AWS Lambda

Website

aws.amazon.com

$ Details

Categories

#Cloud Computing #Cloud Hosting #Business & Commerce #Object Storage

How to GraphQL

Website

howtographql.com

$ Details

Categories

#GraphQL #APIs #Realtime Backend / API #Digital Drawing And Painting

AWS Lambda features and specs

• Scalability
  AWS Lambda automatically scales your application by running your code in response to each trigger. This means no manual intervention is required to handle varying levels of traffic.
• Cost-effectiveness
  You only pay for the compute time you consume. Billing is metered in increments of 100 milliseconds and you are not charged when your code is not running.
• Reduced Operations Overhead
  AWS Lambda abstracts the infrastructure management layer, so there is no need to manage or provision servers. This allows you to focus more on writing code for your applications.
• Flexibility
  Supports multiple programming languages such as Python, Node.js, Ruby, Java, Go, and .NET, which allows you to use the language you are most comfortable with.
• Integration with Other AWS Services
  Seamlessly integrates with many other AWS services such as S3, DynamoDB, RDS, SNS, and more, making it versatile and highly functional.
• Automatic Scaling and Load Balancing
  Handles thousands of concurrent requests without managing the scaling yourself, making it suitable for applications requiring high availability and reliability.

Possible disadvantages of AWS Lambda

• Cold Start Latency
  The first request to a Lambda function after it has been idle for a certain period can take longer to execute. This is referred to as a 'cold start' and can impact performance.
• Resource Limits
  Lambda has defined limits, such as a maximum execution timeout of 15 minutes, memory allocation ranging from 128 MB to 10,240 MB, and temporary storage up to 512 MB.
• Vendor Lock-in
  Using AWS Lambda ties you into the AWS ecosystem, making it difficult to migrate to another cloud provider or an on-premises solution without significant modifications to your application.
• Complexity of Debugging
  Debugging and monitoring distributed, serverless applications can be more complex compared to traditional applications due to the lack of direct access to the underlying infrastructure.
• Cold Start Issues with VPC
  When Lambda functions are configured to access resources within a Virtual Private Cloud (VPC), the cold start latency can be exacerbated due to additional VPC networking overhead.
• Limited Execution Control
  AWS Lambda is designed for stateless, short-running tasks and may not be suitable for long-running processes or tasks requiring complex orchestration.

How to GraphQL features and specs

• Comprehensive Resource
  How to GraphQL provides a thorough introduction and deep dive into GraphQL, covering a wide range of topics from basic concepts to advanced usage, making it a great resource for both beginners and experienced developers.
• Interactive Tutorials
  The platform offers interactive tutorials that allow users to practice and experiment with GraphQL queries and mutations directly in a sandbox environment, enhancing the learning experience.
• Multi-language Support
  How to GraphQL offers tutorials in multiple programming languages, such as JavaScript, Python, and Ruby, allowing developers to learn in the language they are most comfortable with.
• Community Contributions
  Being open-source, it allows contributions from the community, which helps keep the content up-to-date with current best practices and emerging tools.
• Free Access
  All the educational content on How to GraphQL is freely accessible, providing valuable learning resources to developers without any financial barriers.

Possible disadvantages of How to GraphQL

• Steep Learning Curve for Beginners
  While comprehensive, the sheer amount of information and technical depth may be overwhelming for absolute beginners who are not familiar with API design and development.
• Varied Content Quality
  Due to its open-source nature with community contributions, the quality and depth of articles and tutorials can vary, possibly leading to inconsistencies or gaps in knowledge.
• Limited Real-world Use Cases
  The tutorials and examples sometimes lack real-world application and business context, which could make it challenging for learners to see how GraphQL fits into a larger system architecture.
• Dependence on External Tools
  Some tutorials rely heavily on external tools or libraries that may distract from understanding the core concepts of GraphQL itself, making it harder for learners to grasp fundamentals without those tools.

AWS Lambda Vs EC2 | Serverless Vs EC2 | EC2 Alternatives

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