Operations | Monitoring | ITSM | DevOps | Cloud

While the cloud is recognized as more secure than on-premises servers and infrastructures, it does come with the often talked about shared responsibility model. Cloud providers are responsible for security ‘of’ the cloud, while their clients are responsible for security ‘in’ the cloud. It’s ‘differently secure’, rather than the traditionally secure organizations have been used to when working with on-premises environments.

Say hello to the latest arrival in the Azure Integration landscape: Azure API Center, and it’s worth noting that it’s currently in its preview stage!

Success in the cloud continues to be elusive for many organizations. A recent Forbes article describes how financial services firms are struggling to succeed in the cloud, citing Accenture Research that found that only 40% of banks and less than half of insurers fully achieved their expected outcomes from migrating to cloud. Similarly, a 2022 KPMG Technology Survey found that 67% of organizations said they had failed to receive a return on investment in the cloud.

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.