How Can Developers Contribute Towards Cloud Cost Optimization?
In this article, we will discover how developers can optimize cloud costs by implementing cost-efficient coding practices and leveraging cloud-native tools.
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Cloud cost optimization refers to the process of analyzing resources to identify areas where unused or wasted resources can be optimized to reduce expenses. This involves a variety of tasks, including resource analysis, identification, monitoring, and management of instances. However, the process of optimizing cloud costs doesn’t end with resource monitoring and management. It’s important to take a holistic view of cloud costs for every phase of the software development lifecycle (SDLC). Achieving cost optimization at each stage requires careful monitoring and visualization of data.
Cloud cost optimization process is dynamic and requires continuous assessment of cloud resources, pricing, and changing business requirements. Here is how developers can apply cloud cost optimization to different phases of SDLC.
Use Cloud Cost as a Metric
By making cloud costs a priority, businesses can create a culture that emphasizes optimizing cloud-based expenses. To achieve this, organizations need to define key areas where they can monitor, measure, and optimize cloud costs. Some of these key areas include:
- One of the foundational pillars for implementing a culture of cloud cost optimization is “Accountability and Enablement.” This pillar focuses on streamlining financial processes to promote financial accountability and business value. Cloud enablement is a crucial metric for this pillar and can be measured as a percentage.
- The second pillar is “Measurement of Cloud Costs and Realization.” This pillar involves defining resource hierarchy, tagging data architecture, and identifying IT-driven designators. It focuses on attributing cloud resources through consistent tagging, which enables organizations to identify cloud cost centers. Companies can measure cloud allocation metrics for this pillar as a percentage.
- The “Planning and Forecasting” pillar is crucial for cloud cost optimization due to the strategic importance of forecasting. This pillar focuses on planning resource requirements and creating a computational budget, requiring the estimation of annual cloud computing costs. Annual forecast accuracy can be used as a lead metric and measured as a percentage. This includes assessing workload forecasting models, trend-based models for steady-state workloads, and monthly budget variances.
- The final pillar is “Tools and Accelerators,” which focuses on detailed analytics reports of resource tagging and identifying the accelerators of cloud costs. It helps organizations measure the percentage of automation implemented from the analytics tool’s recommendations after analyzing the tagged resources.
Identify Cost Anomalies
Identifying the cloud costs needs monitoring tools and predefined metrics. Some of the critical cloud cost metrics you need to focus on are:
- Uptime: measuring the time for which a system is available to serve user requests.
- CPU utilization: measuring the computed percentage used for completing a specific task or processing a user request.
- Memory usage: measuring the memory used in public, private, and hybrid cloud environments.
- Requests per minute: measuring the number of user requests a cloud-based app will receive every minute.
- Disk usage: tracking the amount of disk volume used on a node and determining whether the storage capacity is enough for workloads.
- Average time to acknowledge: measuring your system’s time to respond to a user request.
- Latency: measuring the time between a request time and a response time.
- Mean time between failure (MTBF): measuring the average time a system or application takes from one failure to another.
- Mean time to repair (MTTR): measuring the time needed for a system to restore services after failure. A shorter MTTR is desirable for cloud cost optimization as it reduces downtime costs.
Rightsize the Resources
Rightsizing is an essential process that involves analyzing computing instances, identifying idle resources, and deactivating such instances to optimize cloud costs. Additionally, it includes matching cloud resources with workloads and right-sizing overprovisioned instances.
Effective rightsizing can result in cloud cost savings of up to 70%, making it a critical practice for organizations. Cloud providers offer pre-built features, enabling users to optimize cloud costs and rightsize instances. For instance, AWS provides spot and reserved instances that help in cloud cost optimization. Spot instances enable users to utilize idle EC2 capacity rather than incurring high costs on on-demand resources.
Webbeds, a leading travel accommodation provider, is an excellent example of a company that leveraged spot instances during the pandemic. By migrating its infrastructure to spot instances in 2020, Webbeds achieved a 64% reduction in cloud costs and improved CPU performance by 40%.
Using reserved resources is another approach that can help in optimizing cloud costs and right-sizing instances. AWS, for instance, provides reserved instances that can significantly reduce cloud costs. Similarly, the Google Cloud Platform offers Google Committed Use Discounts for cloud cost optimization.
Leverage Hybrid Strategy
Vendor lock-in can be a challenge to your cloud cost optimizations. When you use a single cloud service provider for all your resource requirements, chances are there will be specific restrictions. For example, many cloud service providers offer services that are not compatible with external services.
Another significant issue is cloud costs that surge due to changes in pricing. Due to interoperability issues and dependency on a single vendor, cloud costs increase. So, the best way is to leverage a hybrid cloud strategy.
A hybrid cloud approach is where organizations leverage multiple environments to run apps. For example, you can use public cloud infrastructure for specific services and private cloud services for others.
Take the example of British Petroleum’s (BP)’s hybrid cloud approach. The oil giant had a vast network of data centers across seventy-three countries. As a part of the cloud-first approach, it migrated many applications to Microsoft Azure.
However, there were remote locations for which complete lift and shift of the applications were not economically feasible. So, it leveraged a hybrid approach for cloud cost optimization.
Optimizing your cloud costs is not just about cutting corners and reducing expenses, but rather a strategic approach to creating value and enhancing business performance. With the right tools and methodologies, you can achieve significant cost savings, improve resource utilization, and deliver better customer experiences. So, whether you are a small startup or a large enterprise, make cloud cost optimization a top priority and watch your business soar to new heights in the cloud.
Published at DZone with permission of Hiren Dhaduk. See the original article here.
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