5 Indicators of Your Cloud's Health Status

February 1 2015 | by Boris Goldberg

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In my last blog post, I discussed the importance of cost as an operational indicator for cloud efficiency and health. However, it is important to note that cost, alone, doesn’t reflect how effective your cloud is. Knowing that your business paid a certain amount one week and three times more the following week, is not enough to indicate if your cloud is optimized and aligned with your business needs.

In order to analyze whether or not your cloud environment is effective, it is important to correlate three types of data: cost, business metrics, performance metrics and configuration management events. These help you draw the line from service degradation to an event that happened in your environment. In this post, we will go over five valuable indicators that can help you estimate the status of your cloud environment’s health.

1. Utilization Level of Cloud Resources

The cloud’s dynamic nature, flexibility and self services are great features, however there is no doubt that without policies and control in place, the risk of Cloud Sprawl can have an immediate impact on your business. Utilization is generally greater in the cloud than traditional hardware.

The first step is collecting usage data. This includes finding out the utilization level of your resources, such as virtual machine utilization, number of disk IOs, network traffic, and so on. Each element will help you understand what’s happening on the lower level of your infrastructure. Ensure that your AWS deployment is optimally utilized.

2. Application Metrics

Application metrics serve as another great insight to measure efficiency. They provide information like the amount of number of requests that are handled and sent to NoSQL databases, such as DynamoDB. Using tools like New Relic to perform cloud monitoring and track these types of metrics enables IT to learn about trends and the impact of changes made to your application in your cloud infrastructure. Once an alert was made you can take the next step in drilling into your cloud footprint, usage and costs in order to learn more on how the upper stack metric related to your underlying infrastructure.

3. Business Metrics

Business metrics are important indicators of how your business is performing. They can tell you how many new users you have today or this week, the number of purchase orders and invoices that were processed, and the amount of deliveries that were made. These types of metrics can easily describe the functionality of your SaaS operations and indicate issues across your deployment stack.

4. Software Lifecycle Events

Documenting and tracking software lifecycles are important. They can assist when significant changes take place. For example, let’s say you used to run five instances, but your cloud’s automation recently increased your capacity to 15 instances due to a product update. It is important to know about these updates so that you understand your underlying infrastructure’s automatic changes. Additionally, these updates should be correlated into certain detected inefficiencies within your deployment.

5. Auto Scaling Events

Automation is a crucial feature when it comes to cloud operations. The cloud, by definition, supports the option of pay-per-use and the ability to align demand with capacity. The core cloud capability that enables these notions is Auto Scale. When developing the next generation of applications, you must take the elastic manner of IT into consideration, especially when it comes to computing. It is important to monitor auto scale including real time changes as well as trends.

Cloudyn Glues them Together

Today, IT environments are more complex than ever. Deployment may be dispersed between several public clouds and on-premises hosts. Ensuring that business performance is aligned with IT operational costs requires pulling, normalizing, and processing data from quite different sources. With Cloudyn, you can manage and optimize cloud costs per business unit or track deployment usage and capacity anomalies. Learn more.

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