The Azure cloud is moving fast in so many areas. Understandably, migration tools that can assist and automate the process of migrating applications to Azure are of great importance in order to encourage a move away from existing infrastructure.
Two such tools that I’ve discovered recently are the Web Apps Migration Assistant, which is detailed here, and the Data Migration Assistant, detailed here.
The Web Apps Migration Assistant will analyse your hosted IIS (and even Linux) web apps, and can migrate them (if compatible) to the Azure App Service as Web Apps.
The Data Migration Assistant targets SQL Servers and analyses them for migration to Azure SQL Database. This tool does not perform the migration, instead it highlights the incompatibilities that exist and suggests remedial action, this could include preparing fixes as Transact-SQL scripts. Tools such as SSMS or SQLPackage.exe can be used to migrate the database to Azure, a good overview of this process is here and a deeper discussion of the process is mentioned in this SQL CAT blog. Of course, you may want to determine if your database is even suitable for running in Azure and tools exist such as this one to help size the database prior to migration.
These two tools could help fast-track your move to the cloud, and whilst some effort will still be required, they remove much of the manual effort that was previously required in shifting your applications and databases to Azure.
Friday, 31 March 2017
Friday, 24 March 2017
Vertica on Azure
For some time now you’ve been able to deploy a Vertica cluster to Azure via a manual process, but now, the Azure marketplace has the HPE Vertica Analytics Platform available to deploy via an ARM template a cluster with up to 5 nodes.
If you’re not familiar with Vertica, then in brief, it’s a column store relational database with rapid data load features (ingesting to memory) and then optimises the storage of that data on disk through different encoding schemes.
Having worked with Vertica for over 5 years I can recommend it for use in particular scenarios, particularly when your data is very tabular, denormalised, compresses/encodes well and is such that you may want to execute analytic workloads (queries) over that data. It works less well in situations where you need to join table data or perform transactional workloads with update or delete operations.
If you’re looking for an alternative to the likes of AWS Redshift or Azure Data Warehouse and are content to consider IaaS alternatives, then why not give Vertica a go, and spin up a cluster in your cloud of choice, it may just give you better performance, have a deeper feature set for your analytics and could work out cheaper than PaaS offerings.
If you’re not familiar with Vertica, then in brief, it’s a column store relational database with rapid data load features (ingesting to memory) and then optimises the storage of that data on disk through different encoding schemes.
Having worked with Vertica for over 5 years I can recommend it for use in particular scenarios, particularly when your data is very tabular, denormalised, compresses/encodes well and is such that you may want to execute analytic workloads (queries) over that data. It works less well in situations where you need to join table data or perform transactional workloads with update or delete operations.
If you’re looking for an alternative to the likes of AWS Redshift or Azure Data Warehouse and are content to consider IaaS alternatives, then why not give Vertica a go, and spin up a cluster in your cloud of choice, it may just give you better performance, have a deeper feature set for your analytics and could work out cheaper than PaaS offerings.
Tuesday, 7 March 2017
Azure Logic Apps - A blog re-post
For those of you wanting to get started with Azure Logic Apps, I've put together a simple guide to get you started. My example effectively creates an API app in Azure App Service using Logic App callable endpoints...
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