How can you identify and eliminate unnecessary cloud expenses with the help of cloud cost optimization tools?

Continuously optimizing cloud costs is crucial to achieving your org's financial goals while building modern, scalable applications. Cloud providers offer various tools for cost optimization: 1. Cost Analytics: Understand spend, usage, and forecast costs 2. Budgets: Set custom budgets and alerts 3. Advisor: Real-time cost optimization guidance 4. Anomaly Detection: Detect unusual spending 5. Resource Tagging: Enable granular cost tracking Best practices include: - Right-sizing instances - Leveraging reserved instances & savings plans - Utilizing elasticity - Optimizing data transfer Regularly combining these tools & best practices helps identify & eliminate unnecessary expenses, ensuring cost-efficiency & performance in the long run.

You don't have to use cloud cost optimisation tools to save the cloud costs, here are the ways you can monitor and save the cloud costs. 1. Setup the limit and configure alerts that if the costs goes upto this amount, get alerts. 2. Don't limit/restrict the access till SREs/DevOps Engineers, give access of cost explorer (AWS) to the developers so that they can keep the costs in mind and develop a cost effective solution. 3. Setup a recurring meeting with respective stakeholders and review the spikes in the services cost, identify the causes of spike. 4. Periodically review the resources usage and right size the clusters/instances. Cloud cost optimisation is a continuous and iterative process.

Review Pricing and Billing Information. Cloud vendors provide billing details explaining the cost of cloud services. Set Budgets. ... Identify Unutilized Resources. ... Identify Idle Resources. ... Right-Size the Services. ... Use Reserved Instances. ... Use Savings Plans. ... Leverage Spot Instances.

Identifying Unused and Unattached Resources: Cloud cost optimization tools can help identify unused and unattached resources in the cloud infrastructure. These could be underutilized virtual machines, idle databases, or storage volumes that are not in use. Once identified, these resources can be decommissioned, thereby saving costs source. Rightsizing Cloud Resources: Cloud cost optimization tools can assist in 'rightsizing' your cloud resources. This involves aligning the capacity and performance of your cloud resources with the actual needs of your applications, thereby avoiding over-provisioning and wastage of resources.

Identifying and eliminating unnecessary cloud expenses is crucial for managing cloud costs effectively. Cloud cost optimization tools help manage cloud costs effectively by providing insights and control over expenditure, it gives a break down costs by service, region, project, and also identifying anomalies and high-cost areas. Gaining visibility into your cloud expenditure allows you to identify areas where resources are underutilized or redundant, perhaps leading to cost savings.

Consider using on-demand services, spot instances, and different zones based on the purpose, such as production, development, or internal testing. Some resources don't need to be running full time and can be made on-demand to save costs. Identify resources that will be there long term and reserve them to save up to 30% on costs. Sometimes, even a change in architecture like using lambda applications or going serverless might be useful for services that are event-based and not always running. Since this requires regular monitoring, it can be challenging to do manually, so using a tool can be beneficial.

Analyze your detailed billing reports to understand where your cloud spending is going. You can get this information from the billing dashboards of AWS, Azure, or Google cloud. To identify unused resources, use tools to identify idle resources such as unattached volumes, used IP addresses, and stopped instances that are still incurring costs. Detect underutilized resources, such as instances running at low CPU or memory usage. Right-sizing these instances can save costs. For future analysis, the best practice is to identify which resources are driving cost by implementing a robust tagging strategy to categorize resources by environment (e.g., production, staging), project, team, or cost center.

Identify underutilized resources. These can be instances running at low CPU utilization, storage volumes with minimal activity, or databases with low query rates.Either shutting them down or downsizing them can reduce unnecessary costs. Cost optimization tools offer setting up automated policies for cost control. For example: shutting down of non-production environment during non-business hours.

Cost optimization tools assess resource usage patterns, recommend improvements, and identify idle or infrequently used resources. Also it could include reducing over-provisioned resources or recommending other resource types that can accomplish the same task at a lower cost. By identifying these resources one can decide whether to shut the resources down or scale them, reducing excessive costs.

Purchasing Reserved Instances (RIs) can result in significant savings compared to normal on-demand pricing. Optimization tools can analyze usage pattern and recommend the most cost-effective RI purchases. For example AWS Reserved Instances (RIs) is a discount pricing model that enables organizations to save up to 75% on On-Demand Instances when they purchase them in advance for a fixed term of one or three years.

Spot instances are a great way to reduce costs by using spare cloud capacity. They are spare computing capacity offered by AWS at a significantly lower price compared to On-Demand instances. They are ideal for flexible workloads and can tolerate interruptions, as AWS can reclaim these instances with little notice. Users bid on unused EC2 instances, and when their bid price exceeds the current Spot price, their instance is terminated automatically. Spot instances are well-suited for applications such as data analysis, batch processing, and stateless web servers.

Spot instances are pricing model introduced by cloud computing providers, allowing users to bid on unused compute capacity at significant discounts compared to regular pricing. Spot instances offer significant cost savings, potentially saving up to 90% compared to on-demand pricing, making them ideal for businesses with large-scale computing needs but limited budgets. Spot Instances are cost-effective, flexible applications suitable for data analysis, batch jobs, background processing, and optional tasks, allowing for flexibility in application runtime and interruption. You pay the Spot price for Spot Instances,

Automate the start and stop of instances based on usage patterns. For example, stop non-essential instances during off-hours and activate essential instances when needed. This optimizes your costs, as AWS charges you by the hour. You can also use auto-scaling to dynamically adjust resource capacity based on demand, ensuring you are only paying for what you use. Set policies for resource usage and cost thresholds. Automation tools can enforce these policies, such as deleting old snapshots or scaling down underutilized resources.

A common mistake when automating in this area is to consider data from the cloud only. In our case, we consider both application metrics like users, requests, and performance, as well as infrastructure metrics such as resource utilization (CPU, memory, storage) and network traffic. Correlating this information with the cloud data can provide useful insights, which can guide actionable steps. This approach helps to reveal the real potential for cost savings.

Continuous monitoring in the cloud environment enables teams to swiftly respond to cost anomalies, thereby ensuring ongoing optimization and potential cost savings.

Cloud providers, such as Azure, AWS, and GCP, offer well-architected frameworks that include a cost pillar. Considering this and creating an organizational practice will be a good start.