Demystifying Serverless Computing: The Essential AWS Lambda Handbook

Welcome friend! I‘m thrilled you‘re keen on understanding serverless computing with AWS Lambda. By end of this handbook journey, complex concepts like functions, triggers, and container orchestration will feel clear as day. I‘ll explain how Lambda can save boatloads of cost over traditional servers using real customer examples. Fasten your seatbelts for tangible serverless enlightenment!

Serverless Computing 101

Before digging into Lambda, we need solid foundations on the serverless computing model. The key premise is that your code runs in ephemeral containers on-demand without needing to explicitly provision infrastructure. The cloud provider handles all the undifferentiated heavy lifting of capacity provisioning, scaling, patching, config management automatically allowing you to focus on writing amazing code.

Some principles of serverless:

• No need to manage servers at all
• Runs code on-demand in stateless containers
• Auto-scales seamlessly based on usage
• Usage based billing second/ms precision
• Event-driven actions from data sources

With this context, AWS Lambda emerges as the seminal implementation bringing serverless concepts into mainstream. Let‘s dissect Lambda and see what makes it tick!

AWS Lambda Deep Dive

Lambda allows running code in response to variety of event triggers without thinking about servers at all. The essential pieces are:

Functions – Self-contained blocks of code doing actual work

Triggers – Event sources like S3/SNS invoking functions

Services – Integrations with AWS services through triggers

This Function-as-a-Service (FaaS) model radically shifts server provisioning, capacity planning, and infrastructure management to AWS. You simply write the functions containing business logic while Lambda runs the show orchestrating everything behind curtains.

Here is quick peek at Lambda architecture:

Lambda functions execute in response to triggers while integrations handle services plumbing

Now let‘s explore key Lambda capabilities more closely.

Functions In Depth

Functions contain application logic doing actual work. Written in languages like:

• Node.js
• Python
• Java
• C#

Some characteristics:

• Stateless – No affinity between executions
• Ephemeral – Temporary runtime
• Scalable – Run concurrently to match load
• Serverless – AWS manages infrastructure

Here is a comparison of leading Lambda languages:

When getting started, Node.js strikes the right balance across factors like speed, package variety, and async coding approach.

Triggers In Action

Triggers connect data sources to functions, invoking them based on predefined rules. Lambda natively integrates with over 200 AWS event sources including:

• S3 – File uploads, deletes
• SNS, SQS – Messaging
• DynamoDB – Data changes
• API Gateway – HTTP requests

This feeds into an event-driven architecture by reacting to all data changes flowing through pipeline with business logic crunching.

Triggers invoke functions to process data as it moves between services

For example, uploading image files to S3 can trigger Lambda functions for resizing while adding rows in DynamoDB tables can trigger recalculations.

Integrations And Services

Under the hood, Lambda integrates seamlessly with over 200 AWS infrastructure, database, analytics, and messaging services.

Rather than stitching discrete services using custom code, Lambda binds everything together using triggers flowing data across systems.

Some examples are:

• S3, EFS – Storage
• RDS, DynamoDB – Databases
• SQS, SNS – Messaging
• ECS, EKS – Containers
• SageMaker – Machine Learning

This enables building entire architectures on AWS leveraging Lambda as the compute fabric responding to data changes.

Now that you grasp Lambda fundamentals, let‘s examine why it should be preferred over alternatives.

Lambda Benefits Over Containers and Other Serverless

While containers using platforms like Kubernetes and Docker Swarm remain popular, Lambda edges them out in cloud native scenarios:

• No capacity planning pains
• Consistent sub-second scaling
• Fine grained billing up to 1ms increments
• Tight integration with AWS services

Lambda saves up to 72% cloud costs versus containers as per Forrester. Here is a snapshot:

Lambda delivers over 70% savings versus container infrastructure

Among serverless platforms, Lambda remains the undisputed leader in maturity, scale, and ecosystem breadth. Google Cloud Functions comes closest but lags in:

• Number of natively supported events
• Depth of AWS services integrations
• Tooling ecosystem maturity

For cloud workloads already on AWS, Lambda accelerates development velocity while slashing TCO.

Now that benefits are clear, how does pricing work and what optimizations exist?

Lambda Pricing Demystified

Lambda follows a simple pay-per-use model based on number of requests and compute time:

• First 1M requests per month are free
• $0.20 per 1 million requests thereafter
• Compute time metered in 1ms increments
• Price varies based on allocated memory

There is no charge when code is not running. Also free tier covers hobby workloads nicely.

Add-ons like provisioned capacity and destinations offer further savings:

• Provisioned capacity discounts for steady-state production workloads
• Destinations allow sending data between services without code overheads

Watch out for memory size, as increasing incrementally jumps pricing tiers. Right size based on usage profiling.

You can analyze spend by service using cost allocation tags and reports. Also estimate monthly costs using the pricing calculator.

Understanding the pay-as-you-go mechanics is essential for keeping cloud bills reasonable.

Now that basics are covered, let‘s peek at the end-to-end serverless app development lifecycle.

Building Serverless Applications

While architecting serverless applications follows similar principles of modular design, the implementation workflow differs:

Serverless shifts left on infrastructure allowing focus on writing business logic

Here are key phases:

• Design – Decompose app into functions triggered by data sources. Modular.
• Code – Write code for functions leveraging languages like Node.js and Python
• Build – Compile into deployment artifacts and store in source control
• Deploy – Infrastructure-as-code tools deploy stack automatically
• Operate – Monitor metrics, logs, traces to optimize

Notice how provisioning moves left allowing developers to concentrate on writing killer functions. Infra lives as code templates getting deployed automatically.

Let‘s explore the operate phase more as optimizing performance is vital.

Monitoring, Logging, And Tracing

Observability is an operational cornerstone for serverless apps to maintain resiliency and efficiency.

Key techniques:

• Metrics: Surface utilization stats using CloudWatch
• Logging: Insights into executions via CloudWatch Logs
• Tracing: Map complete request lifecycles across services with X-Ray

Setting up robust monitoring by piping logs into tools like Datadog and Grafana illuminates where to tune functions.

This observability completes the CI/CD pipeline for shipping robust serverless applications faster.

Now over to you my friend! We covered a lot of terrain in this Lambda journey – from serverless tenets, function internals, event triggers, and operating best practices.

Next Steps

You‘re now equipped with comprehensive mental models for building on serverless paradigm with AWS Lambda.

Some parting thoughts on next steps:

• Start evaluating use cases like data pipelines, mobile backends that can leverage Lambda‘s strengths
• Build a simple Lambda app hooking into S3 or DynamoDB to cement learning
• Determine if current workloads can benefit from pay-per-execution savings model
• Structure serverless migration leveraging skills of developers already on board
• Instrument monitoring early as apps grow to optimize performance and efficiency

That wraps our guide! I hope you feel empowered to architect the next generation of resilient, agile serverless applications running on AWS Lambda. Per aspera ad astra! (Through hardships to the stars)