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Developing Cloud Applications: Pattern Usage and Workload Modeling

For enterprise companies today, the process of determining one or more common application usage profiles for use in cloud platform performance testing is known as ‘application workload modeling’. Cloud application workload modeling can be accomplished in a myriad of ways, and is a critical piece to properly planning, developing and implementing successful cloud solution technologies.

Some General Best Practices when Developing Cloud Applications.

  • Understand your application usage patterns. New business processes are prime candidates for building out such apps. Silo-ed departmental initiatives often evolve into organizational best practices that get adopted by the entire enterprise, and because most of the programs are developed organically from the ground up, they can leverage the interoperability of the cloud and be scaled depending on demand. This also allows the app to be discontinued with minimal cost if the initiative isn’t deemed efficient or necessary to the organization.

  • Develop and Deploy Your Application. Creating a plan and sequence of key metric drivers help you keep your cloud deployment efforts on track. Start small, grow fast is a common mantra of many start-ups (including ours), the overwhelming majority of which are intimidated by the significant cost of on-premise infrastructure.
  1. Define and Identify the objectives
  2. Document and Identify primary usage scenarios
  3. Develop and Determine navigation paths for key scenarios
  4. Design and Determine individual user data and variances
  5. Determine the likely-hood of such scenarios
  6. Identify peak target load levels
  7. Prepare and Deploy the new cloud solution
  • Monitor Spiked Usage Patterns for “Common Utility Apps”. Within every organization, large or small, there’s at least one program or application that receives spiked usage during a certain time of the year, quarter or month. One example of this pattern is related to corporate tax software, as this app is lightly used for many months, but becomes a highly leveraged application during the end of the fiscal year tax calculation process. Another example is Human Resource Information Systems (HRIS) and the periodic need for employees to subscribe to new company health plans, insurance plans, etc. Other examples include e-commerce websites like Ebay and Buy.com which experience this “peak load” requirement during holiday or special sales seasons.

The common thread across all of these types of “on-demand” cloud apps is that their usage rate is relatively standard or predictable most of the time, but become the most demanded of resources periodically. Utilizing a scalable cloud solution approach in this manner enables greater cost savings and ensures high availability of your enterprise business systems.

Application Load and Scalability, and Dynamically Reacting to Peak Load

As it is most often associated with consumer-facing web apps, unpredictable load occurs when an inordinate amount of traffic is directed toward your site, and the app is subsequently unable to meet this demand—causing the entire website to return a load error message. Nubifer has noticed sudden spikes in traffic when organizations launch fresh marketing campaigns, or receive extensive back-linking from prominent authority sites. Apps and sites eminently susceptible to these load spikes are ideal candidates for the cloud, and the most prominent advantage of this methodolgy is the auto-scale or on-demand capability.

Monitoring, a Primary Key to Any Successful Cloud Deployment

Your cloud platform monitors the patterns of Internet traffic and the utilization of the infrastructure, adding additional server resources if the traffic crosses your preset threshold. The extra servers that are added can be safely deactivated once the traffic subsides and the environment isn’t so demanding. This creates an extremely cost-efficient use case for leveraging a cloud platform for app and site hosting.

To the contrary of unpredictable load occurrences, e-commerce sites commonly experience predictable spikes in traffic. For instance, when Amazon launches pre-ordering for the next novel for Oprah’s book club, they prepare their infrastructure to handle these peak loads. Organizations of this size typically have a ballpark budget figure of the infrastructure cost because of its inherent predictability. There are many occurrences in the public sector that experience predictable bursts as well, such as electoral results and the examination of the latest census reports.

Understanding Application Usage Pattern Trends

Within your business, these patterns are manifested during a virtual company meeting or initiation of a compulsory online training for all employees, but the primary difference between this pattern of usage and the first is that there may not be a periodic recurrence of this particular pattern or spike in resource demand.

It’s paramount that your IT personnel remain cognizant of these peak load times, whether they are predictable or not, as this is a key element for effectively leveraging a cloud solution that offers support and business intelligence data regarding peak load and latency issues.

How We Have Evolved to Solve for Peak Load and Usage Monitoring

Nubifer has solved these business scenarios by developing a robust set of tools and monitoring applications for private and public clouds, named Nubifer Cloud:Link. To learn more about Cloud:Link and Nubifer’s approach to enterprise cloud monitoring visit CloudLink.pro

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