Operations | Monitoring | ITSM | DevOps | Cloud

When we set out to trace applications running outside of AWS Lambda, there was little doubt in our minds that building on top OpenTelemetry was by far the best course of action. There are many reasons for this, but chiefly, it is a question of coverage. At its most fundamental level, achieving coverage requires as-wide-as-possible support for technologies, and interoperability among instrumentations.

There’s plenty of loaded terminology and buzzword bingo when it comes to the latest advances in cloud application delivery. Especially when it comes to multi-cloud – which should merely mean multiple cloud instances when modern cloud applications really leverage multiple hybrid IT operating models, atop both existing business silos and newer microservices application workloads.

Business leaders frequently need to make decisions that could impact the entire future of a company. Armed with pages of data and financial reports, many executives choose to slash costs, double efforts on certain products over others, or otherwise forge ahead with major decisions about cloud usage, spending, and overall business strategy. Great choices could mean huge profits, but unwise choices could spell doom for the business as a whole.

As Kubernetes monitoring continues to standardize on Prometheus as a form factor, more and more developers are becoming familiar with Prometheus’ built-in query language, PromQL. Besides being bundled with Prometheus, PromQL is popular for being a simple yet expressive language for querying time series data. It’s been fully adopted by the community, with lots of great query repositories, sample playbooks, and trainings for PromQL available online.

Check our September 2022 health report on the top most popular cloud providers. We analyze the health of the cloud providers based on the number of outages and problems during the month. The source of the data is made available by the cloud providers themselves via their status page. We normalize it and use it to generate the report.

Azure Container Apps is a serverless platform that enables you to deploy containerized applications and microservices—regardless of their code or framework—without managing any underlying cloud infrastructure or orchestrators. By using serverless containers, Azure Container Apps can automatically scale based on HTTP requests or events supported by Kubernetes event-driven autoscaling (KEDA) in order to accommodate peak demand and meet your budgeting goals.

Continuous integration (CI) demands continous testing: shifting left helps prevent faulty code from spreading, which is one of the core aims of CI. Datadog’s new Azure DevOps extension enables you to seamlessly incorporate integration and end-to-end tests into existing CI/CD workflows on Azure Pipelines, a dedicated CI/CD service that automatically runs builds, performs tests, and deploys your services and applications via cloud-hosted pipelines.

Virtual Machines (VMs) are virtual computers with dedicated amounts of RAM, CPU power, and storage borrowed from a physical host computer. A Virtual Machine is a computer file, typically an image, that acts like a real computer. A Virtual Machine can have any operating system that runs in a window as a separate computing environment. Users can choose between the Linux distribution or Windows Server in the operating system.