Cloud computing is a powerful and flexible way to access computing resources on demand, but it can also be expensive if not managed properly. In this article, you will learn some cost-efficient ways to use cloud computing, such as choosing the right service model, optimizing your resource utilization, scaling your applications, and implementing a private cloud.
One of the first decisions you need to make when using cloud computing is which service model to use. There are three main types of cloud services: infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). Each one offers different levels of control, customization, and responsibility over the cloud resources. Generally, the higher the level of abstraction, the lower the cost and complexity, but also the lower the flexibility and customization. You should choose the service model that best suits your needs and budget, and avoid paying for unnecessary features or capabilities.
In context of aws ,here are the 3 cost optimization strategies on AWS: 1. Commit to Reserved Instances (RIs) or Savings Plans for steady workloads, enjoying reduced pricing. 2. Visualize, understand, and control AWS expenses utilizing Cost Explorer and setting personalized budget alerts. 3. Implement autoscaling groups and load balancers to adjust the number of running instances based on resource usage or traffic patterns.
Lead Consultant - Genpact | Cloud Migration Engineer | 26x Multi-Cloud | 4x MCT
With IaaS, you pay for the compute, storage, and networking resources you consume on a per-hour or per-minute basis. IaaS offers flexibility in resource selection, allowing you to choose instance types, storage options, and networking configurations. PaaS abstracts the underlying infrastructure and middleware layers, allowing you to focus on developing and deploying applications without worrying about managing the underlying infrastructure. PaaS platforms often provide built-in auto-scaling capabilities that automatically adjust resources based on application demand. SaaS applications are typically offered on a subscription basis, where you pay a recurring fee for access to the software and its features.
IaaS: A company using IaaS may rent virtual servers and storage from a cloud provider like AWS to host its website and databases, thereby customizing the environment to meet its specific needs. PaaS: A software development team leveraging PaaS, such as Google App Engine, can focus solely on coding and deploying applications while the provider manages the underlying infrastructure, enabling streamlined development processes. SaaS: Users accessing web-based email services like Gmail or office suites such as Microsoft 365 benefit from SaaS, as the provider handles everything from infrastructure to application management, allowing for simple subscription-based usage without technical concerns.
Some things don't belong in cloud. The first question you need to ask is - where does your workload belong? Is it really a candidate to run in a public cloud? Maybe you should build a private cloud or look at edge infrastructure in a hybrid or distributed cloud model. I am fond of the adaptive cloud or adaptive platforms concept - align the technical and business requirements of your apps with the platforms you plan to invest in. This requires some evaluation and planning, but long-term it can make for a much more efficient use of cloud infrastructure. Of course, part of your platform alignment will be understanding which services are available on each of them and how they align to your apps. Don't treat cloud like a datacenter!
It's important to understand the trade-offs between control, cost, and complexity when choosing between IaaS, PaaS, and SaaS. I would recommend considering your technical expertise, project requirements, and budget when making your decision. Do not use a feature beacuse it exists and is popular. Use it only if your project needs it . The cloud native tools look very simple to enable and use, but always have additional cost and implications. Make sure to decide what is needed. But also choose something which aligns with long term business goals.
Another way to reduce your cloud computing costs is to optimize your resource utilization. This means using only the amount of resources that you need, and releasing them when you don't. For example, you can use auto-scaling to adjust the number of servers or containers based on the traffic or load of your applications. You can also use spot instances or preemptible VMs to take advantage of lower prices for spare or unused capacity, but be prepared to handle interruptions or failures. You can also use monitoring and analytics tools to track your resource consumption and identify any inefficiencies or waste.
In the pay-for-consumption model of the cloud, the single biggest way to reduce your costs is to reduce your consumption. The problem is that we became used to the fixed-cost model of the data center, where removing unused resources has little/no payoff. We've already paid for hardware, & shutting it off won't get us our money back. But in the cloud we only pay for what's running, so finding unused resources & removing/right-sizing gives us an immediate payoff. Anyone who's worked in IT knows, people will always tell you when they need something, but nobody ever tells you when they're done with it. So, in order to keep costs low, IT needs to be proactive by continually looking for underutilized resources & removing/right-sizing them.
To minimise cost due to low utilisation, consider scale-to-zero serverless. If it isn't being used you are not paying. This is perfect for occasional use or POCs where utilisation is inherently low. They only become expensive when utilisation becomes moderate.
Pay per user option itself provided the flexibility of utilizing the resource when it required. 1.Rightsizing the instance based on the utilization metrics. 2. Applying the Savings plan to the compute which will cover the lambda also which is a cost effective option. 3. Make a RI purchase for the Managed DB Instances. 4. Using Spot Instances in the Autoscaling Workloads. 5 . Implement the Weekday/Weekend Scheduler to stop the instances during non-production Instances. 6. Reduce the Min Value to Zero in the Autoscaling groups of non-production Instances. 7. Add the cloudwatch agent for the memory to reduce the size of memory Intensive applications. 8. Release the static IP's which is allocated and not used and cleanup the snapshots.
Optimizing resource utilization is a key strategy for reducing cloud computing costs. This involves efficiently utilizing resources by scaling server instances or containers based on application traffic or load through auto-scaling. Additionally, leveraging spot instances or preemptible VMs can capitalize on lower pricing for spare capacity, albeit with potential interruptions. Monitoring and analytics tools further aid in tracking resource consumption, pinpointing inefficiencies, and minimizing waste, ultimately contributing to cost savings and improved operational efficiency
Optimizing resource utilization is a key strategy for keeping cloud costs under control. Have alerts set as you hit some cost milestones. Autoscaling is good, but ensure you are not ending up paying more when a serverless can do a the same job. Have monthly checks on what resources are consuming more costs. See if something can be done to reduce it. In few cases writing automated job to shutdown developments VM's on friday night can save a ton of cost.
Scaling your applications is not only a way to improve your performance and availability, but also a way to save money on cloud computing. Scaling can be done in two ways: horizontally or vertically. Horizontal scaling means adding more instances or nodes to your application, while vertical scaling means increasing the size or capacity of each instance or node. Horizontal scaling is usually more cost-efficient and scalable than vertical scaling, as it allows you to distribute the load and avoid over-provisioning. However, horizontal scaling also requires more management and coordination, and may not be compatible with some legacy or stateful applications. You should choose the scaling strategy that works best for your application architecture and design.
If your dev, and test environments are running 24/7 you are doing cloud wrong. Now to uncover truths about this you can: 1. Turn them off when not in use. 2. Hire a consultant who will tell you what you already know (hey you can hire me for this also if you like I will provide a long document with charts and all for the right price). 3. Keep paying the costs like we did on prem. Simple stuff like this, that is so basic is not implemented by the smartest people, at the biggest companies.
Entendimento dos Requisitos do Aplicativo: Avalie as necessidades de recursos computacionais, como CPU, memória, armazenamento e largura de banda. Considere requisitos específicos da aplica??o, como bancos de dados, servidores web, servi?os de cache, entre outros. Análise de Tráfego e Carga de Trabalho: Examine padr?es de tráfego para entender picos de uso e demanda sazonal. Analise a carga de trabalho típica e máxima esperada. Arquitetura do Aplicativo: Certifique-se de que a arquitetura do aplicativo seja compatível com a escalabilidade horizontal, permitindo a adi??o de instancias conforme necessário. Utilize servi?os gerenciados da nuvem sempre que possível para simplificar a administra??o.
Scaling applications efficiently in the cloud is not only beneficial for enhancing performance and availability but also for cost savings. There are two primary scaling approaches: horizontal and vertical scaling. Horizontal scaling involves adding more instances or nodes to an application, enabling cost-efficient distribution of the load and avoiding over-provisioning. Although it is more scalable, it requires additional management and coordination and may not be suitable for certain legacy or stateful applications. On the other hand, vertical scaling entails increasing the size or capacity of each instance or node. While this approach may be simpler, it is generally less cost-efficient and has limitations in scalability.
To use horizontal scaling, your application needs to comply with microservices principles. There may be a need to adapt your application for the cloud, which means rebuilding it. You will then fully benefit from the advantage of the cloud by leveraging scalability.
Scaling is a crucial aspect of cloud application management, offering a balance between performance, availability, and cost. The best approach depends on your specific needs. Here's a general guideline: Horizontal scaling is ideal for applications with: High traffic spikes Need for high availability Stateless architecture Vertical scaling might be suitable for: Predictable workloads Simple applications Stateful applications (with careful consideration)
A private cloud is a cloud environment that is dedicated to a single organization or user, and is hosted either on-premises or by a third-party provider. A private cloud can offer some cost benefits over a public cloud, such as more control, security, and compliance over your data and resources, and lower network and data transfer costs. However, a private cloud also requires more upfront investment, maintenance, and expertise than a public cloud, and may not offer the same level of scalability, elasticity, and innovation. You should consider a private cloud if you have specific or sensitive requirements that cannot be met by a public cloud, or if you can leverage your existing infrastructure and resources to create a private cloud.
Some ways are - Dev/Test environments: Use separate environments for development and testing, and scale them down or even pause them when not in use to save costs. Resource sharing: Share resources (e.g., databases, storage) across multiple applications or teams to reduce overall costs. Regular cost reviews: Conduct regular reviews of your cloud usage and costs to identify areas for optimization and cost savings. Optimize licensing costs: Choose licensing options (e.g., bring your own license)that best fit your needs and budget. Use of monitoring and analytics: Use monitoring and analytics tools to gain insights into your cloud usage and performance. This can help you identify inefficiencies and optimize your resources for cost savings.
Isolamento: Os recursos da nuvem privada s?o dedicados exclusivamente à organiza??o, proporcionando isolamento e seguran?a adicionais. Controle Total: A organiza??o tem controle total sobre a infraestrutura, incluindo redes, servidores e armazenamento. Personaliza??o: A nuvem privada pode ser personalizada para atender às necessidades específicas da organiza??o, seja em termos de desempenho, seguran?a ou requisitos de conformidade. Seguran?a Aprimorada: Devido ao controle exclusivo, as organiza??es podem implementar medidas de seguran?a personalizadas para proteger dados sensíveis. Conformidade: A nuvem privada é muitas vezes escolhida por organiza??es que precisam cumprir regulamenta??es rigorosas de conformidade.
Private clouds provide a high level of control over data and infrastructure, making them ideal for organizations with strict security or regulatory compliance requirements. I recall doing a review on Openshift few years back. It is quite popular for development workloads. On cloud developers spin up resources and often time forget about them if the company has no central cloud operations. Private cloud is more limited and companies will invest in processes to conserve it and ask everyone to be mindful of usage.
In a practical example, a financial institution with stringent regulatory requirements and sensitive customer data might opt for a private cloud hosted on its own premises, ensuring maximum control over data security and compliance. This setup allows the institution to meet regulatory needs while safeguarding sensitive financial information, albeit with higher initial investment and ongoing maintenance.
When considering private cloud adoption, it's crucial to weigh the trade-offs between control, security, and upfront investment against the potential limitations in scalability, elasticity, and innovation compared to public cloud offerings. For instance, a manufacturing company with proprietary designs and strict data sovereignty requirements might find a private cloud hosted on-premises to be the optimal solution, ensuring complete control and compliance. Conversely, a startup focusing on rapid growth and resource agility may lean towards public cloud services due to their scalability and cost-effectiveness. Each organization must evaluate its unique needs and capabilities to determine the most suitable cloud deployment model.
Some cloud providers offer discounts if you commit to use a service for long term. Also, in case you already purchased licenses for a database such as SQL Server for example, you can use the existing license and save money too. My last tip is to move stored objects that are not long in use to cheaper tiers. Sometimes you just need to keep them for auditing purposes, but you are paying for them to stay available in more expensive tiers.
While pay as you go model in cloud is lucrative, one must dive deeper into business to make most for it. While designing cloud solution there is no golden rule for everything, it all depends on business. Many cloud vendors offer considerable discounts on advance reservations of services which in fact becomes cheaper then pay as you go model.
?? Embracing automation in cloud cost management is a game-changer! We’ve revolutionized our approach by enforcing tagging on all resources. Any untagged resource? Automatically shut down. This not only promotes adherence to best practices but also significantly cuts down on orphaned resources eating into budgets ?? With cost allocation tags, we’re now able to track spending down to the minutest details, ensuring every dollar is accounted for. We’ve also implemented dynamic scaling and scheduling, ensuring resources are used efficiently ?? Educating the team on the importance of a cost-conscious culture has been key. Regular audits and leveraging cutting-edge tools for deeper insights into our cloud spend have made optimization a constant