Azure Cosmos DB is a fully managed, elastically scalable and globally distributed database with a multi-model approach, and provides you with the ability to use document, key-value, wide-column, or graph-based data.
In this blog, we will dive into the multi-model capabilities and explore the options that are available to store and access data. Hopefully, it can help you make an informed decision on the right API are the right choice.
Setup an Azure Cache for Redis instance
Start Grafana in Docker:
docker run -d -p 3000:3000 --name=grafana -e "GF_INSTALL_PLUGINS=redis-datasource" grafana/grafana
Access Grafana dashboard — browse to
adminas the username and password
Add the Data Source
Are you learning Rust and looking for ways to get hands-on practice with concrete examples? A good approach might be to try and integrate Rust with external systems. Why not try to integrate it with Redis, which is a powerful, versatile database but dead simple to get started with!
In this blog post, you will learn how to use the Rust programming language to interact with Redis using the redis-rs client. We will walk through commonly used Redis data structures such as String, Hash, List etc. …
Apache Kafka often serves as a central component in the overall data architecture with other systems pumping data into it. But, data in Kafka (topics) is only useful when consumed by other applications or ingested into other systems. Although, it is possible to build a solution using the Kafka Producer/Consumer APIs using a language and client SDK of your choice, there are other options in the Kafka ecosystem.
Azure Cosmos DB Cassandra API is a fully managed cloud service that is compatible with Cassandra Query Language (CQL) v3.11 API. It has no operational overhead and you can benefit from all the underlying Azure Cosmos DB capabilities such as global distribution, automatic scale out partitioning, availability and latency guarantees, encryption at rest, backups etc.
At the time of writing this blog, the Azure Cosmos DB Cassandra API serverless is available in preview mode !
Webhook backend is a popular use case for FaaS (Functions-as-a-service) platforms. They could be used for many use cases such as sending customer notifications to responding with funny GIFs! Using a Serverless function, it’s quite convenient to encapsulate the webhook functionality and expose it in the form of an HTTP endpoint. In this tutorial you will learn how to implement a Slack app as a Serverless backend using Azure Functions and Go. …
Well, Microsoft is bringing to you, Data Week 🙌 A celebration of Data & Data Technologies, running throughout the week, starting December 7, 2020!
Change Data Capture (CDC) can be used to track row-level changes in database tables in response to create, update and delete operations. It is a powerful technique, but useful only when there is a way to leverage these events and make them available to other services.
Using Apache Kafka, it is possible to convert traditional batched ETL processes into real-time, streaming mode. You can do-it-yourself (DIY) and write good old Kafka producer/consumer using a client SDK of your choice. But why would you do that when you’ve Kafka Connect and it’s suite of ready-to-use connectors?
In this blog, we will go over how to ingest data into Azure Data Explorer using the open source Kafka Connect Sink connector for Azure Data Explorer running on Kubernetes using Strimzi. Kafka Connect is a tool for scalably and reliably streaming data between Apache Kafka and other systems using source and sink connectors and Strimzi provides a “Kubernetes-native” way of running Kafka clusters as well as Kafka Connect workers.
Azure Cosmos DB is a resource governed system that allows you to execute a certain number of operations per second based on the provisioned throughput you have configured. If clients exceed that limit and consume more request units than what was provisioned, it leads to rate limiting of subsequent requests and exceptions being thrown — they are also referred to as 429 errors.
With the help of a practical example, I’ll demonstrate how to incorporate fault-tolerance in your Go applications by handling and retrying operations affected by these rate limiting errors. …
Currently working with Kafka, Databases, Azure, Kubernetes and related open source projects | Confluent Community Catalyst (for Kafka)