Based on our record, Azure Cosmos DB should be more popular than Azure Container Instances. It has been mentiond 9 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Https://azure.microsoft.com/en-us/products/container-instances and as /u/re-thc posted, GKE Autopilot can be that for Google Cloud. Source: about 1 year ago
Containerize and deploy the application using one of the container delivery services on Azure like App Services, Container Instances, or Kubernetes Services. - Source: dev.to / over 1 year ago
Apache APISIX is an open-source Microservice API gateway and platform designed for managing microservices requests of high availability, fault tolerance, and distributed system. You can install Apache APISIX by the different methods (Docker, Helm, or RPM) and run it in the various public cloud providers because of its cloud-native behavior. In this post, you will learn how easily run Apache APISIX API Gateway in... - Source: dev.to / almost 2 years ago
Yeah datafactory isn’t appropriate for this task. There are custom df tasks you can script up in c# but doesn’t help you here. You have a couple of options but I would suggest azure container instances given your constraints. If you want to orchestrate it using the rest call option in df and long polling then status is the best but you can use logic app as well. ACI is serverless in the sense you maintain no... Source: about 2 years ago
Azure Container Instances may be your best fit: https://azure.microsoft.com/en-us/services/container-instances/. Source: almost 3 years ago
If you are writing the code maybe consider learning Cosmos DB it’s pretty easy to work with and there is a free tier. Also in my experience it’s much faster than a SQL database. Source: 12 months ago
Sometimes you don’t need an entire Java-based microservice. You can build serverless APIs with the help of Azure Functions. For example, Azure functions have a bunch of built-in connectors like Azure Event Hubs to process event-driven Java code and send the data to Azure Cosmos DB in real-time. FedEx and UBS projects are great examples of real-time, event-driven Java. I also recommend you to go through 👉 Code,... - Source: dev.to / over 1 year ago
When debating the database solution for our application we were really seeking for a scalable serverless database that wouldn’t bill us for idle time. Options like AWS Athena, AWS Aurora Serverless, and Azure Cosmos DB immediately came to mind. We believed that GCP would have a comparable service, yet we could not find one. Even after consulting the GCP cloud service comparison documentation we were still unable... - Source: dev.to / almost 2 years ago
If you are looking for one to start with; you can try Cosmos: https://azure.microsoft.com/en-us/services/cosmos-db/. Source: about 2 years ago
I have had an opportunity to work on a project that uses Azure Cosmos DB with the MongDB API as the backend database. I wanted to spend a little more time on my own understanding how to perform basic setup and a simple set of CRUD operations from a Node application, as well as construct an easy-to-follow procedure for other developers. - Source: dev.to / about 2 years ago
Kubernetes - Kubernetes is an open source orchestration system for Docker containers
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
Google Kubernetes Engine - Google Kubernetes Engine is a powerful cluster manager and orchestration system for running your Docker containers. Set up a cluster in minutes.
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.
Apache Mesos - Apache Mesos abstracts resources away from machines, enabling fault-tolerant and elastic distributed systems to easily be built and run effectively.
neo4j - Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.