Monat: August 2017

Imanis Data – Cloud migration, backup for your big data applications on Azure HDInsight

We are pleased to announce the availability of Imanis Data on Azure.

Azure HDInsight is the industry leading fully-managed cloud Apache Hadoop & Spark offering, which allows customers to run reliable open source analytics with an industry-leading SLA. Imanis Data provides data management software that allows users to migrate data and add backup and restore functionality for their big data applications.

This combined offering of Imanis Data on HDInsight and integration with Azure Blob Storage and Data Lake Store enables customers to migrate to cloud faster, protect critical data assets from application or human error.

Microsoft Azure HDInsight – Reliable open source analytics at enterprise grade and scale

HDInsight is the only fully-managed cloud Hadoop offering that provides optimized open source analytical clusters for Spark, Hive, Interactive Hive, MapReduce, HBase, Storm, Kafka, and R Server, backed by a 99.9% SLA. Each of these big data technologies are easily deployable as managed clusters with enterprise-level security and monitoring.

Imanis Data – Cloud migration, backup and restore for big data applications

The explosive growth of cloud computing in general, and the rise of big data applications, has brought about a need to ensure that workloads previously running on-premises can run at-scale in Azure; as well as keeping the underlying HDInsight data assets protected from disasters, human errors and application corruption.

To that end, we’re excited to highlight Imanis Data (formerly Talena, Inc.) who just launched their software solution on the Azure. Imanis Data provides data management software that covers a wide range of use cases that will benefit HDInsight customers, including:

Migration of on-premise or other cloud big data workloads to Azure HDInsight: Imanis Data provides a compelling way for companies to migrate their big data workloads to HDInsight, independent of which Hadoop distribution you’re using. This includes both data and application specific metadata as well.
Cloud Disaster Recovery: Imanis Data can easily be used as the basis for moving both data and metadata of your Open Source Workloads such as Hive, HBase, Spark to a secondary region, enabling cross-region DR.
Scalable Backup and Rapid Recovery: Imanis Data enables extremely rapid backup and point-in-time recovery of petabyte-scale data used by open source workloads such as Hive, HBase, Spark.
Test Data Management: As enterprises move data to the cloud, protecting PII is critical. The native data masking capabilities in Imanis Data enable enterprises to protect sensitive data while migrating data to QA, data analytics or other clusters in the cloud.
Archiving for compliance and regulatory requirements.
Native integration with Microsoft Azure Blob Storage and Azure Data Lake Store. 

To support these diverse use cases, the Imanis Data software architecture incorporates:

A distributed and highly-scalable file system that enables support for petabyte-scale workloads.
Rapid recovery capabilities with an intuitive metadata catalog, the flexibility to recover to different database topologies, and support for parallel data transfers.
A built-in storage optimization engine that focuses on incremental-forever backups, global block-level de-duplication, and compression.
Agentless integration with various databases.
Support for data mirroring and replication across multiple Azure regions.

To learn more about Imanis Data offering on Azure, please see this.

Getting started with Imanis Data on Azure HDInsight

You can install Imanis Data from Azure marketplace. Imanis Data software is installed on a VM which sits outside the cluster.

To configure Imanis Data for Azure HDInsight, please read this detailed guide. Following is a screenshot of configuring Imanis Data for HDInsight.

After you install it, connect to the Azure HDInsight cluster and perform the following operations:

Connect Imanis Data to on-premise Hadoop or Spark cluster: Imanis Data can help migrate data from on-premise Hadoop, Spark or HBase, as well as metadata associated with these workloads to the cloud. You can store the data in Azure Blob Storage or Azure Data Lake Store. Once you move the data you can run Hadoop, Spark or HBase or use R Server on Azure HDInsight to perform advanced analytics.
Cloud Disaster Recovery: Imanis Data can easily be used as the basis for moving both data and metadata of your Open Source Workloads such as Hive, HBase, Spark to a secondary region, enabling cross-region DR.
Scalable Backup and Rapid Recovery: Imanis Data enables extremely rapid backup and point-in-time recovery of petabyte-scale data used by open source workloads such as Hive, HBase, Spark.
Test Data Management: As enterprises move data to the cloud, protecting PII is critical. The native data masking capabilities in Imanis Data enable enterprises to protect sensitive data while migrating data to QA, data analytics or other clusters in the cloud.
Archiving for compliance and regulatory requirements.

Joint webinar on cloud migration, backup and restore, and more

We hosted a joint webinar on June 27, during which we highlighted how enterprises can benefit from using Imanis Data to manage their big data applications on HDInsight. We covered various patterns on how you can use Imanis Data to set up a hybrid environment, dev/test management, backup and restore, and replication across different regions in Azure. The following diagram shows a summary of the patterns covered. In case you missed it, you can still watch the webinar to learn more. We look forward to talking with you and getting your feedback.

Resources

The following resources are available to learn more about this integration:

Learn more about Azure HDInsight
Talena Enables Rapid Migration of Modern Data Workloads to Microsoft Azure HDInsight
Get Imanis Data from Azure Marketplace
Getting started with Imanis Data on Azure
Getting started with Imanis Data on Azure HDInsight
Imanis Data Management Solution on Azure Data Sheet
Deploy Imanis Data on Azure HDInsight for a cross-geo replication scenrio
Learn more about Imanis Data on Azure
Ask HDInsight questions on stackoverflow

Summary

This combined offering of Imanis Data on HDInsight and integration with Azure Blob Storage and Data Lake Store enables customers to migrate to cloud faster, protect critical data assets from application or human error. If you have any feedback or questions, feel free to drop us an email at hdiask@microsoft.com. We’d love to hear from you!
Quelle: Azure

On-premises data gateway support for Azure Analysis Services

Azure Analysis Services now supports the shared On-Premises Data Gateway which is used with Power BI, Flow, Logic Apps, and PowerApps. This has been a top ask in our user feedback. The shared gateway allows you to associate many services to one gateway or you can continue to use a dedicated gateway. With the shared gateway, managing connectivity is much easier. For example, you can configure multiple Azure Analysis Services servers to use the same gateway just by associating each one to the same gateway.

To use the shared gateway, the first step is to setup the On-Premises Data Gateway by downloading and running the gateway installer on a local computer. During the install, you will be prompted for your work or school account which will be setup as a gateway administrator in the gateway service. In order to associate your gateway to an Azure resource, you will need to be an administrator. After you set up a recovery key, you may need to change the region of the gateway.

For performance and reliability purposes, Azure Analysis Services will only use a gateway resource from the same region. For instance, if you have an Azure Analysis Services server in the East US 2 region, you will need to have a gateway configured for that region. Multiple Azure Analysis Services servers in East US 2 can use the same gateway. Picking the right region is required or you won’t be able to associate the gateway to Azure Analysis Services.

Once you complete the setup and any needed network configuration for firewalls, ports, et cetera, you will need to create a gateway resource in Azure. You can use the same settings and trouble shooting steps as for the Power BI On-premises Data Gateway since it is the same gateway!

Again, it will need to be in the same region as the gateway and Azure Analysis Services.

After adding the gateway resource in Azure, you can now go to your Azure Analysis Services server and configure it to use that gateway with the new gateway blade. On this blade, just pick the gateway and connect it to Azure Analysis Services.

Now it is connected!

You can use this same gateway for multiple Azure Analysis Services servers in this region. You can also use this gateway with Flow, Logic Apps, PowerApps, and Power BI (if Power BI is in the same region). This is also useful for dev/test configurations. Keep in mind you need to have admin privileges on the gateway and Azure Analysis Services to create the connection, and Azure Analysis Services and the gateway need to be in the same region. Once connected, any Azure Analysis Services data source can use that gateway for Direct Query or processing. 
Quelle: Azure

Investing deeply in Terraform on Azure

As customers increase their deployed applications in Azure, we are seeing a growing interest in DevOps tooling on Azure. We also see customers looking to deploy applications across multiple environments, including hybrid and multi-cloud deployments while using the same tooling and enabling the same DevOps experiences. In order to meet these growing needs, I am excited to announce that we are greatly increasing our investment in Terraform, partnering closely with HashiCorp, a well-known voice in the DevOps and cloud infrastructure management space.

Our partnership with HashiCorp goes back to early 2016, where we jointly announced plans to bring full support for Azure Resource Manager across many tools in HashiCorp’s portfolio including Packer and Terraform. Since then, our customers have found significant value in the HashiCorp support on Azure.

Today, we’re extending our partnership and will offer an increasing number of services directly supported by Terraform, including Azure Container Instances, Azure Container Service, Managed Disks, Virtual Machine Scale Sets and others. We want to give additional flexibility to express infrastructure-as-code and to enable many more native Microsoft Azure services to be easily deployed directly through Terraform. Learn more about the Azure provider for Terraform.

I am really excited about our partnership with HashiCorp. They are well-positioned to support the complexity and diversity of this space. They also have a rich portfolio of products that can help our customers adopt DevOps principles to automate management of their infrastructure on Azure and across multiple environments.

If you’re looking to get started, give Terraform in Azure a try today! Stay tuned for additional updates as we work together in the open source project to deliver this increased support.

 

See ya around,

Corey
Quelle: Azure