How can you choose the right AWS pricing model for cost optimization?

AWS's simplest and most flexible pricing model charges you for resources on an as-you-go basis—compute, storage, or network—billed either by the hour or second, depending on the service. This on-demand model requires no upfront commitments or reservations, providing scalability based on your needs. Ideal for unpredictable or short-term workloads demanding control and flexibility, it's a straightforward but pricier option, with the highest rates applied to the resources you consume. While offering unparalleled adaptability, it's crucial to weigh this against the potential cost implications, making it a strategic choice for specific use cases.

On-demand pricing charges by the time the resource is used. On some companies, too small for RI o SP to be adecuate for their business model, on-demand pricing may be the only option so, in order to optimize costs, the options are switching on and off the servers, right-sizing, autoscaling configurations that allow to use the smallest tier possible on baseline demands and that can grow to absorb peaks. On other on-demand IaaS services, like S3, having a proper life-cycle configuration can help optimize costs on companies that have this pricing model as their only feasible option.

The Reserved Instances pricing model enables you to secure resources for a defined period, like one or three years, at a discounted rate compared to on-demand pricing. Offering variations such as standard, convertible, or scheduled reserved instances, it caters to diverse needs. Ideal for consistent or foreseeable workloads demanding long-term commitment and reliability, it comes with the trade-off of upfront or monthly installment payments. While cost-effective over the long run, the inflexibility of changing or canceling reservations should be considered, making it a strategic fit for stable and enduring workloads where predictability takes precedence.

The Spot Instances pricing model empowers you to bid for AWS's surplus resources at a discounted rate, with charges based on the current spot price dictated by supply and demand. Tailored for flexible or interruptible workloads tolerant of fluctuations and potential interruptions, it offers cost savings. However, the caveat is the potential loss of resources as AWS may reclaim them when the spot price surpasses your bid. While economically advantageous, this model requires a readiness for resource volatility, making it well-suited for workloads with resilience to intermittent interruptions and a focus on optimizing costs.

Spot Pricing is excellent when you have identified workloads that do not need 24/7 needs. Ideally, this should be decided based on the findings through your cost improvement measures in alignment with your organization's FinOps strategy. This can help to reduce overall cloud costs if used smartly when compared to reserving them But, it can be a nightmare if you choose the wrong workloads (especially workloads that have stable needs). You might end up with out-of-control costs for such workloads. So collaborate with your FinOps, procurement and engineering teams before you choose the workloads for SPOT pricing.

To optimize costs on AWS, understand your workload costs and compare pricing models. Use tools like AWS Cost Explorer to find discount opportunities. Understand the benefits of different pricing models like On-Demand and Spot Instances and dedicated discounts such as Savings Plans and Reserved Instances. Regularly adjust your capacity to match demand, especially for low-utilization EC2 instances. Remember, cost optimization is a continuous process.

Pricing models and terms can be unique to you and your agreements (EDPs are a good example) based on your workload forecast. Working with everyone involved in your cloud environment and operationalizing the FinOps principles is always a good starting point. This way, you can approach your account team as a unified front, talking on the same terms and working towards the same goals. Financial Commitments and planning can seem daunting, but remember that they (AWS) need you in their cloud just as much as you need a home for your workloads. AWS is a great partner when you approach problems in that way with a shared goal in mind.

Selecting the right AWS pricing model for cost optimisation involves assessing workload demands and criticality. Understand the resource needs of each workload, differentiating between non-production and production environments. Utilise diverse pricing models, such as Reserved Instances for predictability and Spot Instances for flexibility. Leverage autoscaling to dynamically adjust resources and consider Savings Plans for versatility. Regularly review and adapt your strategy, using AWS cost management tools. Aligning pricing choices with workload characteristics ensures cost efficiency without compromising performance, adapting to evolving business needs.

In my experience, I've never encountered adoption of a single pricing model by the entire organization, unless it's a start-up in early stages. Usually, it's a hybrid or a mix of pricing models. General Assumptions I follow if needed to choose fast: 1. Pay-per-Use: use it for event-driven architecture and microservices (Lambda) 2. Spot Instance: rare cases of workloads that are OK with interruptions 3. Reserved Instances (RIs) - fit you have B2B solution with pretty much consistent workloads 4. Savings Plan - Pretty much like a reserved instance, but gives more flexibility in resources and regions. Web apps with stable traffic. Maybe Databases 5. On-Demand: hard to predict I use for Test & Dev cases

AWS account teams can also support and guide on best options to consider based on needs. The AWS Marketplace also offers a variety of ISV and SI partner offerings to help with cost optimization in an automated format as well. For example: nOps automates selecting the appropriate RIs at the right time. SI partners have built-in offerings as part of their managed services where they take on the ongoing cost optimization efforts without the customers having to manage it on their own. The ultimate question to be answered is: do organizations have the team's available to manage cost optimization effectively or would they benefit from having the partner ecosystem support them?! I would recommend starting with the partner ecosystem first.

Cost optimization in AWS can be a double-edged sword. On one edge: They need to keep you optimized and functioning at the lowest possible cost with the resources you run. On the other: They are a for-profit organization, and have fiduciary duty to maximise their profits for investors and growth projections. This double sided interest sometimes can work for and against you (and occasionally both for and against at the same time) There are multiple vendors that can help you optimize your workloads while identifying waste and idle resources. You should use them if only to keep AWS honest in their dealings, ensuring your environment is optimized for both scale and performance while ensuring that your cloud spend is maintained correctly.

In cost optimization, one key thing to note is that one size does not fit all and there may be moments where your workloads could easily work with Spot instances and at other times with Reserved instances. The key thing is to understand which works best and even go ahead to employ a mix of the different pricing options to have the best of 'both worlds' within your workloads.