Azure services in the cloud

Posted by gautham on September 21st, 2019

Azure services in the cloud

In azure there are many services are listed for the users. Here we will some of the services of azure in detail.
Azure Redis cache
Azure Redis cache is open-source. Azure Redis cache is based on the popular source Redis. The difference is azure technology manages Redis for us. It saves from the trouble of spinning up a VM. Users can use the Redis cache using the Azure portal. This azure Redis can be accessed from any of the application within the azure. One can provide this through the Azure portal.
This azure Redis cache is available in three tiers.
Basic tier
This tier provides a single node in multiple sizes. This tier has no service level agreements
Standard Tier
In standard tier provides a resource for a specified cache two nodes in the configuration managed by Microsoft. This tier also have service level agreement
Premium tier
In the last tier, it includes everything in the standard tier and better performance, enhanced security and users can able to handle easily. You can study and learn concepts on azure through azure certification and practise them easily

Bigger workloads, and disaster recovery.
You can use Redis persistence to persist data stored in the Redis cache. You can also take snapshots and back up the data (which can be reloaded later in case of failure). You can use Redis cluster to shard data across multiple Redis nodes, creating workloads of bigger memory sizes for better performance. You can deploy your Redis cache in a VNet, providing enhanced security and isolation for your Redis cache, as well as subnets, access control policies, and so on.
Azure HDInsight
Azure HD Insight is fully managed Hadoop service. Hd insight includes popular platforms like apache HBase, apache storm, apache storm, etc
HDInsight is used in big data scenarios. In this case, big data refers to a large volume of collected—and likely continually growing data that is stored in a variety of unstructured or structured formats. This can include data from weblogs, social networks, Internet of Things (IoT), or machine sensors either historical or real-time. For such large amounts of data to be useful, you have to be able to ask the right question. To ask the right question, the data needs to be readily accessible, cleansed (removing elements that may not be applicable to the context), analyzed, and presented. This is where HDInsight comes into the picture.
The Hadoop technology stack has become the de facto standard in big data analysis. The Hadoop ecosystem includes many tools HBase, Storm, Pig, Hive, Oozie, and Ambari, just to name a few.
One can also certainly build your custom Hadoop solutions by using Azure VMS. You can also deploy HDinsght cluster on windows or other platforms, provisioning Hadoop Cluster with HDinsght can be the time-saver. You can learn on azure technology through Microsoft azure certification by experts.

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