Cloud Performance Management Metrics to Watch | Synopsys Cloud
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A cloud performance management (CPM) system measures metrics and benchmarks for cloud systems. It informs you about how well your cloud system works as well as how to improve it.

Efficiency in the cloud is critical to ensuring business continuity and access to cloud services for all users. Whether you rely on basic cloud use, complex hybrid, or multi-cloud architectures, reliable performance is key. By monitoring cloud performance metrics, you can ensure seamless communication between all components in the cloud.


Key Cloud Performance Management Metrics

For most cloud environments, you will want to track a few key CPM metrics.

 

Average Compute/Storage Costs 

You can more easily control costs by tracking the total cost of your cloud-based computing resources, including virtual machines and serverless functions. Increasing computing costs without increasing demand can potentially result in an over-provisioned environment, which wastes money until it's fixed. 

Make sure to keep an eye on your cloud storage costs. These costs include databases, object storage, and block storage. Increasing storage costs without corresponding needs might indicate a problem, such as inefficient tiering or data lifecycle management.

 

Error Rates 

An error rate metric tells you how often a request fails and what types of errors frequently occur. This metric of cloud performance management indicates the overall health of your application and the cloud environment. 

Though an application might cause errors, you might also find that your cloud environment is malfunctioning. The lack of availability of a cloud service–an issue your cloud provider should solve for you–or an improperly configured access credential for services in your cloud can both provoke issues in your environment. 

 

Server Availability

Another way to ensure efficient cloud performance management is to track how many servers you have that are up and running as a percentage of how many you have deployed.

If a server goes down, cloud orchestration and automation tools can re-distribute workloads automatically. Yet, these tools can only do so until they run out of servers. Serious issues can arise if the number of available servers drops below 90% of the total deployed.

 

Requests Per Minute 

By tracking how many requests a cloud application receives per minute, you can detect when these requests differ from historical averages. This metric makes it easier to predict when to increase your cloud capacity. 

 

Acknowledgment Time 

Acknowledgment time measures how long it takes for your cloud-based app to respond to a request. When you track acknowledgment time, you can find out if your load balancers forward requests quickly enough. 

You might also discover you have a problem with underprovisioning if acknowledgment times are slow. Make sure to monitor and compare time-to-acknowledge metrics for each cloud region or individual cloud rather than analyzing them in aggregate. Doing so can help you pinpoint latency issues specific to a particular region or cloud.

 

Response Duration 

Response duration measures how long it takes a cloud application to respond. You can tell if your app has enough cloud resources by referring to this metric. A slow response time may indicate a bug or communication issue within the app. You should also track response duration by region and cloud if you want the best visibility into latency.


Cloud Performance Management and Chip Design

The high-performance computing environment for chip design and verification takes hundreds of thousands of servers and hundreds of petabytes of storage. Chip designers, therefore, must analyze cloud performance frequently to ensure they have the best cloud provider. 

Cloud performance management helps your company identify and fix performance bottlenecks in systems and applications. You can also use CPM to help you find cost-effective ways to achieve optimal performance. 

Synopsys Cloud's FlexEDA model frees you from license and capacity restrictions. Because we remove capacity constraints, you can break down projects into faster cycles, allowing more innovation time and less scheduling. At the same time, we can optimize your cloud performance to ensure your chip projects run smoothly. 


Synopsys, EDA, and the Cloud

Synopsys is the industry’s largest provider of electronic design automation (EDA) technology used in the design and verification of semiconductor devices, or chips. With Synopsys Cloud, we’re taking EDA to new heights, combining the availability of advanced compute and storage infrastructure with unlimited access to EDA software licenses on-demand so you can focus on what you do best – designing chips, faster. Delivering cloud-native EDA tools and pre-optimized hardware platforms, an extremely flexible business model, and a modern customer experience, Synopsys has reimagined the future of chip design on the cloud, without disrupting proven workflows.

 

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