By understanding the goal of measuring the consumption by a tenant, you can determine whether the cost allocations need to be approximate or highly precise, which affects the specific tools you can use and the practices you can follow.
By understanding the goal of measuring the consumption by a tenant, you can determine whether the cost allocations need to be approximate or highly precise, which affects the specific tools you can use and the practices you can follow.
DTL helps developers within teams to efficiently self-manage virtual machines (VMs) and PaaS resources without waiting for approvals, providing a worry-free self-service environment.
“Continuing our Advancing Reliability blog series , which highlights key updates and initiatives related to improving the reliability of the Azure platform and services, today we turn our focus to Azure Active Directory (Azure AD).
As we discussed in part 2 of this blog series, if you design your edge computing realistically, your systems may not be connected to the network all the time. But there are a variety of tools you can use to manage those edge deployments effectively, and that can even tie them back into your main environment! In this third blog of the series, we’ll discuss the role of software in edge computing, and Google Cloud’s solutions to this end.
Azure Virtual WAN is a unified hub and spoke-based architecture providing Network-as-a-Service (NaaS) for connectivity, security, and routing using the Microsoft Global Backbone. Customers transforming their networks by migrating to Azure cloud or utilizing hybrid deployments shared between Azure and their traditional data center or on-premises networks, take advantage of Azure Virtual WAN for scalability, ease of deployment, reduced IT costs, low latency, transit functionalities, high performance, and advanced routing
With the increased adoption of critical applications running in the cloud, customers often find themselves revisiting traditional strategies that were adopted for on-premises workloads. When it comes to IBM DB2, one of the first decisions to make is to decide what backup and restore method will be used.
Should disaster strike, business continuity can require more than just periodic data backups. A full recovery that meets the business’s recovery time objectives (RTOs) must also include the infrastructure, operating systems, applications, and configurations used to process their data.
In this article Azure Kubernetes Service (AKS) simplifies deploying a managed Kubernetes cluster in Azure by offloading the operational overhead to Azure. As a hosted Kubernetes service, Azure handles critical tasks, like health monitoring and maintenance.
In process manufacturing, it’s important to fetch real-time data from data historians to support decisions-based analytics. Most manufacturing use cases require real-time data for early identification and mitigation of manufacturing issues.
Large enterprises need to consider many factors when modernizing their existing monitoring solution. Enterprises can achieve centralized monitoring management by using Azure Monitor features. This example scenario illustrates enterprise-level monitoring that uses Azure Monitor.
AWS Resilience Hub is a new service that helps you understand and improve the resiliency of your workloads using AWS Well-Architected best practices. As the lead for the Reliability Pillar of AWS Well-Architected , I am eager to share with you how you can use Resilience Hub to ensure your workload architecture is as reliable as you need.
Many lessons you learn in larger companies aren’t directly applicable to a startup’s first stack. In a product’s initial explore stage, you need to optimize deployment for speed, cost, and optionality. Optionality refers to how fast you can change directions within a given architecture.
In this blog post, we will show how Amenity Analytics improved the continuous integration (CI) pipeline speed by 15x. We hope that this example can help other customers achieve high scalability using AWS Step Functions Express.
Society has long benefited from the power of computing, but the digital era has reached a point where changes in society’s landscape, not performance advances, will play a critical role in determining the next generation of business-altering computing change.