Imagine accidentally spending USD 65,000 on AWS. One way to do that is by allocating your in-house devs with little to no experience in platform engineering or site reliability to conduct experiments on your cloud.

Hanlon’s razor is sufficient to cover this use case —

Never attribute to malice, that, which can adequately be explained by stupidity.

But even experts can make mistakes with too much confidence in their own automation scripts and systems; like this infamous case of a startup founder who, while working with his AWS “expert” ended up spending USD 80,000 overnight.

On the flip side, there are success stories of teams, like Pinterest, that are actively in pursuit of cloud cost optimisation and drastically reduce their liabilities arising due to lack thereof.

Reasons why your cloud costs may blow up

We'll cover 2 common scenarios of why this may happen – first, when you have a well designed cloud architecture but its implemented poorly - second, if the architecture is poorly designed to begin with.

Even though there's a clear third scenario of teams with good architecture and great implementation of it – those are mostly very use-case specific issues like the ones Segment faced, back in 2017. Although interesting to look at, they may not apply to every business.

Lets dig in –

Scenario 1: You have a well-designed cloud architecture but poor implementation

For teams that have a sound cloud architecture already designed, problems may arise in the following areas — especially due to inadequate implementation.

1. Over-provisioning: Sometimes, we just go overboard with resources, thinking more is better. But in the cloud, unused resources equal wasted money. So, it's essential to right-size your infrastructure to match your actual needs.
2. Zombie resources: These are unused or forgotten resources that keep running and racking up costs. Regularly hunting them down and shutting them off is a smart move.
3. Inefficient data storage: Storing data in the cloud can get expensive if not managed properly. Opting for cost-effective storage classes and implementing data lifecycle policies can help you not lose money due to inefficiencies.
4. Poor visibility and lack of alerts: It's hard to control what you can't see. Gaining visibility into your cloud costs and usage patterns is crucial to identifying areas of waste and potential savings — including, setting up automatic alerts in situations where the meter starts to go through the roof.
5. Lack of automation: Automation is your best friend when it comes to cloud cost management. By mindfully automating processes like scaling, resource allocation, and monitoring, you can ensure optimal resource usage and avoid unnecessary expenses.
   

Even if your architecture is great for the current scale of the system and business – and the implementation is flawless — you must, with all humility, revisit the architecture every now and then or worse, when your system fails to scale without blowing up the cost.

Scenario 2: You lack a well-designed cloud architecture

Needless to say, a lack of good cloud architecture leads to countless fundamental problems —

1. Inefficient resource utilisation: A poorly designed architecture might not take full advantage of the cloud's scalability and elasticity. This can lead to over-provisioned resources or a lack of auto-scaling, resulting in higher costs.
2. Suboptimal data transfer: Poor architecture can cause unnecessary data transfers between different cloud services or regions. These data transfers can add up and make a dent in your wallet.
3. High-latency operations: A badly designed cloud infrastructure can lead to high latency, which affects the performance of your applications. This may require more resources to compensate, driving up costs.
4. Single points of failure: If your architecture doesn't have redundancy built in, it's vulnerable to single points of failure. This can result in downtime, which can be expensive in terms of both direct costs and reputation damage.
5. Difficulty in monitoring and managing: An overly complex or convoluted architecture can make it challenging to monitor and manage your cloud environment effectively. This lack of visibility can result in uncontrolled costs and potential security risks.

How to not let your cloud costs blow up unexpectedly (Best Practices)

Now that we’ve made a case for good architecture and a good implementation of it, let's dive into some best practices that'll help you optimise your cloud spending without compromising performance or security.

Measure 0 — Set up cost alerts and notifications

To proactively manage your cloud expenses, configure alerts and notifications using tools like PagerDuty, Datadog, or native cloud provider services. This will help you stay informed about any unexpected cost increases or unusual patterns in your cloud usage. By addressing these issues promptly, you can prevent your cloud costs from spiralling out of control and ensure you stay within your budget.

Cloud providers also offer cost management tools like AWS Cost Explorer or Azure Cost Management to help you analyse and visualise your cloud spending. Use these tools to identify trends, uncover cost-saving opportunities, and set budgets and alerts to keep your spending in check.

Measure 1 — Take control of managing your instances

When you design your cloud architecture, be mindful of choosing instance types that closely match your application's resource needs. To not end up paying for zombie resources, regularly review your resource utilisation and adjust your instance sizes accordingly to avoid paying for resources you're not using. It's worth recommending using tools like AWS Trusted Advisor or Azure Advisor, which can give you valuable recommendations in terms of where and how you can save costs.

If you have predictable workloads, consider committing to reserved instances or savings plans. These options can give you significant discounts over on-demand pricing, saving you a bundle in the long run.

When you have workloads that can tolerate interruptions, consider using spot instances or preemptible VMs. These discounted instances can save you up to 90% compared to on-demand pricing, but be prepared for the possibility that they might be terminated with short notice.

Here’s a quick playbook to proactively manage your instances well--

1. Monitor instance utilisation: Keep a close eye on your instances' performance metrics, such as CPU, memory, and storage utilisation. This will help you identify underutilised instances that might be costing you money for resources you're not using.
2. Rightsize instances (frequently): After analysing your instances' utilisation, adjust their sizes to better match their actual workload requirements. This may involve scaling down oversized instances or consolidating workloads onto fewer instances, both of which can lead to significant cost savings.
3. Schedule start and stop times: In many cases, instances don't need to run 24/7. By scheduling start and stop times for non-critical instances, you can ensure they're only running when they're actually needed, cutting down on unnecessary costs.
4. Leverage auto-scaling: Implement auto-scaling policies to automatically adjust the number of instances based on real-time demand. This way, you can maintain optimal performance without over-provisioning resources and incurring additional costs.

AWS, for instance, provides auto-scaling for compute, DB and other instances. With your auto-scaling policies in place, you can leverage AWS CloudWatch to get lightning-fast metric visibility, store data for over a year, and perform number-crunching to spot cost-saving opportunities.

By setting up alarms with cost-focused metrics, your team can make sure auto-scaling policies kick in when needed. This way, your infrastructure can scale out or scale in, using resources efficiently and keeping costs under control.

5. Opt for reserved or spot instances: Reserved instances offer discounted rates for committing to a specific usage period, while spot instances let you bid on unused capacity at a lower cost. Both options can help you save money on your cloud spend, as long as you carefully consider your workloads' requirements and plan accordingly.
   

Measure 2 — Optimise data storage and transfer

Storing data in the cloud can get expensive if not managed properly.

1. Choose the right storage class: Different storage classes come with varying performance characteristics and costs. Analyse your data access patterns and choose the storage class that best matches your needs, whether it's high-performance SSDs for frequently accessed data or low-cost object storage for infrequently accessed data.
   
   For example, the following image depicts different storage classes in AWS S3 –

2. Use data lifecycle policies: Implement data lifecycle policies to automatically transition data between storage classes or delete it when it's no longer needed. This can help you save on storage costs by ensuring you're only paying for the storage you actually need.
3. Enable data compression: Compressing your data before storing it in the cloud can significantly reduce storage costs, especially for large datasets. Many cloud storage services support automatic data compression, which can be easily enabled in their settings.
4. Optimise data transfer: Reducing the amount of data transferred between cloud services and your users can lead to significant cost savings. Utilise caching, content delivery networks (CDNs), and data deduplication techniques to minimise data transfer costs.
5. Monitor data transfer costs: Regularly review your data transfer costs to identify any unexpected spikes or patterns. By understanding the factors driving your data transfer expenses, you can make more informed decisions about optimising your data storage and transfer practices.

Measure 3 — Monitor and optimise container usage

Monitoring and optimising container usage is crucial for effective cloud cost management. It's a bit like managing your fridge: if you keep adding more groceries without keeping track of what's already in there, you'll end up with a messy fridge, wasted food, and unnecessary expenses.

Firstly, it's essential to consistently monitor container usage. Utilise tools like Kubernetes Metrics Server or Prometheus to gain insights into resource consumption. By staying informed, you can identify inefficiencies and make well-informed decisions to improve container management.

Next, continuously adjust container configurations based on the gathered data. Seek opportunities to consolidate containers or decrease resource allocations when not required. The goal is to achieve an optimal balance between resource usage and cost.

Additionally, consider implementing auto-scaling for your containers. Similar to instance auto-scaling, container auto-scaling helps you make efficient use of resources. By scaling container replicas up or down based on demand, you'll maintain a balance between performance and cost.

Measure 4 — Consider a multi-cloud strategy

If you can architect a well-rounded multi-cloud infrastructure and acquire the capability to manage it, the cost-saving upside can be worth it.

It’s been on the rise and for good reasons — look at the adoption rate for multi-cloud:

There are several risks that a Multi-Cloud strategy could help you mitigate and avoiding the risk of cost overruns is one of them. Following are 3 ways it can help –

Cloud provider-specific cost savings

Each cloud provider has its unique pricing models, features, and incentives for certain services. By identifying and capitalising on these provider-specific advantages, you can tailor your multi-cloud strategy to optimise costs.

For example, AWS offers EC2 Spot Instances, while Azure provides Azure Spot VMs, both allowing you to utilise spare capacity at a fraction of the regular price. By being well-versed in each provider's offerings, you'll find cost-saving gems.

Further, if you have access to credits from multiple cloud providers, it's worth your while and money to consider this measure.

Data transfer and egress cost optimisation

Data transfer costs can be one of the sneakiest culprits behind inflated cloud bills. Each cloud provider has distinct data transfer pricing structures.

A multi-cloud strategy enables you to design your cloud architecture, taking into consideration the most cost-effective data transfer routes between providers. This approach helps to minimise data egress costs and avoid unexpected surprises on your bill.

Cost optimisation through workload distribution

By spreading workloads across multiple cloud providers, you can take advantage of cost-saving features like autoscaling, serverless computing, and container orchestration in each environment. This approach not only helps optimise resource utilisation and costs but also provides additional benefits like improved performance and reduced latency.

Finally, if you do go down this path, consider utilising cloud cost management tools to gain insights into your multi-cloud infrastructure. Tools like CloudHealth, CloudCheckr, or even native cloud provider tools like AWS Cost Explorer can help you monitor, analyse, and optimise costs across multiple cloud environments. These tools provide granular cost insights, allowing you to make data-driven decisions to fine-tune your multi-cloud strategy and reduce expenses further.

Measure 5 — Build a cost-conscious engineering culture

When everyone on the team is aware of the financial implications of their decisions, they're more likely to make choices that keep costs in check.

If fixing cost-explosion fires is treating the symptoms — building a cost-conscious engineering culture is curing the disease.

This measure involves all the obvious but hard-to-do stuff —

• Set clear cost optimisation “Objectives” and a committee for ensuring different teams have measurable and time-bound “Key Results” associated with those objectives.
• Make cloud costs and resource usage visible to all team members and reward the teams and people who achieve the objectives they set out for.
• Equip your team with the knowledge and skills they need to make cost-effective decisions. Offer training on cloud pricing models, cost management tools, and best practices to ensure everyone is well-informed.
• Organise workshops, webinars, or meet ups to help teams stay updated on the latest cloud services, pricing models, and cost optimization strategies. Encourage knowledge sharing and collaboration between teams to drive best practices adopted across the organisation.
• Regularly review and revise your cost management policies, guidelines, and best practices as your organisation's cloud usage evolves. Stay agile and adaptive, ensuring your approach to decentralised cloud management remains effective and efficient.
  

Conclusion

To wrap things up, we've taken a journey through the world of cloud cost optimisation, touching on the challenges and diving into some best practices that'll help you make the most of your cloud bucks.

We've talked about being proactive with instance management, getting smart with data storage and transfers, keeping an eye on container usage, exploring the power of multi-cloud strategies, and fostering a centralised cloud management mindset with a cost-conscious culture.

By putting these tips into action and staying flexible, you'll be well on your way to conquering the cloud cost conundrum. So, gear up, take the reins on your cloud expenses, and revel in the rewards of a fine-tuned cloud ecosystem.

Cloud cost optimisation is not just about cutting costs, but also about maximising the value of your cloud resources. With a proactive, forward-thinking approach and a commitment to continuous improvement, your organisation can stay ahead of the game and make the cloud work in your favour.