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Cloud Computing Performance Metrics

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Monitoring and management are central elements of any public cloud deployment strategy. Proper management can help an organization ensure that public cloud usage, performance, cost, and even business benefits meet or exceed requirements. Monitoring can often identify service gaps or issues that an organization should be aware of.

Cloud Computing Performance Metrics

Cloud Computing Performance Metrics

Cloud architects, administrators, and developers need the right tools to overcome these challenges. Public cloud providers have a selection of tools that provide detailed information tailored to their platform. There are also third-party offerings that support one or more public clouds. The tool you choose should be able to provide a set of useful metrics that support your business needs and goals.

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Let’s list a number of metrics and parameters that can help businesses monitor their public cloud usage and look at some tools that can collect the necessary data.

A metric is a parameter that can be directly measured and tracked over time to identify trends. For example, the number of requests to a load balancing service and the CPU usage of a compute instance are metrics.

In comparison, a KPI – also known as a key performance indicator – usually represents a specific parameter that is important to the performance or growth of the business. KPIs can be directly measured. For example, the monthly cost of a cloud provider’s services can be considered a KPI because it is of particular importance to the business.

However, KPIs are often obtained or calculated through a combination of indicators. For example, business KPIs such as cost per transaction cannot be directly measured by the cloud provider because cost per transaction is not specific to the cloud provider. These details can be calculated from metrics such as cloud provider bandwidth and monthly billing figures.

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Let’s focus on metrics first, as these parameters can usually be measured easily or directly by the cloud provider.

Public cloud infrastructure is perhaps the most common and objective source of metrics for cloud users. These metrics measure what is happening with the provider’s resources and services.

Organizations often complain about the lack of transparency in public clouds, but providers have made strides in these areas in recent years. For example, they now provide access to infrastructure KPIs and metrics through common interfaces such as consoles and APIs.

Cloud Computing Performance Metrics

With infrastructure metrics, businesses can measure resource and service usage and determine application availability, performance, health, and more. This makes infrastructure metrics key to effective public cloud management.

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Cloud administrators can choose from a bewildering array of data points. While it’s not necessary or even desirable to track every metric available, here are the most common infrastructure data points.

Compute metrics relate to the size and performance of compute instances in the public cloud, such as Amazon EC2 or Microsoft Azure VM instances. These metrics can include CPU, memory, disk, network, and general health and availability parameters. Such indicators help determine whether the application in each case works and functions properly.

The storage metrics mentioned above are for temporary storage associated with the compute instance itself. Long-term storage resources such as Amazon S3 or Google Cloud Storage provide a diverse set of metrics that detail the usage, performance, and health of storage resources separated by compute instances.

Load balancing services such as Google Load Balancing and Azure Load Balancer are used to distribute incoming network traffic from the Internet across public cloud workloads such as Google Compute Engine instances or Azure VMs, respectively.

Pdf] Qos Metrics For Cloud Computing Services Evaluation Amid

For example, enterprises often place copies of critical workloads in multiple regions to facilitate latency management. Load balancer metrics show the performance of the load balancer itself and the performance of the endpoint workload it serves.

IT teams can choose from a number of databases and other services to integrate and analyze data. For example, AWS has Amazon Aurora, Relational Database Service, Redshift, DynamoDB and more. Public cloud metrics are essential for monitoring throughput, performance, and utilization of database services.

Because the database is primarily a workload installed and run by the cloud provider, administrators and developers need additional CPU, disk, I/O, and network performance for the database compute instance . can access the liq collection. computational sample metrics discussed earlier. This creates additional transparency and allows users to see what is happening on the cloud provider’s side.

Cloud Computing Performance Metrics

Cloud providers offer hosted and managed storage services. The goal is to use memory to store frequently accessed data without requiring access to slower services such as disk storage. This provides better throughput and lower latency for critical workloads.

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For example, AWS offers ElastiCache and Google has Memorystore, both of which support Redis and memcached caching mechanisms. These metrics report cache performance along with workload performance using the cache.

As with databases, cache is primarily a workload implemented and maintained by the cloud provider, and additional metrics such as CPU, disk, I/O, and network metrics are also available for the cache compute instance.

Developers use serverless computing services like AWS Lambda, Azure Functions, and Google Cloud Functions to run small workloads called functions without having to provision and pay for dedicated compute instances. They simply load the code and initialize the parameters. The cloud provider loads, runs, and then downloads the feature automatically when the activation parameters are met.

Collecting metrics from a cloud provider can reveal important details about the provider’s resources and services, but typically doesn’t tell a business how well a particular workload is performing. A business may wish to perform application performance monitoring or user experience monitoring to make determinations about that business or workload.

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The shift from metrics to KPIs typically occurs when businesses use metrics to calculate or obtain business-oriented details that are not directly available from a cloud provider. Special tools such as Amazon QuickSight may be required to collect key metrics and perform calculations to create the required KPIs. There are many KPIs of business interest, but some common KPIs might include:

Enterprises typically calculate KPIs for strategic business objectives, such as cloud migration. Business metrics for cloud migration are not readily or directly available, but must be calculated or derived for business analysis. For example, a business can calculate the time required for a migration, the cost of the migration process, downtime, etc.

Cloud architects need the right tools to collect public cloud metrics and derive KPIs. Public cloud providers offer monitoring services that can track and report on many common metrics.

Cloud Computing Performance Metrics

For example, IT teams can calculate trends by collecting metrics, logs, and events using Amazon CloudWatch. This information helps you monitor application health and performance, optimize resource usage, and more. Azure Monitor and Google Cloud Platform both have monitoring and reporting tools, such as Azure Monitor and Google Cloud Operations, for daily cloud metrics and cloud cost management.

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However, none of these tools include an easy way to translate local metrics into business-oriented KPIs. For example, there’s no way to know if a cloud provider wants to capture business KPIs, such as cost per transaction, failure rate, or the myriad other parameters that help make public clouds profitable for businesses. IT teams must use additional internal and third-party tools to calculate and capture critical KPIs. A small sample of the possible tools for KPI and data analysis include: Cloud metrics are a great way to optimize the benefits of the cloud for your business. If you want to run a cloud application or move a project to the cloud, you need a cloud provider like Amazon Web Service or Microsoft Azure to match your level of performance.

Whether you’re undertaking a cloud migration project or want to implement a new cloud, you’ll need to match the cloud provider that best suits your needs without overspending on workload performance. Cloud computing benchmarks are a great way to compare price to performance.

Determining what your real computing needs are is the first step in choosing the right cloud solution. By analyzing your systems, activities and processes, you can determine your unique requirements.

Continuous operations are the foundation of any business. This means 24/7 working conditions. To eliminate scheduled maintenance, you have the infrastructure in place and applications continue to be maintained until they are upgraded to new versions after you install and test them.

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To achieve the goal of continuous operations, enterprises choose cloud servers from several redundant platforms. While using the cloud makes it easier to secure the resources you need, you pay for them in case of scheduled maintenance.

Idle cost affects the company whether planned or unplanned. As companies move toward seamless operations, cloud metrics play a critical role. Only by collecting and analyzing continuous and regular cloud measurements can they provide this

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