|By Srinivasan Sundara Rajan||
|January 20, 2011 10:15 AM EST||
Auto Scaling Windows Azure
My last article on comparing Dynamic Scaling Features between Windows Azure vs Amazon EC2 mentioned that Both EC2 and Azure provide an auto scaling feature. While EC2 provides a backbone and framework for auto scaling, Azure provides an API that can be extended. We are already seeing several third-party providers delivering tools for Azure auto scaling.
One such third-party auto scaling product company, Paraleap Technologies, has recently released a product called AzureWatch that provides a SaaS-based approach to scale the Windows Azure compute roles. Some of the observations about the product are mentioned below. The company also provides a free 14-day trial of the product whereby some of the facts can be ascertained in a live situation.
The following aspects of the product were observed, based on the technical documentation available with the product vendor.
The core of the Azurewatch data collection and aggregation and decision-making process is available as a SaaS-based solution in the form of Azure Watch Service. The AzureWatch Service aggregates and analyzes performance metrics and matches these metrics against user-defined rules on a regular and configurable basis. When a rule produces a "hit," a scaling action occurs.
However, there are some glue or controlling components installed on the ‘On Premise' systems in the form of the AzureWatch Monitor and Control Panel. The Monitor is responsible for sending raw metrics to SaaS-based systems and executing scaling actions. The Control Panel is a simple but powerful configuration and monitoring utility that allows you to configure custom rules and to monitor your instances.
This approach is useful, because much of the overhead of the Data Storage and maintenance of the metrics data is kept away from the enterprises and only a lightweight component in the form of the AzureWatch Monitor and Control Panel needs to be installed ‘On Premise.'
The following diagram, courtesy of vendor, explains the solution.
Rules Engine-Based Interface
As we have seen, Auto Scaling is typically handled by the Pro Active Monitoring, which is done by the AzureWatch Monitor coupled with the analysis and the metrics gathered by the AzureWatch Service. Finally the scaling action is taken based on the rules configured using an easy-to-use GUI tool.
For each of the roles as part of your Azure subscription, Azurewatch provides simple predefined rules that can be tailored further. The two sample rules offered are simple rules that rely upon calculating a 60-minute average CPU usage across all instances within a Role. The Rule Edit screen is simple yet powerful. You can specify what formula needs to be evaluated, what happens when the evaluation returns TRUE, and what time of day should evaluation be restricted to.
Dashboards & Reports
The success of the monitoring tools are measured by the nature of the dashboards and reports, as the metrics data in the raw form is very difficult to understand. Dashboards in AzureWatch provide the following information.
- Instance Count
- Instance History
- Metrics Display based on Windows Counters
Like traditional data center-based monitoring tools, AzureWatch has built in notification capabilities so that emails are sent based on scaling conditions that happen. AzureWatch can track active/unresponsive/other instance counts for you. You can create rules that either trigger scaling actions or notification emails based upon conditions that rely on instance counts.
Nice to Have
Currently the metrics watch service needs to be carefully watched, and metrics can get stale if the service stopped for some reason. It would be nice to have more ways to avoid the metrics getting stale.
If new packages are installed, they may get missed from monitoring if the instructions are not followed.
If there are options to manually set the Metrics for some special reasons that may provide more control. It's similar to the way in which Oracle and other databases handle Stale statistics.
Over all AzureWatch and similar third-party tools will make the Cloud Deployments really fruitful because they're meant to improve the core tenant of the Cloud-based deployment, namely the elasticity and dynamic scaling.
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