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
Serverless computing has numerous advantages over classical server-centric infrastructure. Developers are usually able to release products faster, benefit from inherent scaling and reduce infrastructure costs. Serverless also requires less know-how of infrastructure management and is easier to get started with.
Benefits of serverless are associated with on-demand functionality, pay-as-you-go pricing model and faster time to market.
With serverless, developers spend less time provisioning, scaling and managing infrastructure, freeing up time to develop value-added business logic. On top of that, function code is often easier and faster to write since it’s concise and should be designed to do only one thing at a time.
Serverless infrastructures scale up and down based on demand for specific functions of the system. For developers, this means less problems and a smoother experience when a product or an application suddenly becomes very popular. Usually cloud-providers set limits for maximum concurrency to protect developers from runaway costs but those limits can be changed and revoked on request.
Developers are only charged by the amount of compute and resources they end up using. In case the system is idle, no cost is associated. In addition, AWS provides a generous free tier of 1M Lambda function requests per month, not to mention other services.
Serverless ecosystem features building blocks for common functionalities like databases (DynamoDB, Aurora), file storage (S3), API (API Gateway) and user management (AWS Cognito), among others. This simplifies getting off the ground at first and also increases the stability of system because those services are built and maintained at the highest quality.
Serverless can be used for a wide variety of use cases, including batch processing, stream processing, web applications, mobile applications, IoT (internet of things), and ETL (extract-transform-load).
One of the most common use cases for serverless tends to be building backend APIs that service web and mobile applications. Serverless APIs are generally easy to build and manage and work well in fluctuating load scenarios.
The event-driven nature of serverless is well suited for data processing. Lambda functions can be assigned to consume events from data streams or set as workers to process tasks in bulk. Another great example why pay-per-use billing model is attractive, although at high loads, compute can be more expensive with serverless.
Devices that connect to internet to read or write data are an excellent use case for serverless. Services like Alexa and home appliances like iRobot are well-known serverless users. Serverless is also seeing a lot of adoption in home automation and other custom-built solutions.
Lambda is also well suited for automating cloud tasks like backing up databases, changing condigurations periodically and for taking care of periodical jobs that don’t require a server constantly running.
Although above we listed the most common use cases and the strongest advantages of serverless computing, many other use cases and benefits exist. Theoretically anything is possible to build on serverless.
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End-to-end observability and real-time error tracking for AWS applications.