Cloud Optimization and Best Practices
Cloud optimization is the process by which an organization’s cloud spending is optimized according to its needs. It considers the organization’s needs vis-a-vis its investments in the cloud and uses machine learning and other technologies to balance this need with application requirements. When applied properly across an organization, cloud optimization leads to more efficient utilization of resources, better application performance, and higher employee productivity, among other benefits.
Definition of Cloud Optimization
The market for cloud services has grown since the launch of Amazon Web Services (AWS) some two decades ago, so much so that it has now become a go-to option for many organizations. This is not surprising since cloud services offer many advantages, including lower initial capital expenditure, faster time to market, and easy scalability based on changing requirements.
However, surveys have shown that there are many organizations that do not have an idea about the actual costs of investing in cloud services. The dearth of detailed pricing information among some cloud service providers can aggravate the problem.
This lack of cost-awareness can make cloud services more expensive unnecessarily. For instance, if you choose a much larger server instance than what you currently require or when you choose not to power down instances during weekends, even when you can afford to do so, you spend more than necessary. In addition, choosing to migrate applications as-is and without any architectural changes, even if they are not ideal for deployment to the cloud, can increase your overall costs. The cost of maintenance may also be a problem, especially if you lack qualified personnel.
Thus, it may happen that you are spending more than you need on cloud services. Cloud optimization provides a way to address this issue.
With cloud optimization, you can have a clear idea about which area of your cloud services spending you can cut down on. Examples of cloud optimization include:
Benefits of Cloud Optimization
The major benefits of cloud optimization are discussed below.
Improves Cloud Visibility
With cloud optimization, your organization can better identify opportunities for improving your presence on the cloud. By using the right tools, you can identify which resources are overprovisioned, cloud services and features that are underutilized, capabilities that are enabled or not on your account, and tools that are not being used properly by your team. You can then act accordingly to address these issues.
Minimizes Cloud Costs
Studies have shown that wasteful spending on cloud services is widespread among organizations. Ideally, it should be easy to access data that can help them guide DevOps in curbing costs. However, this is not often possible, given the vast number of cloud pricing plans. Although to their credit, many cloud service providers provide straightforward pricing.
With cloud optimization, IT teams are empowered to act on their own to curb pricing where they see fit while making it easy for higher management to understand the rationale for their actions.
Enhances Cloud Utilization
The number of cloud platform features can be overwhelming to many organizations. For example, AWS has over 200 cloud services. With cloud optimization, it is easier to track which features are essential and those that you can do without. You can also determine better alternatives to what you are currently doing.
Increases Productivity of your DevOps Engineers
With cloud optimization, your DevOps engineers can focus on creating code to optimize your applications instead of wasting time on issues that your service providers can already handle. For example, if your service provider is free to enhance your platform with new capabilities, your team can focus on other areas such as application security.
Gives Rise to Efficiency and Innovation
Cloud optimization empowers your team members to work with each other and discover newer and more efficient ways of doing things. For example, when given the responsibility, your DevOps team can prevent overspending before the actual overspend happens, which may not be feasible if you continue to assign this task to your finance people.
Considerations for Cloud Optimization
As you can see from the above, there are various aspects to cloud optimization, including cost, reliability, and improving carbon footprint.
Cost is a primary consideration for many organizations when it comes to cloud optimization. This is because it is easy to overspend on cloud services, especially when more resources are allocated than necessary to applications and services. Complex pricing plans can compound the problem.
Some cloud services provide basic tools for cost monitoring. These tools may not be enough when you have multiple cloud service providers. In this case, you can use third-party tools instead.
Another aspect of cloud optimization is application reliability. To address the issue of reliability, organizations often implement redundancy. However, deploying multiple instances of an application to different clouds can drive up costs rapidly. When this happens, you need to find a balance between application reliability and cost optimization.
Finally, improving carbon footprint is driving cloud optimization efforts in many organizations, especially now that environmental sustainability has become a growing concern. It is fortunate that reliability and carbon footprint improvement are often complementary—improving application reliability often leads to minimizing your carbon footprint.
The ideal cloud optimization strategy is to take a comprehensive approach when it comes to these three aspects. This way, your organization can build the optimal cloud. Your strategy will depend on your priorities and objectives.
Formulation of a Cloud Optimization Strategy
When building your cloud optimization strategy, it is necessary to have your engineering teams view cloud cost as a primary metric, especially when it comes to your applications and infrastructure. Thus, integration of your cloud optimization strategy into your development lifecycle is recommended. This ensures detection of potential scaling issues later, future-proofing your IT infrastructure.
However, cost is not solely the purview of your engineers—your finance team should be involved as well. This ensures that both teams are coordinated when it comes to your cloud services goals. Otherwise, you may find out about issues only when you receive the bill from your service provider.
You can divide the formulation of your cloud optimization into four stages, namely:
- Planning stage: During this stage, your teams collect usage and cost data. Make sure to compute the benefits that your cloud services provide. Are the costs commensurate with the returns? You also need to identify which areas need to be optimized.
- Deployment and operation stage: Once you have identified which areas can be optimized, it is time to remove unneeded components. Your teams can also add components at this stage.
- Design and build stage: Ensure that there is enough data on service costs so that you can decide where to make further adjustments when necessary.
- Monitoring stage: Refine the architecture further so that it would be easy to decide which service to expand or contract further.
Your cloud optimization strategy must be flexible enough that your teams can transition between these stages at any time.
Best Practices in Cloud Optimization
These are the best practices you can follow when it comes to cloud optimization.
- Review your needs and resize: Your team should plan for regular reviews of your application requirements so that you can resize accordingly when needed.
- Use automatization strategies: There are automation tools you can use to minimize manual errors when installing, configuring, and managing your cloud services. Make sure to use them.
- Schedule your workloads: As much as possible, limit your workloads to specific days or hours. If you can schedule them during normal working hours, the better. This way, you can shut down applications and services when they are not needed.
- Review your usage with analytics: Take a regular look at the dashboard and analytics from your cloud service provider. For more detailed information, you can also utilize a cloud management platform to perform this task.
- Remove redundant items: Ensure that your teams review applications and services regularly so that those no longer needed can be removed from your plan.
Parallels RAS: A Cost-Effective Cloud Optimization Solution
Parallels® Remote Application Server (RAS) supports multiple cloud solutions, including a hyper-converged infrastructure solution, which integrates compute, storage, and networking components into a single entity. Nutanix, HPE Hyper Converged, and Scale Computing HC3 are among the hyper-converged solutions supported by Parallels RAS
With hyperconverged technology, Parallels RAS can deploy virtual applications and desktops on-demand and create and deploy virtual machines (VMs) on the fly. These capabilities can prove to be a tremendous benefit to your company’s cloud optimization strategy. Moreover, since a software-defined datacenter means lower hardware requirements and cheaper systems to upgrade and maintain, hyperconverged solutions also help in your cost reduction efforts.
Integrate Parallels RAS to streamline your cloud optimization efforts!
