Mainframe and midrange hardware is composed of a family of systems from various vendors (all with a history and goal of high performance, high throughput, and sometimes high availability).These systems were often scale-up and monolithic, meaning they were a single, large frame with multiple processing units, shared memory, and shared storage.
This article demonstrates using Azure Monitor to monitor a serverless application built using Event Hubs and Azure Functions. It discusses useful metrics to monitor, describes how to integrate with Application Insights and capture custom metrics, and provides code samples.
When it comes to infrastructure security, every stakeholder has the same goal: maintain the confidentiality and integrity of their company’s data and systems. Period. Developing and operating in the Cloud provides the opportunity to achieve these goals by being more secure and having greater visibility and governance over your resources and data.
AWS CloudFormation and the AWS Cloud Development Kit ( CDK ) provide scalable and consistent provisioning of AWS resources (for example, compute infrastructure, monitoring tools, databases, and more). We’ve heard from many customers that they’d like to benefit from the same consistency and scalability when provisioning resources from AWS Partner Network (APN) members, third-party vendors, and open-source technologies, regardless of whether they are using CloudFormation templates or have adopted the CDK to define their cloud infrastructure.
This example shows how to establish a development and test environment for SAP NetWeaver in a Windows or Linux environment on Azure. The database used is AnyDB. (AnyDB is the SAP term for any supported DBMS that isn’t SAP HANA.) Because this architecture is designed for non-production environments, it’s deployed with only one virtual machine (VM).
In this post, you’ll learn how to implement an active/active strategy to run your workload and serve requests in two or more distinct sites.
Hospitals and clinical trial sites manage sensitive patient data. They are often required to grant remote access to custom Windows-based applications for patient record review and medical image analysis. This typically requires providing physicians and staff with remote access to on-premises workstations over VPN, with some flavor of remote desktop software.
With the introduction of cloud technology and by extension the rapid emergence of Internet of Things (IoT), the barrier to entry for creating smart building solutions has never been lower. These solutions offer commercial real estate customers potential cost savings and the ability to enhance their tenants’ experience.
Mindful Containers is a fictitious company that is creating containerized microservice applications. They need a fully managed compute environment for deploying and scaling serverless containerized microservices. So, they are considering Cloud Run
Customers operating in hybrid environments today face tremendous challenges with regard to operational management, security/compliance, and monitoring. Systems administrators have to connect, monitor, patch, and automate across multiple Operating Systems (OS), applications, cloud, and on-premises infrastructure.
In this blog, you learn how Amazon Neptune as a graph database, combined with Amazon Elasticsearch Service (Amazon ES) for full text indexing helps you shorten risk analysis processes from weeks to minutes. We give a walk-through of the steps involved in creating this knowledge management solution, which includes natural language processing components.
Amazon Elasticsearch Service (Amazon ES) is a fully managed service that you can use to deploy, secure, and run Elasticsearch cost-effectively at scale. The service provides support for open-source Elasticsearch APIs, managed Kibana , and integration with Logstash and other AWS services.
A multitenant Kubernetes cluster is shared by multiple users and workloads that are commonly referred to as “tenants.” This definition includes Kubernetes clusters that are shared by different teams or divisions within an organization, as well as clusters that are shared by per-customer instances of a software-as-a-service (SaaS) application.
A popular approach in digital transformation scenarios is to see whether existing applications and middleware tiers can run as-is in a hybrid setup where Microsoft Azure serves as the scalable, distributed data platform. This example describes a data-first approach to middleware integration that enables IBM message queues (MQs) running on mainframe or midrange systems to work with Azure services so you can find the best data platform for your workload.
