Jun 30, 2021 · 9 min read
Sending messages reliably and quickly between services is a core requirement for most distributed systems. Apache Kafka is a popular, durable message broker that enables applications to process, persist and re-process streamed data with low latency, high throughput, and fault tolerance. If you are a beginner in Kafka, please consider reading the articles in my Apache Kafka series to get up to speed in no time. One of my Twitter friends, among others, reached out to me to understand how to implement retries in Kafka.
Apr 11, 2021 · 10 min read
In this series: Development environment and Event producer Event consumer Azure Event Hubs integration (this article) Azure Event Hubs is a horizontally scalable event ingestion service capable of receiving and processing millions of events per second. It supports Apache Kafka Producer and Consumer API that you can use as an alternative to running a self-managed Apache Kafka cluster. Now you can integrate the Kafka ecosystem applications such as Kafdrop and many others with Event Hubs.
Apr 04, 2021 · 8 min read
In this series: Development environment and Event producer Event consumer (this article) Azure Event Hubs integration Let’s carry our discussion forward and implement a consumer of the events published by the Employee service to the leave-applications Kafka topic. We will extend the application that we developed earlier to add two new services to demonstrate how Kafka consumers work: Manager service and Result reader service. Source Code The complete source code of the application and other artifacts is available in my GitHub repository.
Mar 29, 2021 · 12 min read
In this series: Development environment and Event producer (this article) Event consumer Azure Event Hubs integration An event-driven architecture utilizes events to trigger and communicate between microservices. An event is a change in the service’s state, such as an item being added to the shopping cart. When an event occurs, the service produces an event notification which is a packet of information about the event. The architecture consists of an event producer, an event router, and an event consumer.
Feb 05, 2021 · 12 min read
Many times, your application needs to run tasks or jobs on regular intervals. Scheduling might be necessary when polling an API every night, or dispatching emails with reports each week. And sometimes you may find that you need to trigger a host of tasks across multi- or hybrid-cloud and need a way to run these tasks in a reliable, cross-cloud manner. In this article, let’s look at one way to do that using a Heroku dyno for our task, and Microsoft Azure Logic Apps as our scheduler service.
Jan 14, 2021 · 11 min read
Web applications are optimized for throughput and latency to service a high number of HTTP requests as quickly as possible. For improved performance, web applications defer the CPU intensive, IO intensive, time-intensive, and scheduled processing workloads to background jobs that run independently of the user interface. These background jobs must function without intervention from the user interface and should not block a synchronous user and system interaction. Offloading slow and compute or memory-intensive activity to background jobs improves web applications' performance and throughput.
Jan 02, 2021 · 10 min read
In many event-driven applications, preserving the sequence of events is essential. For example, an event-driven eCommerce application might have the following states, transitions, and events. A user adds N items to the basket. This action generates the item added event. The user checks out the basket. This action generates the basket checked out event. The user pays for the items. This action generates the payment made event. Inventory decrements the count of available items by N.
Sep 06, 2020 · 8 min read
In this lab, we will create an Azure Logic App that monitors Twitter, analyzes the sentiment of customer tweets with Text Analytics v2 service, and creates incidents in Pager Duty. PagerDuty is an incident management platform that provides reliable notifications, automatic escalations, on-call scheduling, and other functionality to help teams detect and fix problems quickly. This application can help customer service agents react swiftly to customer complaints and avoid brand reputation damages.
Apr 12, 2018 · 10 min read
According to the Reactive Manifesto, a reactive system should have some essential characteristics which include: responsiveness, resiliency, elasticity, and being message-driven. Out of all the aspects, the most significant differentiating factor of Reactive Microservices from others is its characteristic of being message-driven. Using messages as the glue that holds your Microservices application together, you can design systems that isolated. High degree of isolation also helps enhance the scalability of a system which is an essential aspect of a Microservices application.