How can cloud application architecture be optimized for cost savings?

Understand the requirement of the business. There is no one size fits all solution. Following are few things to consider. - Nature of business - Number of users - Startup/Enterprise - Tech stack - On-premises vs cloud - FinOps process for regular improvements - And much more

Optimizing cloud application architecture for cost savings is essential to ensure efficient resource utilization and minimize unnecessary expenses. Here are several strategies to help optimize your cloud application architecture for cost-effectiveness: Rightsize Resources, Use Auto-Scaling, Reserved Instances and Savings Plans, Spot Instances, Use Serverless Architectures, Optimize Storage Costs, CDN for Content Delivery, Implement Cost Tagging, Monitor and Analyze Resource Utilization, Use Multi-Region Deployments Wisely, Manage Database Costs, Implement Cost Alerts, valuate and Use Reserved Capacity, Regularly Review and Update, Educate and Involve Teams.

Cloud computing brings various out of the box solutions to bring security, cost optimization and less hassles of infrastructure maintenance. The possibilities to choose SaaS, PaaS or IaaS brings the first step. High availability, Auto-Scalability, Cost & Performance Predictability makes the life of organizations much easier. Fault Tolerance brings more confidence to the set back for the reliability of the solutions presented to the customers. Lots of features like Azure Containers, Azure Functions and event driven Server-less apps makes the life of developers lot easier. Last but not the least, the flexibility to choose from Public, Private, Hybrid or even Multi-Cloud to combine services from various providers is amazing!!!

Proper selection of cloud deployment model and cloud service models Optimal sizing - Selection of appropriate instance types, storage class, and regions etc. Availing auto scaling, serverless features Cloud watch for monitoring, SNS service for notifications on usage Use of containerisation services Cloud will turn more costly if it is not managed well as cloud service providers don’t alert to stop the service if not required any more.

One of the best thing in cloud service models, that they are flexible as well. If the contracted model and service provider is chosen carefully with the aim of maximum adaptability to business needs than your cloud would be able to follow the external and internal changes of requirements making you highly responsible to changes. There are already big players on the market who would allow you to change between the models within an existing contract, even offer services to help and support you to evaluate if the change of model beneficial for the company or not. Probably the best option is to choose an actual fit model with a cloud service provider who enables changes on the model itself as well.

Microservices may not be a one stop solution to all business needs. Maturity, skill and governance around microservices adoption and discovery are key before even thinking about adopting.

Leveraging microservices and containers is one approach to architect for cost savings, but a proficient architect understands when to apply this design pattern based on various factors. Monoliths should not be dismissed as a solution; they can be optimized for cost savings where appropriate. Additionally, considering usage patterns and forecasting is crucial. If predictable and stable usage patterns are known, reserved instances can offer significant cost savings.

Fantasy-land. Containers and microservices are rarely the most cost effective design pattern from a cloud provider billing perspective. I have never seen an organization choose a microservices design pattern for cost considerations. Generally monoliths will actually produce lower cloud provider bills. BUT, from a TCO (total cost of ownership) including support, cost of downtime, cost of time to repair and data loss, containerized microservices can have an advantage if your dev and ops teams know how to build and use them properly. Containers will definitely give you greater density of running systems on a hardware host than VMs will but can sometimes have greater day 2 operations costs than VMs, depending on the workload.

MVP Product - Early-stage startup: - Monolith Okay Growth phase: - More SOA and later microservice Microservices and containers only work on certain business scales. If you want to build your first MVP products, just go for the easier one.

Microservices is not the answer to everything, but if there is a right fit based on the solution you are building it can bring in incredible benefits if the complexity warrants it. Containers are not necessarily the only way to deliver microservices, as well that this imposes a learning curve on development teams. Balance correctly the need for microservices and containers to ensure you are not over-engineering your solution.

CDNs and caching are valuable tools for implementing cost savings in the cloud, with all major cloud providers offering methods for their utilization. Beyond cost efficiency, these mechanisms can enhance the performance of your application by strategically placing resources physically closer to users in various geographic locations. Understanding when to implement caching is key. Two things that this section did not mention: First, large media files, such as videos, are prime candidates. Second, dynamic content that does not change frequently is also a suitable candidate for caching.

With a CDN, you can have massive cost cut on traffic volume and computation. Many cloud providers overcharge for egress network and by using a CDN you can significantly save money. Many strategies are available, in my experience trying to create fully static websites and caching images or fonts can gain a cache-hit ratio of up to 98%. It is important to study and apply the best practices about E-tag and more generic cache headers. Is is good to include a good strategy to identify the best cache-key to apply to your content. Using a CDN can also prevent some sort of DDoS attacks and better protect your assets. Other than saving more costs to defend your inner infrastructure.

Caching and CDN (content delivery networks) can reduce your cloud costs in a couple of ways. 1) Reduced load on your source systems. If the data or assets are being served from outside your core compute systems you will be able to service many more requests with the same amount of resources. Many CDN endpoints can even do basic computation functions (edge compute) at a lower cost than centralizing all that computation. 2) All major cloud providers charge data exit fees for data leaving the cloud provider's network. Generally the fees associated with using a CDN to deliver data or assets is much lower per GB transferred. Don't forget that caching and CDN services come with their own costs which need to be taken into account.

Both caching and CDNs are fundamental technologies for web delivered applications as long as you match them with your business requirements. The more that can be offloaded to not be processed and served by your application multiple times the fewer requests your application has to handle, improving response time and reducing overall cost.

While the emphasis should be on automation and monitoring, this section lacks details on the importance of capturing metrics that monitor your usage patterns across bandwidth, CPU, memory, and disk usage. Monitoring these metrics allows you to dynamically scale your application based on demand, significantly reducing your cloud costs by only paying for the resources you need when you need them. Cloud providers offer ways to integrate these metrics into your infrastructure, including EC2 autoscaling, CloudWatch, and Kubernetes autoscaling policies.

Automating and closely monitoring cloud resources and processes is key to optimizing cloud costs. By setting up automatic scaling of cloud compute resources like instances and containers based on demand, overprovisioning can be avoided which saves money. For example, if application traffic tends to peak at certain times of day, having additional instances automatically launched during peak times prevents overpaying for unused capacity during off-peak periods. Monitoring tools should track cloud resource utilization across services like computing, storage, databases, networking, and API usage to find inefficiencies. Alerts can automatically notify teams when predefined cost or usage thresholds are exceeded or usage trends higher than usual.

It is important to monitor and automate your infrastructure. This helps to improve your business service quality and reduce mundane tasks that can be costly for your business. Always monitor to prevent things that can go wrong!

Monitoring helps to monitor resources for health as well as cost. By using tools like grafana , splunk we can build nice dashboards.

Automation is absolutely critical in modern times to ensure fast, stable and repeatable deployments removing human intervention and reducing the risk for errors along the way to deliver business value and new capabilities to your customers. Monitoring is absolutely critical to ensure things are operating correctly, focusing on measuring what matters and combine with automation to proactive fix issues to reduce or eliminate the amount of time customers are subject to errors.

Serverless technologies have their place in cloud computing. While they can be considered as a cost-saving strategy, always explore the Total Cost of Ownership (TCO) before proceeding down this path. Many organizations can quickly outgrow the pace of serverless, and it can become cost-prohibitive after a certain amount of growth. Additionally, managing and maintaining serverless solutions can become complex as the number of services in an organization grows.

Even though serverless is considered a cost-effective alternative to traditional infrastructure solutions, always be cautious about the operational costs associated with it. Sometimes it's better to go with a reserved instance that could auto scale

With serverless, you only pay for actual function execution, eliminating the need for provisioning and maintaining idle server capacity. This on-demand model optimizes costs by aligning expenses directly with usage. Serverless platforms automatically scale resources, ensuring efficient resource allocation and reducing the risk of over-provisioning. Additionally, serverless architectures shift operational responsibilities to the cloud provider, freeing up development teams to focus on coding rather than infrastructure management. By leveraging these advantages, organizations can achieve substantial cost savings while ensuring a highly scalable and responsive cloud application architecture.

Serverless computing can be the most cost effective design pattern when there is no or low usage of the system or system usage spikes are short-lived and infrequent. Reserved or even spot market instances can be much more cost effective. Serverless costs scale with usage but also with code in-efficiencies. Unoptimized code can cost a lot. The only time I have ever seen a CFO interested in optimizing code was with an application that made heavy use of serverless functions. I'm sitting in the CIO's office discussing tech strategy when the CFO bursts in, slams a printout of the monthly cloud provider bill on the table, points to a line item and says "Why is your application making so many damn database calls?"

Depending on the volume of operations and the capabilities the cloud provider offers, serverless can be a cost effective solution, especially where the solution allow this type of technology when balanced with amount of isolation and network security required.

Always understand the context, the business problem, as well as any Go-to-Market (GTM) strategies for the solution you are trying to deliver. Cloud-native design patterns can be used to optimize costs, but organizations should be careful to understand the approach and the potential disadvantages. These may include vendor lock-in, limited customization and control, and challenges related to data security, compliance, and privacy. Recognizing all the unrealized costs for a solution is crucial before committing to a particular approach.

Consider right sizing resources to specific workloads, or business/mission critical applications. Reduce excessive resources to ensure cost efficiency and ROI. Identify and minimize assets or cloud licensing that are not needed for optimization and greater savings.