How can you optimize IaaS costs over time?

We can consider below IaaS Service Optimization Techniques that ultimately help to reduce your IaaS cloud cost. - Select Right-sizing Instances - Leverage auto-scaling features - Use Reserved Instances - Utilize spot instances for non-critical workloads - Use Right Tiered Storage Classes - Implement Lifecycle Policies for storage - Regularly Review your storage and delete unused data - Optimize Data Transfer cost by leverage CDNs - Use FREE Cloud-native Cost Management Tools by hyperscalers (AWS, Azure, GCP, OCI, any other ) - Leverage Peer-to-Peer (P2P) Networking

Make Your IaaS Budget Smile! ?? I'd advise: - Assess your needs thoroughly – like planning a perfect road trip. ??? - Shop around for providers and plans – think of it as cloud bargain hunting. ?? - Monitor usage closely; monitoring tools are your best pals. ?? - Embrace automation for smarter resource management. ?? - Don't shy away from exploring new tech solutions – be a cloud pioneer! ?? - Regularly revisit your contract – it's like a health check for your cloud spend. ?? Pro Tip: Use CloudHealth for comprehensive cost management and optimization! ??

Most of the things are covered by rest of the industry experts; I will add just 1 perspective. Think carefully if you really need IaaS; if its a very heavy application running on prem, 24*7 say like 4 node RAC cluster or Infiniband based low latency application; its much better to go with Capex based approach rather than Opex as in cloud. Just for the sake of moving to the cloud; don't do it. If data center exit is the only option or strategy then look for colo facility. But definitely not everything is for cloud. If we are into IaaS in cloud; then we know how the cost will look like but its worth estimating it before moving rather than later always works well.

Begin optimizing IaaS costs by keenly assessing your needs. Regularly review resource usage, eliminate redundancies, and align infrastructure with actual requirements. This dynamic evaluation ensures a cost-efficient IaaS tailored to your evolving business demands.

Dynamic infrastructure is cheaper than static infrastructure. Cloud infrastructure costs a lot less when it's not running. Can your business turn things off? Step 1 is to identify opportunities for dynamic infrastructure: can "daily" batch jobs run at any hour of the day, or must they run at a certain time? Can you access auction-based pricing to run batch workloads at cheaper times of day? Can non-production infrastructure be turned off at night or on weekends/holidays? Step 2 is to look at horizontal versus vertical scaling. Sometimes a fleet of small VMs/instances is the right answer (horizontal scaling). Sometimes one big system is cheaper than many small ones (vertical scaling).

- Go through the different pricing models offered by the provider. This can include pricing of pay as you go service, reserved instances, spot instances or even pricing based on enterprise contracts. - Use of reserved resources when load pattern is predictable - Use of spot instances for workloads that are flexible.

To manage costs effectively, users must plan, select appropriate regions, pricing models, and resources. Key factors influencing costs include pricing models, resource types, services, location, and Azure billing zones. Optimal cost optimization strategies include moving workloads to containers for efficient resource usage, leveraging serverless computing with Azure Functions for on-demand scalability, and implementing resource tagging for better tracking and shutdown strategies. Storage tiering in Azure Blob Storage provides cost-effective options by moving less critical or infrequently accessed data to lower-cost tiers.

Cost = Usage * Rate. I’d recommend focussing almost all your internal effort on optimising usage, and outsource the rate optimisation. Two reasons: 1) the highest savings come from turning off unneeded usage, but clearly internal knowledge and access is required to make this saving. 2) rate optimisation should be done little-and-often - a distraction when done internally - committing as usage increases, using a blend of commitment types and terms. A good outsourced provider of rate optimisation can effectively offer a free service, as they can commit far more effectively building far more flexibility than an internal team doing occasional sprints

Cloud providers also provide discounts if computes are used over a sustained period of times, i.e. sustained used discounts. One key pattern is using instance groups behind a load balancer and scale them based upon workload and resource utilisation. With careful monitoring and identifying minimum usage of computes you can decide to run them continuously over a period of time to use SUDs and scale resources whenever needed. Also time based scaling can help reduce IaaS costs in certain cases where you can reduce computes for those periods when workloads are thin, e.g. over weekends depending upon your business.

Choosing the right pricing model is a task that can start already during the initial assessment. Aligning the pricing model with the workload criticality is important from the beginning i.e. : use the highest SLAs for business critical applications, accept downgraded SLA for development and training purposes. Invest in reserved capacity for workloads with higher levels of predictability and use pay-as-you-go to burst extra capacity. FinOps activities are needed once migrated in the public cloud, there is always an optimization opportunity that will allow you to reinvest in innovation projects.

Implement auto-scaling to automatically adjust the number of resources based on demand. This ensures that you have the necessary capacity during peak times and can scale down during periods of lower demand. Be mindful of data transfer costs, especially if your application involves a lot of data transfer between regions or outside the cloud provider's network. Optimize data transfer patterns where possible. Such as for storage, there are often egress costs as well! Last but not least, ensure that your team is aware of cost implications and best practices. Provide training on resource optimization and encourage a culture of cost consciousness.

Implement and rigorously manage a full blooded orchestrator/Automator and in parallel a fully capable hybrid cost optimiser/reporting tool - if you can't see it you can't measure it; if you can't measure it you can't improve on it, and to really improve on it automate the heck out of it because people make mistakes. Then keep regularly revisiting and optimising; nothing is static especially not costs!

Optimize your usage 1. Conducting a review by figuring out what the usage is how it's trending with time. 2. Identify resources that are underutilized or over utilized. 3. Use of tag to associate cost between different teams or areas 4. Use of reserved instances if the load is predictable.

To optimize cloud costs, use automated tools for tracking, set budget alerts, and analyze usage patterns. Rightsize instances, utilize reserved and spot instances, and implement dynamic scaling policies. Embrace serverless architectures and leverage cost-effective services. Explore discounts and commitment-based pricing options. Conduct regular audits to identify and eliminate unused resources, and foster a cost-conscious culture within the team for ongoing optimization.

The majority of the Hyper scalers cloud providers have tools like #Azureadvisor that can help you optimize and improve efficiency by identifying idle and underutilized resources. You can follow optimization recommendations to identify potential inefficiencies and act on a recommendation to resize a virtual machine and benefit from a more cost-effective option.

Using cloud-native features means moving away from IaaS in many cases, and to PaaS or SaaS. IaaS offerings, regardless of the cloud privder, still have a relatively large Total Cost of Ownership (TCO). When you calculate TCO for more managed services, it more than balances out the slightly higher cost of that cloud's monthly bill.

Cloud native features might seem costly was a starting point but they are designed to provide performance and scalability for future growth. Over time, cloud native features can be utilized to optimize cost as one scales. Additionally one can use monitoring tools provided by the provider to optimize for cost. For example, the user can configure alerts based on certain usage that doesn't match the pattern or for usage when the bill of an account exceeds a predetermined number.

Leveraging cloud-native features like auto-scaling, spot instances, and reserved instances can optimize IaaS costs. Auto-scaling allows automatically adding or removing resources to match demand, ensuring you run just enough capacity needed. Spot instances utilize unused EC2 capacity for up to 90% savings on workloads with flexible start/stop. Reserved Instances provide significant discounts on resources used steadily by reserving capacity upfront or monthly. Monitor usage patterns and leverage these built-in cloud features to automatically scale, utilize discounted transient capacity, and reserve steady-state resources. Cloud-native optimization features align resource usage and spending with actual demand.

Optimizing IaaS costs over time includes leveraging cloud-native features like storage tiers, load balancers, auto-scaling, and serverless functions. These features can streamline operations, boost performance, and cut costs. Storage tiers save money by matching cost to data access frequency, load balancers distribute traffic to enhance reliability, auto-scaling adjusts resources to meet real-time demand, and serverless functions offer a pay-per-use model, eliminating server management overhead. Utilizing these features smartly aligns spending with actual usage and need.

Features like storage tiers, load balancers, auto-scaling groups, and serverless functions streamline operational complexities, elevate performance, and cut costs. Storage tiers facilitate data migration to cost-effective or high-speed storage based on access frequency. Load balancers enhance availability by distributing traffic across servers. Auto-scaling groups dynamically adjust resources to fluctuating loads. Serverless functions enable server-free code execution, billed solely for actual execution time. Leveraging these features aligns operations with cloud dynamics, fostering efficiency and cost-effectiveness.

One thing I've found helpful is understanding the factors that can affect costs in Azure, such as resource type, consumption, maintenance, geography, and subscription type. For instance, understanding the cost implications of different resource types and their settings, including the Azure region, can help you make cost-effective choices.

Reassessing your cloud provider every 2-3 years is a smart move. The cloud landscape evolves rapidly, and what was a good fit a few years ago might not be the best choice now. Regular reassessment can reveal opportunities for savings or more suitable services. Additionally, being aware of competitive pricing in the market can be a powerful negotiation tool. You might find that your current provider is willing to offer discounts or improved terms to retain your business, especially when they know you're considering other options. This strategy can lead to cost savings without the hassle of migrating to a new platform. It's all about staying informed and using that knowledge to your advantage.

Don't shy away from renegotiating for better terms like discounts or credits based on your usage and loyalty. Regularly check your cloud contracts to ensure they still fit your needs.

Reviewing your cloud contracts annually and renegotiating terms is a key way to optimize costs. Analyze usage data to rightsize services. Renegotiate for reserved instance discounts if workloads are steady. Seek volume discounts as usage grows. Lock in lower rates with 1-3 year terms. Consider paying annually vs. monthly to reduce fees. Leverage spend thresholds for credits. Consolidate services for bundled pricing. Monitor service changes and redeploy if costs increase. Keep an open dialogue with providers for custom solutions. With ongoing contract reviews and negotiations, you can ensure cloud spend aligns with usage and business needs.

To manage IaaS costs effectively, periodically review and renegotiate contracts with your provider. Assess whether current terms meet your evolving needs and seek renegotiation for potential discounts, credits, or refunds, reflecting your usage and loyalty. This proactive approach can secure optimal value and prevent overspending on redundant or undisclosed services. Regular contract assessments ensure alignment with your organization's requirements and financial efficiency.

Be careful of doing these although its definitely good to keep an eye on alternatives. The likelihood is that you don't want to mess up something that is already setup, working and glitch-free. The downside is even more costs (not just in dollars and cents) if something breaks down from executing an alternative. Then again, do your cost-benefit analysis. When there are risks, manage it. Reduce the risks so that if something happens, it will not be impactful enough to cause unwanted outcomes. Nonetheless, there are always unexpected outcomes so see if you can get an experienced hand on that!

One can explore switching to a different provider if the current provider doesn't fulfill all the needs. Alternatively, if the growth is predictable and scalability is of needs, it might make more sense to move to a hybrid model. One can also utilize open source solution inlace of the commercial one offered by the provider.

Sustaining IaaS cost optimization involves a willingness to explore alternative solutions. Embrace emerging technologies, innovations, or providers that may offer superior or more cost-effective IaaS solutions. Consider hybrid or multi-cloud strategies to harness the strengths of different cloud environments, mitigating risks associated with vendor lock-in, downtime, or compliance. This proactive stance not only keeps you competitive but also positions you to capitalize on the latest trends and opportunities in the dynamic realm of cloud computing.

Assess whether services like AWS Lambda, Fargate, or App Runner could replace provisioned EC2 instances to only pay for compute when needed. Consider database services like DynamoDB or Aurora that auto-scale and charge per usage rather than provisioned capacity. Analyze if storage services like S3 or EFS could replace dedicated storage volumes. Evaluate using modern application architectures like serverless and containers to drive efficiency and savings. Remain open to new services, features, and architectures as they emerge. The cloud evolves rapidly, and being willing to explore, test, and adopt new approaches and alternatives is critical for realizing the best value and optimizing IaaS spending.

To optimize IaaS expenses, stay attuned to emerging technologies and alternative providers that may offer more cost-effective solutions. Consider adopting hybrid or multi-cloud strategies to exploit the strengths of different environments, mitigate downtime, and prevent vendor lock-in. Such strategic flexibility can provide competitive advantages and ensure alignment with the latest cloud computing trends and opportunities, leading to potential cost savings and enhanced service quality.

In my experience, the only way to really save cost on Cloud is to move out of Cloud :) But some options to save a couple of bucks on IaaS would be: 1. To use resource(CPU, IOPS) level monitoring to fan-in and fan-out. 2. Modernising your application is not always the right solution, migrating to the new containerised architecture might cost you 3 times than your previous architecture. 3. Leverage cloud services like Monitoring and Error Reporting for absolutely Free. 4. For containers, on a very broad level, use right metrics(different) for VPA, HPA. Choose the right autoscaler type. 5. Doing a simple analysis of your previous quarter spend can put you in right direction.

The first step is to establish continuous monitoring of IaaS usage and conduct regular data analysis to identify key areas for cost reduction, such as data transfer, storage, or computing. In my experience, storage often receives inadequate attention. Inefficient use of storage tiers and failure to effectively clean up or archive old data are common issues. Addressing these can be a quick win for many. Consider offloading parts of your system to more affordable cloud providers. Exploring beyond standard providers can yield cheaper options for compute, storage, and GPU. Integrating these alternatives can significantly reduce your overall cloud expenses.

Great insights and responses by fellow contributors. Cloud IaaS cost optimisation should be Rinse and Repeat approach and so Cloud FinOps should be an integral part of Cloud Center of Excellence. The Cloud FinOps Governance team should not only measure and report the dollar ?? leakage but track it back to users who are using these cloud resources. Tagging and Resource mapping is very important and if this can be clubbed with chargeback and credits, it will be an icing on cake??

Here're more ways you can assess your use which is the most important step to optimising IaaS costs over time. Map the dependencies between different components of your applications. Understand how various components interact can help in making informed decisions about resource allocation and optimizing for performance. Develop cost models to estimate the expenses associated with different resource configurations. This allows you to simulate different scenarios and choose the most cost-effective options for your specific needs. Leverage predictive analytics to forecast future resource needs based on historical data and trends. Machine learning models can help in predicting future workloads and optimizing resource allocation accordingly.

When migrating towards the public cloud, the best optimization possible is by leading with SaaS first, PaaS, and, for the more specific needs like legacy or tailored-made applications, IaaS seems the most convenient option. The beauty of the cloud offerings is that every organization can make its own recipe, while combining all these options to optimize time to market, innovation, price for value, scale-up and down capabilities, increased security and compliance with local, regional or industry standards. The most important question is: "What is the expected outcome when moving to the cloud" so we can make sure the solution will fulfill the business expectations.