Articles

Top Microservices Testing Tools Testers Should Know About

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Microservices have crafted highly flexible and adaptable IT infrastructures. Microservices is a unique software development approach that concentrates on creating single-function modules that work jointly to execute the same tasks. It enables you to alter only one service, without modifying the rest of the infrastructure. In simple words, one can easily deploy and change every service without affecting the functional facets of other applications or services. Instead of following an old monolithic architecture (sole app with manifold functions), testers and developers use this microservice approach to build independent modules for every function.

However, the microservice architecture can also make an app extra complicated, particularly when we add several functionalities. Likewise, testing the combined functionality of numerous services is a lot more complicated due to the distributed nature of the app. As microservices follow a dissimilar architecture, we also require an exceptional strategy for testing microservices. In this article, we will explore different tools for testing microservice applications. Testing microservices can assist us in eradicating several issues by avoiding a domino effect. 

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Defining Event-Driven Architectures: AsyncAPI

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In this article, I am going to be talking about how we can define your event-driven architectures using the AsyncAPI definition.

Introduction

A while ago, I published an article about how you can document REST APIs using Open API 3 specification. This was for synchronous APIs.

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Open Source Solution for Building Invincible Apps

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Introduction

I left Microsoft after 19 years, where I led teams that built system software for highly scalable cloud applications. This included leading development of the Microsoft Orleans framework from its inception at Microsoft Research until it became one of the most successful open-source projects within the .NET ecosystem. Orleans powers a number of large-scale Microsoft systems such as Xbox Game Services, Skype, Azure IoT, Azure ML, Azure Active Directory, and many more cloud services outside Microsoft. So if you’ve ever played online multiplayer games like Halo or Call of Duty, our team built much of the underlying infrastructure that supports it.

When I originally joined Orleans, cloud computing was still in its infancy. We had a 10,000-foot vision and not a single line of actual code. We needed to reimagine how cloud-scale applications should be coded because, at the time, available and high-performance scalable systems were only achievable by experts. And while everyone knew the cloud was coming, we had no idea how to build applications in a way that ensured they would be accessible and productive for millions of software engineers.

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Distributed Tracing in ASP.NET Core With Jaeger and Tye, Part 2: Project Tye

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In This Series:

  1. Distributed Tracing With Jaeger
  2. Simplifying the Setup With Tye (this article)

Tye is an experimental dotnet tool from Microsoft that aims to make developing, testing, and deploying microservices easier. Tye’s opinionated nature greatly simplifies the lifecycle of development and deployment of .NET Core microservices.

To understand the benefits of Tye, let’s enumerate the steps involved in the development and deployment of the DCalculator application to Kubernetes:

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Getting started with Java Serverless Functions using Quarkus and AWS Lambda

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The serverless journey started with functions – small snippets of code running on-demand and a short period in Figure 1.  AWS Lambda in the “1.0” phase made this paradigm very popular, but it had its limitations around execution time, protocols, and poor local development experience. 

Since then, developers realized that the same serverless traits and benefits could be applied to microservices and Linux containers. This leads us into what we’re calling the “1.5” phase in Figure 1.  Some serverless containers here completely abstract Kubernetes, delivering the serverless experience through an abstraction layer that sits on top of it, like Knative.

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Kumologica: Handling Data in Different Formats [Videos]

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Photo by Oskar Yildiz on Unsplash.

When building integration components, it’s almost a given that we will have to process data in different formats like JSON, XML, YAML, etc. It’s imperative that any integration product should have very good support for handling these data formats. This kind of robust support for handling data in different formats makes the product flexible to be adapted to different use cases.

In this article, we will look into the support provided by Kumologica for handling the data in these different formats.

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App Modernization + Hybrid Cloud Architectures With Apache Kafka [Video]

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Hybrid cloud architectures are the new black for most companies. A cloud-first is obvious for many, but legacy infrastructure must be maintained, integrated, and (maybe) replaced over time. Event Streaming with the Apache Kafka ecosystem is a perfect technology for building hybrid replication in real-time at scale.

App Modernization and Streaming Replication With Apache Kafka at Bayer

Most enterprises require a reliable and scalable integration between legacy systems such as IBM Mainframe, Oracle, SAP ERP, and modern cloud-native applications like Snowflake, MongoDB Atlas, or AWS Lambda.

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How to Debug Microservices in the Cloud

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The growth in information architecture has urged many IT technologies to adopt cloud services and grow over time. Microservices have been the frontrunner in this regard and have grown exponentially in their popularity for designing diverse applications to be independently deployable services.

Trivia: In a survey by O’Reilly, over 50% of respondents said that more than 50% of new development in their organisation utilise microservices.

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Business optimisation architecture – Example planning optimisation

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business optimisationIn my previous article from this series I shared the logical view of the business optimisation use case for retail stores.

The process was laid out how I’ve approached the use case and how portfolio solutions are the base for researching a generic architectural blueprint.

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Scale to Zero With Kubernetes

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In the era of web-scale, every organization is looking to scale its applications on-demand, while minimizing infrastructure expenditure. Cloud-native applications, such as microservices are designed and implemented with scale in mind and Kubernetes provides the platform capabilities for dynamic deployment, scaling, and management. 

Autoscaling and scale to zero is a critical functional requirement for all serverless platforms as well as platform-as-a-service (PaaS) solution providers because it helps to minimize infrastructure costs.

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