Monitoring platform for keeping systems up and running at all times.
Full stack visibility across the entire stack.
Detect and resolve any incident in record time.
Conform to industry best practices.
Dashbird continuously monitors and analyses your serverless applications to ensure reliability, cost and performance optimisation and alignment with the Well Architected Framework.
What defines a serverless system, main characteristics and how it operates
What are the types of serverless systems for computing, storage, queue processing, etc.
What are the challenges of serverless infrastructures and how to overcome them?
How systems can be reliable and the importance to cloud applications
What is a scalable system and how to handle increasing loads
Making systems easy to operate, manage and evolve
Learn the three basic concepts to build scalable and maintainable applications on serverless backends
The pros and cons of each architecture and insights to choose the best option for your projects
Battle-tested serverless patterns to make sure your cloud architecture is ready to production use
Strategies to compose functions into flexible, scalable and maintainable systems
Achieving loosely-coupled architectures with the asynchronous messaging pattern
Using message queues to manage task processing asynchronously
Asynchronous message and task processing with Pub/Sub
A software pattern to control workflows and state transitions on complex processes
The strategy and practical considerations about AWS physical infrastructure
How cloud resources are identified across the AWS stack
What makes up a Lambda function?
What is AWS Lambda and how it works
Suitable use cases and advantages of using AWS Lambda
How much AWS Lambda costs, pricing model structure and how to save money on Lambda workloads
Learn the main pros/cons of AWS Lambda, and how to solve the FaaS development challenges
Main aspects of the Lambda architecture that impact application development
Quick guide for Lambda applications in Nodejs, Python, Ruby, Java, Go, C# / .NET
Different ways of invoking a Lambda function and integrating to other services
Building fault-tolerant serverless functions with AWS Lambda
Understand how Lambda scales and deals with concurrency
How to use Provisioned Concurrency to reduce function latency and improve overall performance
What are Lambda Layers and how to use them
What are cold starts, why they happen and what to do about them
Understand the Lambda retry mechanism and how functions should be designed
Managing AWS Lambda versions and aliases
How to best allocate resources and improve Lambda performance
What is DynamoDB, how it works and the main concepts of its data model
How much DynamoDB costs and its different pricing models
Query and Scan operations and how to access data on DynamoDB
Alternative indexing methods for flexible data access patterns
How to organize information and leverage DynamoDB features for advanced ways of accessing data
Different models for throughput capacity allocation and optimization in DynamoDB
Comparing NoSQL databases: DynamoDB and Mongo
Comparing managed database services: DynamoDB vs. Mongo Atlas
How does an API gateway work and what are some of the most common usecases
Learn what are the benefits or drawbacks of using APIGateway
Picking the correct one API Gateway service provider can be difficult
Types of possible errors in an AWS Lambda function and how to handle them
Best practices for what to log in an AWS Lambda function
How to log objects and classes from the Lambda application code
Program a proactive alerting system to stay on top of the serverless stack
Developers can invoke an AWS Lambda function through an HTTP API1. AWS also provides SDKs2 that wrap Lambda API endpoints and make it easier to interact with functions.
When a Lambda function is invoked synchronously, it will keep the connection open until the execution is finished. Once it’s done, it returns the response provided by the function’s code (or an error, if that’s the case).
This is the default invocation type for all Lambda functions. Although not necessary, to explicitly invoke a function synchronously, the API consumer provides the InvocationType parameter as RequestResponse.
When you invoke a function asynchronously, Lambda sends the event to a queue. A separate process reads events from the queue and runs your function. When the event is successfully added to the queue, Lambda returns a success message to the client3.
To invoke a function asynchronously, the API client must explicitly specify the InvocationType parameter as Event.
This invocation type will validate the parameter values and verify whether the API client has appropriate permission to invoke the function. It will not actually execute the function code, only carry out a verification and validation process.
Simply specify DryRun as the InvocationType parameter to invoke a function in this mode.
Below is a list of services that integrate with Lambda. They invoke a given function either synchronous or asynchronously, depending on the service.
S3 is a scalable and highly durable storage service by AWS. It an hold from image and video to text and columnar data files.
The main operations in S3 are PUT (save or update an object), GET (retrieve an object), DELETE (remove an object). It can automatically send asynchronous event messages to AWS Lambda whenever an object is stored or deleted, for example4.
Lambda receives an S3 event, which contains basic information about the object. It can then perform whatever task is needed in response to the operation executed against this object.
DynamoDB is a distributed, highly scalable NoSQL database by AWS. By enabling DynamoDB Streams, write operations (insert, update, delete) against a DynamoDB table will be stored in a stream of events. These events can be read by a Lambda function asynchronously to perform any kind of job in response to the database changes5.
To learn more about DynamoDB Streams, please read our page about Operations and Data Access patterns.
SQS is a queue buffer service by AWS. Lambda can poll the queue of events and invoke a given function synchronously6. Messages are read in batches from the queue to improve performance and reduce costs. When the function successfully processes the queue messages, Lambda deletes them from the queue.
Lambda can be used as the backend processing platform to answer REST API requests received by an API Gateway7. Each request method (GET, PUT, POST) can be matched to a different Lambda function or a single function can serve all requests from an endpoint (or a group of endpoints).
API Gateway will invoke Lambda synchronously. Beware that, even though Lambda timeout limit is 15 minutes, API Gateway is limited to 29 seconds8.
Similarly to the API Gateway integration, Lambda can also serve HTTP requests received by an Application Load Balancer (ALB)9. Also as API Gateway, the ALB will invoke the Lambda function synchronously.
ALB does not have a hard timeout limit. Processing time is limited to the Lambda timeout of 15 minutes.
SES is an email sending and receiving service by AWS. When configured to receive messages, it can invoke a Lambda function passing the email received as a parameter10. SES can invoke in both synchronous and asynchronous modes, depending on how the integration is intended to work. Please refer to the AWS documentation for more details11.
CloudFront is a content delivery network (CDN) service by AWS. It serves static content in a performant way distributing and replicating content across hundreds of points-of-interest that are geographically closer to application users.
Lambda@Edge is an integration between CloudFront and Lambda that allows to customize content delivered through the CDN12. This can be used to inspect cookies and customize content returned by CloudFront, or to manipulate headers in the CloudFront HTTP responses, for example.
Amazon Kinesis Data Firehose can automatically transform data received through streams. By integrating with AWS Lambda, it’s possible to implement custom transformation processes13.
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