The latest News and Information on Serverless Monitoring, Management, Development and related cloud technologies.

Ensure First Come First Server using Azure Service Bus

One of the patterns easily supported by the Azure Service Bus is the first-in-first-out (FIFO) pattern, which isn’t supported in the other queue service – Azure Storage Queues. To realise FIFO with the Azure Service Bus is to use sessions. Any service can create a session when sending a message to a queue or topic by setting the SessionId property. Subsequently, the session comes into existence when the queue or topic is session aware, which means you have specified ‘Enable session’ when creating the queue or topic.

Why you need to build globally distributed applications

Today's users of web and mobile applications and services expect fast and outstanding experiences. Delivering successful web services and applications means meeting these baseline expectations: In this blog post, we dive into why these three goals are vital to modern web applications and services. Then, we will look at how building global and distributed architectures achieve these goals.


Benchmark Your Serverless Database with Thundra

Every millisecond costs you in serverless functions. The visible cost is the one that cloud providers charge. The hidden one is when your customers are unhappy with the performance of your application or website. While performance monitoring is a must for modern applications, it may require a high level of effort to implement correct and useful monitoring. Monitoring tools save a life here. We will use Thundra’s APM to measure the latency of the two serverless databases in this article.


Tracing AWS Lambdas with OpenTelemetry and Elastic Observability

Open Telemetry represents an effort to combine distributed tracing, metrics and logging into a single set of system components and language-specific libraries. Recently, OpenTelemetry became a CNCF incubating project, but it already enjoys quite a significant community and vendor support. OpenTelemetry defines itself as “an observability framework for cloud-native software”, although it should be able to cover more than what we know as “cloud-native software”.


Not on MY Servers

Picture this: you run a development organization for a small startup. Or a large corporation. You’ve had to make some decisions that, while expedient, aren’t necessarily the most elegant. Time is money and money is time. You need to ship product fast. You have solid architectural standards but the tyranny of the urgent has upended some of your good intentions. This is our story.


Hitchhiker's guide to Prometheus (Part 2)

In Part II (Part I is here) of our “Hitchhiker’s Guide to Prometheus,” we are going to continue with the overview of this powerful monitoring solution for cloud-native applications. In particular, we’ll walk you through configuring Prometheus for scraping exporter metrics and custom application metrics, using the Prometheus remote write API, and discuss some best practices for operating Prometheus in production. Let’s get started!


Serverless observability and real-time debugging with Dashbird

Systems run into problems all the time. To keep things running smoothly, we need to have an error monitoring and logging system to help us discover and resolve whatever issue that may arise as soon as possible. The bigger the system the more challenging it becomes to monitor it and pinpoint the issue. And with serverless systems with 100s of services running concurrently, monitoring and troubleshooting are even more challenging tasks.