Operations | Monitoring | ITSM | DevOps | Cloud

Microsoft Azure provides a completely managed event routing service called Azure Event Grid. It allows you to respond to events received from various Azure services and external applications and forward them to different Azure services and endpoints. Azure Event Grid provides a unified way to manage events in Azure with event-driven programming. With Event Grids, you can create event-driven applications in a serverless environment, cutting down costs and performance lags.

Multiple Azure subscriptions are typically managed by a Tenant in an enterprise. Each subscription is tailored to a specific product, project, module, or environment. This article addresses the utilization of Serverless360 for the monitoring and managing these diverse Azure subscriptions.

We’re here to shed a little light on how you can host and configure your multi-app projects on Upsun with a step-by-step guide on how to set up a project on our platform. Enabling your team to focus more on creating incredible user experiences and less on multi-app infrastructure management. As well as a few multi-app development tips along the way. We’re going to look at this through the lens of a customer on the lookout for multi-application hosting with a few specific constraints.

As technology advances and business environments become increasingly competitive, your DevOps team has to continuously improve your product. The challenge is to free up their time so that they can release new product features and improve existing ones. Automating repetitive tasks is one way to accomplish this. Manual approaches also tend to generate or miss errors, slow time to market, and fail to test and monitor system health quickly enough.

Google Cloud Operations, formerly known as Stackdriver, is relatively new to the observability space. That being said, its position in the GCP ecosystem makes the platform a serious contender. Let’s explore some of the key ways in which Google Cloud Operations differs from Coralogix, a strong full-stack observability platform and leader in providing in-stream log analysis for logs, metrics, tracing and security data.

We explain why you should connect the leading two cloud providers, the options available, and which one is right for your business.

We recently moved our infrastructure fully into Google Cloud. Most things went very smoothly, but there was one issue we came across last week that just wouldn’t stop cropping up. What follows is a tale of rabbit holes, red herrings, table flips and (eventually) a very satisfying smoking gun. Grab a cuppa, and strap in. Our journey starts, fittingly, with an incident getting declared... 💥🚨

Ever since its release in September 2014, Kubernetes has been equally powerful and meme-able in the engineering world. For all the magic of its container orchestration and compute resource management, it’s also mysterious and, to many, confounding — especially when it comes time to pay for it. As we’ve written before, migrating to Kubernetes often means losing cost visibility.

Apache Kafka, born at LinkedIn in 2010, has revolutionized real-time data streaming and has become a staple in many enterprise architectures. As it facilitates seamless processing of vast data volumes in distributed ecosystems, the importance of visibility into its operations has risen substantially. In this blog, we’re setting our sights on the step-by-step deployment of a containerized Kafka cluster, accompanied by a Python application to validate its functionality. The cherry on top?

Azure Functions offers a serverless solution that streamlines the development process, minimizes infrastructure overhead, and results in cost savings. The beauty of this approach is that you no longer need to grapple with server deployment and maintenance; the cloud infrastructure automatically furnishes the essential resources to support your applications.