All-in-one serverless DevOps platform.
Full-stack visibility across the entire stack.
Detect and resolve incidents 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
There are a lot of strong options for picking an APIGateway provider and while they vary in terms of what they offer, how easy they are to implement or how much they cost, they do have one thing in common. They are the driving force behind your application, that thing that carefully choreographs all the interactions between the front end and the backend microservices.
Since Amazon is already the leading cloud provider it stands to reason that they would have one of the most popular API Gateway solutions called, well, API Gateway. It’s a fully managed serviced that can be deployed with little to no effort from your AWS Dashboard and if you are using Lambda or EC2 in your application, you will have the option of deploying in the same region, reducing latency considerably.
Similar to Amazon’s API gateway, Microsoft has it’s own API management platform that just like AWS API Gateway works best with other services from Azure like Azure Functions. It’s a great tool for streamlining your work across hybrid or multi could environments while keeping all the management under one roof.
It’s by far the oldest Api management service provider, founded in 2004 and aquired in 2016 by Google. Apigee has a complicated architecture, compared to the other options listed here requering a highly complex setup that you’ll be managing yourself. While complicted to install and set up, Apigee has a really strong following among Fortune500 companies running hybrid applications.
Kong is a cloud-native, fast, scalable, and distributed Microservice Abstraction Layer (also known as an API Gateway, API Middleware or in some cases Service Mesh). Made available as an open-source project in 2015, its core values are high performance and extensibility.
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End-to-end observability and real-time error tracking for AWS applications.