Azure Functions, Microsoft’s serverless offering, allow cloud software developers to focus on their code and not be concerned with infrastructure or DevOps. Thanks to a slew of built-in integrations, you can use configurations rather than code to send and retrieve messages to various services or be triggered by events in …
Cloud Native Application Architecture and Design best practices are well established. We would like to focus this session on Cloud Native Data, introduce the concept, and get into some detail around relevant Architectural and Design concepts. Traditional data architecture is geared towards data consolidation, multi-tenant environment, and supports a mixed …
This video provides an overview of Google Cloud Spanner, Google mission-critical, relational and scalable application database, which is now publicly available as a managed service on Google Cloud. You’ll learn how Cloud Spanner evolved, how Google uses it internally, and how you can use it for your next project.
Data governance and data locality play a huge role in deciding where to deploy your databases. And with the combination of Cloud Foundry and CumuLogic inside the firewall, you can empower your application teams with the agility and operational maintainability to meet enterprise requirements.
This video provides a retrospective on running MongoDB on Windows Azure for the past 2 years.
MongoDB is an open source NoSQL database. This article from Lynn Langit introduces both MongoDB and Windows Azure, and then explore the technical details and benefits of deploying MongoDB to the Microsoft cloud.
MetricsHub is a monitoring and scalability service for public clouds, allowing companies to continuously gather data from their systems and auto-scale their deployments to optimize service costs. Taking advantage of Cassandra rapid ingestion rates, reliable replication model, and easiness of deployment, Metrics Hub can handle billions of datapoints per day. …
This presentation covers the challenges and solutions Adobe faced when adopting Neo4J as their graph solution, moving it out of the data center and into the cloud, how Neo Technology worked with Adobe to overcome hurdles and evolve the product, and what putting a truly global cluster into production entailed.
