Keynote: Why local development for serverless is an anti-pattern | Gareth McCumskey
It’s been a few weeks since we wrapped up another great edition of the Serverless Architecture Conference but we still remember the amazing talks! One of them was Gareth McCumskey's keynote, “Why local development for serverless is an anti-pattern”, where he argues that in the serverless community, there is no need to waste a lot of time and effort building an environment that is a replica of the cloud.
Cloud Native Serverless Java with Quarkus and GraalVM on AWS Lambda
If you haven't shouted "Bingo" yet, you have only yourself to blame. How can it be possible to use almost all of the bleeding-edge technologies, frameworks and platforms listed above successfully together in a real-world project away from the greenfield and Hello World demos? A field report.
The Battle of the Clouds
Today’s data landscape is overflowing with complex and sophisticated architectures, which can help you dynamically customize your digital ecosystem according to your project requirements and needs. Unfortunately, managing complex cloud architectures can be a difficult task, especially if you are trained to use one cloud vendor and not any of the others. Database as a Service (DBaaS) offerings can help you fill this gap. DBaaS models provide cloud users with managed database offerings. This article reviews DBaaS models offered by the top three cloud vendors—AWS, Azure, and Google Cloud.
With AWS Lambda to Multicloud
In the future, many companies will try to grow their IT infrastructure with the help of the cloud or even move it completely to the cloud. Larger enterprises often call for multicloud. In terms of serverless, there are a few ways to achieve multicloud operation. Using AWS Lambda, a function can be made available and the whole thing can be made cloud-independent with Knative.
Serverless, not Headless!
Serverless architectures are the next step in the evolution of cloud services. The first attempts at walking with them are easy. However, you should know the stumbling blocks in order to be able to avoid them. This article presents the typical challenges with corresponding possible solutions.
Long-Running Workflows as Serverless Functions in Azure
Azure Functions have many features that make your work easier. However, they are less suitable for long-running processes. This is where Durable and Entity Functions can help.
Serverless Java: Reduce Infrastructure Overhead
Java is still the first choice when it comes to software development for business use . However, the development of Java software alone is not enough: machines, operating systems, JREs, application servers, etc. are required for productive use - and large frameworks and libraries are also required as the basis for code functionality. This overhead hurts more the simpler the required functionality is, because it makes development, testing, and operation more difficult. The alternative concept: Serverless.
Serverless Microservices using Azure examples
Why does it have to be "Serverless or Microservices"? It should be "Microservices with Serverless"! Based on some of the generally accepted principles of microservices, we can use serverless architectures and technologies to build highly focused microservices. Let's take a pragmatic and concise approach to building microservices with Azure Functions, Azure Service Bus, Azure Storage, and other services and tools. And it works for almost all software developers: Java, .NET, Node.js, and even Python.
To FaaS or not to FaaS
In times when ever larger amounts of data are processed and the speed of development in IT is - in order to keep up with the competition - becoming increasingly sought after, it is more and more important to be able to react scalably to a growing business volume and to establish a fast development and innovation cycle. This is exactly where serverless can help, as it eliminates much of the complexity of operation and allows you to bring speed to development.
4 Tips for Solving Lambda Performance Issues
AWS Lambda provides serverless computing in the form of functions as a service (FaaS). This means you can leverage on-demand infrastructure without the need for provisioning and hardware maintenance. Overall, Lambda is a great service for real-time data processing and backends. However, to achieve optimal performance you need to do some troubleshooting. In this article, you will learn how to improve cold start performance, implement efficient monitoring and logging, debug functions, and avoid timeouts.