What is Cloud Cost Optimization? 12 Best practices to cut your Cloud bill
Higher costs become unavoidable if you stuff more than what you can chew. Among a large number of end users, cloud technology enables scalable on-demand resources and cost-sharing. It allows end-users to store, process, and manage data efficiently at very high speeds. However, some enterprises complained of facing amplified costs and they are looking for ways to lessen their cloud spend. A Gartner report estimates that around 70% of the cloud costs are wasted. Cloud cost optimization is possible to attain by recognizing and alleviating suboptimal cloud infrastructure provisioning and creating the finest practices of cloud financial management. This blog will explain what cloud optimization is, look at the factors causing the surge in expenses, and offer tips on cloud cost optimization.
What is Cloud Cost Optimization?
Cloud cost optimization certifies the most cost-efficient and appropriate cloud resources allocated to each application or workload. It balances the necessary security, compliance, cost, and performance requirements to ensure cloud investments are suitable and optimal for organizational requirements. It involves identification, resource analysis, management, and monitoring instances for optimized cloud costs.
In a cloud deployment, every workload is unique, and its needs evolve over time. To elevate the cloud cost, you must identify the performance verges for each workload on the basis of actual operational metrics and domain gen. Optimization reduces cost while certifying that performance thresholds are met.
Responding to constantly changing cloud service and pricing options and responding to changing application needs, cloud cost optimization is dynamic. Cloud cost optimization needs detailed analytics, metrics, and automated tools because of the enormous complexity of cloud environments.
Reasons for higher cloud costs
Cloud-based solutions, like every other solution, can overwhelm the budget of your organization if not optimized properly. Below mentioned are the reasons for higher cloud costs:
Issues with Poor Visibility
Cloud monitoring is the key to the success of a business, as poor visibility may lead to high costs. As per a survey, 82% of cloud and IT decision-makers said they suffered superfluous cloud costs. 71% of respondents cited the lack of visibility being one of the top reasons. There are innumerable reasons for lowly visibility on the cloud, such as problems with opaque containers, lack of authority, and blind spots. Apart from this, with changing customer demands and rapid cloud adoption, the predictability of cloud costs is interrupted.
Previously monitoring was easy to predict and delivered the advantages of single pricing, has now become complex. The fluctuation of cloud spending on the basis of agility requirements and customers’ needs makes it quite challenging to manage. Apart from this, a further lack of visibility and governance makes cloud resources opaque resulting in unnecessary costs
Issues with Overprovisioning
Overprovisioning means organizations are spending more on cloud resources than what is needed. When instances run idle, the load is low, leading to higher costs. The best way to shrink overprovisioning costs is to recognize underutilized resources, check for memory leaks, and dismiss sluggish instances. Several organizations choose to overprovision resources and cloud-first approach. Overprovisioning is not the sole issue when you go for a cloud-first approach. Data gravity has been a major challenge that has to be overcome.
Issues with Data Gravity
Often it is easier for businesses to transmit and store a large amounts of data on the cloud instead of on the premises. This may lead to a data gravity phenomenon where, at first, more data moves to the cloud. With organizations becoming more efficient with their resources, they use on-premises systems. Thus, businesses end up spending on paying for data migration to the cloud and then back to one on-premise setup. This is a highly costly and inefficient approach. One way of avoiding data gravity is having a project infrastructure management plan.
Issues with the Complexity of cloud contracts
Before signing them, cloud contracts need thorough analysis as they are complex. Moreover, most businesses are not aware of the hidden costs of cloud contracts and end up paying more. So, there is a need of an expert in cloud assessment to help you figure out pricing structures and contracts. Moreover, you need to analyze the terms of data compliance requirements, data ownership, and cloud contracts. For a business wishing to opt out of the services, cloud contracts must explain the exit strategies. It must also include add-on details such as data transmission and connectivity costs.
Cloud pricing may be an opaque and complex process. This may lead businesses to spend maximum time researching the best deals or directly negotiating with providers. Some cloud calculators need knowledge of computing resources such as the details of workloads, type of instances, ram, and cache size. Because of this, it becomes quite overwhelming for a CFO or CEO with limited technical knowledge of using these calculators. Another key challenge is to keep yourself updated with the price fluctuations of cloud services. Unfortunately, several organizations have to be aware of price hikes and tend to spend more on instances that increase cloud costs.
Best Practices for Cloud Cost Optimization
1. Optimizing the cost at every stage of the Software Development Lifecycle
Optimizing cost at every stage is the key to reducing the expenses on the cloud. Optimizing cloud costs at every SDLC stage needs system monitoring, data tracking, and continuous assessment throughout the lifecycle. So, you may apply cloud cost optimization at various phases of SDLC.
Planning: Plan the process of software development and, for critical decisions to avoid tech debts, use a data-driven approach. The planning stage involves cost analysis, assessing system requirements, and a framework created for the process of development.
Design and Build: The design process needs data analysis for cloud-based applications. So, you must analyze key data points such as the architecture, what they must be, and how they will impact the app performance. Also, you need to analyze the required cloud computing resources and the app architecture cost.
Deployment and Operation: You need to analyze the ROI and the operational expenses of the product developed at the development stage. Also, you must consider the cost of plan automation and cloud deployment to improve competence.
Monitoring the maintenance and performance costs: The key to ensuring better ROI is monitoring the performance and application costs. So, you need to analyze the app’s performance and behavior to define metrics. It will help you reduce expenses on maintenance costs and error rectification.
2. Conducting performance analysis and implementing continuous monitoring
Switching to pay-as-you-go or dynamic pricing will save money in many cases. You have to utilize the reporting features of a Cloud Service Provider to achieve these savings and conduct an in-depth performance analysis. The CSP data lets you know how well the application has been executing in the cloud, however, measures the experience of the end users. You will have to identify and configure your reporting tools to aim at those performance metrics that mean the maximum of your users. After a proper analysis of the application services, the peaks, resources, and users will display a clear image of whether the application will be profitable in the cloud.
Cloud Service Providers provide cost optimization tools, but the I/O team must have a real understanding of the environment. They must monitor what specs to what servers are being built continually. The reports and tools that you put for analysis form the pillar of continuous monitoring. To control costs and ensure performance, set up automated actions and alerts.
3. Investing in automation
You can take advantage of the auto-scaling as well as other automation services that your CSP provides with the wealth of data captured by your monitoring. You need to ensure that the automation you configure scales up and down. An example of this is the development systems that are used during the workday only. To turn off these systems during weekends or nights, you may set up automation so that you do not pay for the 60% of the time when anybody is not using the systems.
4. Using cloud cost as a system of measurement
When businesses keep cloud costs as a priority, they can build principles of optimizing cloud-based expenses. As a metric, cloud costs need to define key areas where organizations optimize, measure, and monitor costs. Some key areas involved are- Enablement and accountability: This is a foundational pillar to implement cloud costs as the metric culture. It aims at streamlining the financial processes for accelerating business value and accountability. Cloud enablement is a vital metric, and you can measure that in percentage.
Realization and measurement of cloud costs: It involves identifying IT-driven designators, tagging data architecture, and resource hierarchy. This pillar aims at cloud resource attributions via consistent tagging. This enables organizations to identify cloud cost centers. For this pillar, companies can measure cloud allocation in percentage.
Planning and forecasting: Because of the strategic standing of cloud cost optimization, this is a vital pillar of cloud costs. This pillar aims to create a computational budget and plan the resource requirements. So, annually you have to estimate the cloud computing costs. The calculation of annual forecast accuracy involves assessing monthly budget variances, trend-based models for steady-state workloads, and workload forecasting models.
Accelerators and tools: This pillar aims at identifying the accelerators of cloud costs and detailed analytics reports of resource tagging.
5. Identifying the cost irregularities
Identification of cloud costs needs monitoring predefined metrics and tools. Some of the vital cloud cost metrics that you have to focus on include:
Uptime: This metric helps measure the time for which a system is available for serving user requests.
Memory Utilization: This helps the memory used in private, public, and hybrid cloud environments.
CPU Utilization: This helps measure the computed percentage used for processing a user request and completing a specific task.
Disk usage: This metric enables you to track the amount of disk volume used on a node. It helps to determine whether a storage activity is pretty enough for workloads.
Requests per minute: This is the number of user requests a cloud-based app receives each minute.
Latency: This is a difference in time between the request and response. Simply put, this is the time that the user sends a request and a response is received.
Average time to acknowledge: This metric helps measure the time your system needs to respond to a user request.
MTTR (Mean time to repair): This metric helps you to find the time required for a system to restore the services after a failure. For cloud cost optimizations, a shorter MTTR is desirable as it reduces downtime costs.
MTBF (Mean time between failure): This is the average time that an application or a system takes from one failure to another. This helps in determining when cloud computing works before failing.
Top cloud monitoring tools
The tools mentioned below provide data insights and analytics in a visual format. This makes cloud cost optimization quite unique. The tools are:
Harness: This is a platform that has a pre-built cloud cost management module focused on enhancing resource efficiency, governance, and transparency.
Kubecost: This cloud-cost management tool enables users to generate accurate reports to locate cost anomalies by monitoring resource allocation.
CastAI: This is a platform that helps in optimizing, analyzing, and monitoring Kubernetes apps. It enables you to automate cloud optimization through instance selection, rightsizing, and autoscaling of resources.
Cloudchekr: This cloud cost monitoring tool helps to monitor, track, and report the main expenses for your applications. Moreover, it leverages the data recorded for creating policy-based automation.
Cloudability: This is a cloud optimization and monitoring tool that collects key data from the previous 10-30 days on resource usage. Moreover, it leverages algorithms to offer rightsizing recommendations.
6. Rightsizing the resources
The process of rightsizing involves analyzing computing instances, switching off these instances to optimize cloud costs, and identifying idle resources. Moreover, it involves matching the cloud resources with the proper workload and rightsizing the overprovisioned instances. Knowing how to rightsize instances, your savings on the cloud cost will go above 70%. Cloud providers have some pre-built features to rightsize instances and optimize cloud costs.
For instance, AWS provides reserved and spot instances that users can utilize to optimize cloud costs. Spot instances are backup that enables users to utilize the idle EC2 capacity instead of spending too much on on-demand resources. You can rightsize instances and optimize your cloud costs by using reserved resources. AWS offers reserved instances that can be used to reduce cloud costs. To optimize resource provisioning, rightsizing is also important.
7. Reducing excess storage
Storage utilization is the biggest factor that drives the costs in cloud IT up. Business habits and IT culture can push many duplicate data and create redundancies that drive up costs exponentially. Simple adjustments in how data is versioned and copied will need re-educating staff on processes for making it more cost-effective while utilizing cloud storage. For cloud storage infrastructure, pricing models include monthly fees for cost per GB of stored capacity. Cloud storage has to be optimized through various storage tiers in the cloud, with data aging in its lifecycle. Ensure that the provider has transparent pricing that guarantees every factor and rises in cost with the growth of usage.
8. Identifying overprovisioning
The enhanced monitoring put in place for leveraging vibrant pricing will categorize where you have been overprovisioning funds. This is true, especially when you have migrated applications from keen physical servers in the cloud to virtual servers. The average physical server that supports one app is underutilized in the data center. The extensive adoption of server visualization determines this. Also, you may see improvements in the speed of the CPU, the data bus, and the memory speed in your cloud environment.
9. Optimizing resource provisioning
Resource provisioning needs analysis of the system. To create a resource requirement plan, you need to analyze the workloads. For optimized provisioning, you need to ask a few questions, such as how much it can cost to make a feature; for feature allocation, what is the extent of resource allocation; the type of resources it will need; how much is the usage of cloud storage is required to acquire a new customer; what will product or service development cost be on the cloud, the type of products or services do customer seek; the cost of operations number of resources required to keep the operational downtime lower; the type of workload required that you may need to and deploy provision, the cost of migrating a system to a cloud environment, and the cost of deploying the application on the cloud.
10. Leveraging a hybrid strategy
Vendor lock-in might be a challenge to your cloud cost optimization. While using a single cloud provider for all resource needs, there are chances that you might face specific restrictions. Like, some cloud service providers offer services not compatible with external services. Cloud costs that surge because of changes in pricing are another significant issue. Cloud cost increase because of dependency on a single vendor and interoperability issues. So, leveraging a hybrid cloud strategy is the best way. A hybrid cloud strategy is where organizations leverage several environments to run apps.
11. Simplifying cloud contracts
The key to reducing costs is simplifying cloud contracts, as there are various hidden expenses and clauses that can go unnoticed. Cloud contracts require proper breakdowns and assessments by consultants to avoid overhead costs. Some essential things to be considered while signing a cloud contract. This includes analyzing the cloud cost breakdown; researching the contractor for any add-ons, capacity information, and hidden expenses; understanding the migration policies and data ownership clauses; ensuring security measures in the contract; and looking for service-based clauses and SLA availability.
12. Paying attention to software licenses
Often software licenses are limited to use in particular environments. This means that if you are using licenses currently that were bought for your on-premise infrastructure, you cannot use the same licenses in the cloud. It requires creating an inventory of licenses, gain insight into the insights, and determine appropriate licenses per your budget. There are cases where you can reduce the cost of licensing by leveraging a cloud service such as Azure Hybrid Benefit. Helping you bring your own license to the cloud helps you save costs.
Optimizing the cloud costs needs engineering excellence, the right scaling of instances, an understanding of pricing, and cloud services. Choosing the perfect cloud service provider can help in optimizing cloud costs. You can leverage various cloud service providers through a hybrid method for optimized cloud costs. Combining the development strategies, business processes, and technical methodologies into a unified understanding of the cloud will be key to your success. Organizations that embrace the cloud and the culture and operational changes that go with its position their offerings for growth in a competitive marketplace. Get in touch with the cloud experts now and reap the advantages of cloud cost optimizations!