Amazon Web Services Lambda

Website

docs.aws.amazon.com

$ Details

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Categories

#Development #Cloud Computing #VPS #Cloud Infrastructure

Akka

Website

akka.io

$ Details

Categories

#Web And Application Servers #Data Integration #Monitoring Tools #Stream Processing

Amazon Web Services Lambda features and specs

• Scalability
  AWS Lambda automatically scales your application by running your code in response to each trigger, handling scaling from a few requests per day to thousands per second.
• Cost Efficiency
  Lambda charges you only for the compute time you consume, without the need to pay for idle server time, which helps optimize cost efficiency.
• No Server Management
  You don't have to manage any servers or infrastructure, allowing you to focus on writing code and developing functionality rather than maintaining hardware.
• Event-driven Model
  Lambda integrates seamlessly with other AWS services and can be triggered using AWS events, making it highly suitable for building event-driven and serverless architectures.
• Flexible Scaling and Processing
  AWS Lambda provides flexibility in resource allocation, allowing you to adjust memory and execution timings to optimize performance for different workloads.

Possible disadvantages of Amazon Web Services Lambda

• Cold Start Latency
  The first invocation of a Lambda function can experience a delay known as 'cold start,' which can affect applications sensitive to latency.
• Execution Timeout
  Lambda functions have a maximum execution timeout of 15 minutes, which may not be suitable for long-running processes or tasks.
• Resource Limitations
  Lambda has limitations on memory, disk space, and other resources, which can restrict the functions it can perform depending on application requirements.
• Vendor Lock-In
  Using AWS Lambda heavily can lead to vendor lock-in, making it challenging to migrate to different platforms without significant re-architecting.
• Complexity in Large Systems
  For large systems with numerous functions and dependencies, managing and orchestrating Lambda functions can become complex and challenging.

Akka features and specs

• Scalability
  Akka is designed to handle high concurrency and provides excellent scalability by leveraging the actor model, enabling developers to build distributed systems that can efficiently scale up or out across multiple nodes.
• Resilience
  Akka promotes building systems that are resilient to failures, using features like supervision strategies and self-healing, to automatically recover from errors and maintain system stability and uptime.
• Concurrency
  By using the actor model, Akka facilitates easier handling of concurrency, allowing developers to work with asynchronous and non-blocking message-driven communication that reduces complexities associated with multithreaded programming.
• Flexibility
  Akka integrates with a broad ecosystem of tools and technologies and can be easily used with various JVM-based languages such as Scala and Java, providing flexibility in designing and implementing solutions.
• Event-driven Architecture
  Akka supports building reactive, event-driven applications, which are responsive, maintainable, and adaptable to changing demands and requirements.

Possible disadvantages of Akka

• Steep Learning Curve
  The actor model and the associated paradigms in Akka present a steep learning curve for developers who are accustomed to traditional object-oriented or procedural programming models.
• Debugging Complexity
  Debugging in an actor-based system can be more challenging compared to traditional systems, due to the asynchronous nature of message passing and lack of a global state.
• Overhead
  There can be additional overhead associated with context switching and message passing between actors, which might impact performance in scenarios with extremely high-frequency messaging.
• Integration Challenges
  Integrating Akka with existing systems or libraries that are not designed for an actor-based model can pose challenges, requiring developers to adapt or wrap existing codebases.
• Tooling and Ecosystem
  While the Akka ecosystem is growing, it still lacks the extensive tooling support found in more traditional frameworks, making certain tasks like monitoring and tracing more cumbersome.

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