platforms provide automatic scaling and support for different pricing models.
Whichever platform you choose, it is essential to consider your specific needs and workload to make an informed decision.
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