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
In a previous topic we covered the Asynchronous Messaging architectural pattern, its advantages and some high-level examples.
Pub/Sub is one way of implementating this type of architecture, and now we are going to cover it more in depth.
Pub/Sub (or Publish/Subscribe) pattern is a way for multiple services to communicate with eachother by publishing messages to a topic, which are then distributed to subscribers of that topic.
Differently than a Message Queue, each topic can have multiple subscribers (or consumers, as it would be called in a Queue model).
Another difference is that messages published to a topic are delivered immediately to all subscribers. As a result, Pub/Sub does not offer many options in terms of message delivery.
The Pub/Sub model allows for one message to be delivered to multiple subscribers. Each of them can perform a different task in parallel.
This pattern can also prove to be a good solution for controlling data processing workflows, as well as for implementing a Fan-Out strategy to conquer larger tasks.
Since topics will notify subscribers when new messages come in, there is no need to continuouslly poll the topic and check for new data. This can save resources and speed up processing of tasks.
It is easy to add new subscribers to an existing topic. New jobs can be performed for the same types of messages without Publishers having to control a list of destinations.
Most Pub/Sub systems will provide multiple protocols to deliver messages. These are some of the protocols commonly available:
Pub/Sub systems usually provide a way for subscribers to filter messages that are relevant to them. This can save resources and also increases flexibility for how messages are distributed across a set of compute services.
Pub/Sub can be easily be deployed in any project by leveraging modern cloud services. AWS, for example, offers SNS, a serverless Pub/Sub system, fully managed by their team.
This releases teams to work on aspects of the software that are really going to differentiate it in the market. Another benefit of using a managed service is faster time-to-market.
Nonetheless, for larger teams with access to advanced DevOps skills and enough financial resources, there are also great open source projects, so that development teams don’t have to reinvent the wheel.
Some options are:
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