Ensuring your customers are operating within costs while maintaining high service standards can be a challenge in cloud computing. Yet, optimizing the cost is essential for managed service providers (MSPs) to protect their customers’ bottom line, and showcase value while cloud spending continues to rise. Using practical strategies, MSPs can help customers reduce expenses and maximize the value of cloud investments.
Right-size resources
Underutilized resources are a significant source of excess cloud costs for many businesses. When you over-provision cloud environments, you end up paying for resources your applications avoid fully leveraging.
For instance, provisioning large compute instances may seem like a way to ensure performance. But if your applications can’t fully utilize the available CPU and memory capacity, you’re essentially paying more for unused resources. As a result, you inflate your cloud expenses while missing out on a real performance advantage.
Right-sizing involves analyzing the current resource utilization and adjusting it to match the actual needs of the workload. This could mean scaling down over-provisioned instances or shifting to different instance types that align with performance requirements.
Tools like Amazon Web Services (AWS) Trusted Advisor and Azure Advisor can provide invaluable resource optimization recommendations. These platforms look at your usage patterns and suggest changes to improve efficiency.
Implement continuous monitoring and cost management tools
Continuous monitoring and cost management are critical for avoiding financial pitfalls, especially since 29 percent of businesses fail due to cash flow issues. In cloud operations, staying on top of costs is essential to prevent budget overruns and maintain profitability.
Several tools can help you provide real-time analytics to monitor expenses closely. This allows for timely adjustments that keep cloud spending in check and improve overall financial performance.
These tools function by offering detailed insights into cloud usage, breaking down costs by service, resource, and even time of day. They allow you to set budgets and create alerts when spending approaches predefined limits. Moreover, they examine usage patterns to discover inefficiencies, such as services that you could reallocate or scale down.
AWS Cost Explorer and Google Cloud’s Cost Management offer dashboards that visualize spending trends and forecast future costs based on current usage. This level of insight can help you make data-driven decisions that optimize cloud expenditures without sacrificing service quality.
Leverage auto-scaling
Auto-scaling can optimize cloud infrastructure by automatically adjusting resources in real-time based on demand. This strategy is especially useful considering more than 80 percent of container spend is wasted on idle resources, with 54 percent of this wasted spending attributable to cluster idle. Implementing auto-scaling can significantly reduce these inefficiencies, ensuring you only use resources when necessary.
Auto-scaling works by continuously monitoring resource utilization and scaling resources up or down based on predefined metrics. These metrics can be anything from CPU usage and memory consumption to the number of active sessions. For example, auto-scaling can increase the number of instances to handle the load during peak traffic times and maintain consistent performance. It will also decrease those instances during off-peak hours to cut costs.
Several tools like AWS offer autoscaling services to reduce wasteful spending and optimize your cloud operations.
Suggest the right pricing model
Selecting the appropriate pricing model optimizes cloud costs while maintaining flexibility and performance. With various pricing options available, it is crucial to understand how each model aligns with your specific workloads.
Two of the most commonly used pricing models are reserved instances and spot instances. Reserved instances offer a large discount. For example, AWS provides up to 72 percent off, but customers must commit to this type of instance over a one-year or three-year term. This model is ideal for stable, predictable workloads that run continuously. By locking in resources at a lower cost, your customers can achieve substantial savings on long-term cloud operations.
Conversely, spot instances allow customers to bid on spare cloud capacity at a significantly reduced price, sometimes up to 90 percent off the standard on-demand rates with AWS. However, the trade-off is that these instances can experience interruptions through the cloud provider with little notice.
Therefore, they are more suitable for flexible, non-critical workloads handling interruptions, such as batch processing or data analysis. Overall, spot instances can let you take advantage of cost savings while maintaining the ability to scale as needed.
Consider multi-cloud strategies
Relying on a single cloud provider for all services may be convenient but often leads to higher costs and potential redundancies. Instead of using multiple cloud providers, you can suggest customers to use various strengths and pricing models.
A benefit of a multi-cloud strategy is being able to avoid vendor lock-in. When this occurs, it limits the bargaining power. Customers often pay higher prices over time, especially as they depend more on that single provider. Therefore, distributing workloads across multiple cloud providers makes sense to negotiate better terms and pricing.
Additionally, a multi-cloud strategy will prevent the risk of service interruptions or outages. Provider-specific failures can be costly but diversifying your cloud environment will prevent those instances and enhance your operational continuity.
Maximizing cloud efficiency for long-term success
As you work to help customers manage cloud cost optimization, know that each strategy is vital to maximizing efficiency and profitability. There are several approaches you can take to manage customers’ cloud infrastructures. Consider trying a mixture of tactics to reduce expenses and ensure long-term mutual success.
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