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How to Calculate Cloud Migration Costs and Avoid Overpaying for Services After Migration

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How to Calculate Cloud Migration Costs and Avoid Overpaying for Services After Migration

Roman Burdiuzha

Cloud Architecture Expert Co-founder & CTO of Gart

April 8, 2024

Table of contents

Key Questions to Consider Before Cloud Migration
Local Infrastructure Costs
Cloud Migration Costs
Future Cloud Infrastructure Costs
Conclusion

Speaking of the benefits of cloud deployment, simplicity of use, flexibility, scalability, and reliability are often mentioned. However, migration is not just about moving infrastructure to the cloud, it is also about switching to a different cost model.

To understand how profitable this is, it is necessary to calculate the current costs of local infrastructure, the planned costs of the cloud, as well as the cost of migration. In this article, we will tell you how to correctly calculate the costs of transferring infrastructure and not overpay for services after migration.

Key Questions to Consider Before Cloud Migration

Here are some questions businesses should ask themselves before migrating to the cloud:

Is downtime critical for the company? There is no need for the cloud if the business can wait a day or two for server and other component recovery/replacement without major consequences.

Has the equipment been purchased? How long ago? Cloud migration can be delayed if the servers are less than three years old and the company does not plan to grow rapidly.

Is a cloud solution necessary? A cloud solution is necessary if the project is new and the equipment is not yet available. Or if it is already working, the infrastructure is more than three years old, and one to four hours of downtime is critical for the company.

Other questions to consider:

What are the business goals for migrating to the cloud?
What are the specific applications and workloads that will be migrated?
What are the security and compliance requirements for the cloud environment?
What are the costs and benefits of migrating to the cloud?
What is the migration timeline and plan?
Who will be responsible for managing the cloud environment after migration?

Local Infrastructure Costs

To determine the potential financial benefits of migrating to the cloud, it is necessary to calculate the current costs of the local infrastructure as accurately as possible and obtain data on its performance. Only then will it be possible to determine the correct configuration of the cloud infrastructure and compare the current local costs with the planned costs in the cloud.

Costs are divided into direct and indirect.

Direct costs:

Capital expenditures:
- Purchase of servers, storage systems, network equipment, etc.
- Software licenses.
- Data center construction or rental costs.
Operational expenditures:
- Electricity costs.
- Cooling costs.
- Maintenance and repair costs.
- IT staff salaries.

To calculate the total cost of local infrastructure, it is necessary to consider all of these factors. Once the total cost is known, it can be compared to the cost of cloud computing to determine whether migration is financially viable.

Direct Costs

Direct costs can be broken down into five main categories:

IT Equipment Acquisition: This includes the purchase of servers, storage systems, network equipment, and other IT hardware.
Data Center Colocation or Server Room Maintenance: This includes the cost of renting space in a data center or maintaining your own server room.
Software Licensing and Renewals: This includes the cost of purchasing and renewing licenses for operating systems, applications, and other software.
Hardware Setup and Maintenance: This includes the cost of installing, configuring, and maintaining IT hardware.
Software Updates and Equipment Service Contracts: This includes the cost of purchasing software updates and service contracts for IT hardware.
IT Personnel: This includes the cost of salaries, taxes, health insurance, vacation, bonuses, and office equipment for IT staff.

It is also important to consider the costs of HR, procurement, and accounting departments. These departments also spend some of their resources on ensuring the functionality of the corporate IT infrastructure

Indirect Costs

Indirect costs are not as obvious as direct costs and can be more difficult to calculate. The main part of indirect costs is related to downtime, customer dissatisfaction, damage to business reputation, and lost profits. An example of indirect costs would be a corporate website crashing or freezing on Black Friday.

One way to calculate indirect costs is to review incident and degradation reports to determine how often and for how long the equipment fails. To calculate the amount of damage, it is necessary to multiply the downtime by the average hourly rate of employees.

Indirect costs:

Downtime costs:
- Lost productivity due to system outages.
- Revenue losses due to unavailability of applications or services.
Security risks:
- Data breaches.
- Compliance violations.
Business agility:
- Inability to quickly scale up or down resources to meet changing business needs.

Cloud Migration Costs

Several key factors influence the cost of cloud migration. These include:

Defining migration goals: It is important to clearly define the goals of the migration before starting the process. This will help to determine the scope of the migration and the resources required.
Identifying key pain points: Once the goals are defined, it is important to identify the key pain points that the migration is intended to address. This will help to prioritize the migration tasks and focus on the areas that will have the biggest impact.
Data volume to be transferred: The amount of data that needs to be migrated will have a significant impact on the cost of the migration. It is important to accurately estimate the amount of data to be transferred and to choose a migration method that is appropriate for the volume of data.
Cloud service model: The cost of cloud migration will also vary depending on the cloud service model chosen. Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) all have different pricing models.
Provider selection: The cost of cloud migration will also vary depending on the cloud provider chosen. It is important to compare the pricing and features of different cloud providers before making a decision.

It is also necessary to assess the readiness of local applications for cloud operation. This is necessary to understand what can be immediately transferred to the cloud, what needs to be modernized, and what is better left in the local environment. Costs will need to be calculated for each scenario.

The migration process itself is the most labor-intensive and costly part of the migration. The costs of this stage consist of the following:

Initial costs for deploying new servers and cloud services. At the same time, the organization will incur additional time and financial costs for local infrastructure and data synchronization.
Modification of applications and code, creation of new infrastructure according to business needs. A significant part of the costs is for labor.
Solving potential problems with data privacy and security during the move.

Overall, it is quite difficult to calculate the exact cost of migration. The cost of migration depends heavily on the skills of the team. The more qualified it is, the lower the cost of the move. A cloud provider or partner with the necessary competencies can help reduce the time and cost of migration.

Successful Cloud Migration Case Studies by Gart:

Future Cloud Infrastructure Costs

After the migration, the cost structure changes. There is a regular fee for computing resources. However, it is only possible to estimate the costs of cloud infrastructure approximately, since it is difficult to predict the exact amount of resources needed to host applications in the cloud.

Fortunately for the customer, the estimate is usually higher than the actual costs. This is because the estimate is based on their own equipment, which is purchased with a margin. In the end, VM resources are optimized, and scaling is done on an as-needed basis.

How to Avoid Unnecessary Expenses

Ironically, many organizations move to the cloud to reduce costs, but in reality they overpay. According to a 2023 report by the American company Flexera, respondents estimated that their organizations lost 32% due to overspending.

Therefore, before migrating, it is necessary to develop a strategy for working and optimizing in the cloud. Depending on the industry, strategies may vary, so it is important to start from the needs of the business and the real VM load.

Here are some tips for avoiding unnecessary cloud infrastructure costs:

Optimize Costs

It is important to track your monthly cloud spending to identify any areas where you may be overspending. If you are not using a cloud service, you should terminate it to avoid paying for it. You should rightsize your VMs to ensure that you are only paying for the resources that you need. You can use spot instances to save money on your cloud costs.

Control Resource Allocation

To avoid overspending, it is important to use the correct amount of cloud resources. Most often, part of the cloud storage volume is wasted because it is larger than necessary. According to Flexera, 40% of cloud instances exceed the workloads required for operation.

Here are some tips for controlling resource allocation:

When you create a VM, you should choose the right size for your needs. There are many different VM sizes available, so you should be able to find one that is a good fit for your requirements.
You can use resource groups and tags to organize your cloud resources. This will make it easier to track your usage and costs.
You can use autoscaling to scale your cloud resources up or down as needed. This will help you to avoid overprovisioning resources.
You should monitor your cloud usage to track your resource allocation. You can use a cloud monitoring tool to help you monitor your usage.

Comparing cloud provider services

Comparing cloud provider services is a complex task, but it helps to reduce the overexpenditure of cloud resources. Organizations that work with multiple providers at the same time must regularly review their contracts, which helps to reduce their cost.

Revaluating assets

Conduct an assessment to identify and remove assets that have become unnecessary. It is also worth using cloud cost optimization tools.

Choosing a migration model

You can choose one of the three main models, namely migration to:

Public cloud

You purchase the capacities of one or more large data centers that simultaneously cooperate with many clients. This is an option that provides the business with the necessary flexibility and the ability to automate routine tasks.

Private cloud

Development and arrangement of your own cloud infrastructure on your own resources. This is a great solution for large companies with a developed IT infrastructure, a large number of branches, and those who find it difficult to maintain the operability of the system under the old conditions. A private cloud allows you to ensure absolute confidentiality of important data.

Hybrid cloud

A compromise option, when the main array of services and data is serviced on its own resources, and due to an external data center, the company has the opportunity to quickly and confidently scale, as well as test new technological solutions without the risk of “letting in” the main system.

Whichever option you choose, Gart Solutions will help you understand how to design and create a cloud for file storage and hosting your infrastructure, so that your business processes are as protected as possible from the influence of any factors, and are also efficient regardless of the scale of your activities.

Regardless of the method you choose for migration to the cloud, we will help implement all the possibilities of this choice in practice, including automatic backup to the cloud.↳

Conclusion

Migration to the cloud and the transition to a new cost model can be beneficial for business if you approach this process responsibly: compare the costs of local infrastructure and cloud in advance, develop a strategy and carefully monitor costs. Gart Solutions will be happy to take over the “turnkey” migration to the cloud, freeing up the time of your company’s specialists for the implementation of more important projects.

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FAQ

What is cloud migration?

Cloud migration is the process of moving an organization's IT resources from internal data processing servers to a public or private cloud architecture. The process involves the use of specialized software for virtualization and performance optimization. Migration can be implemented either using public cloud hosting tools or by creating your own private cloud.

Why migrate to the cloud?

The advantage of any cloud migration is the placement of applications and data in the most efficient and secure IT environment. Particular attention is paid to failsafe operation, data protection, and cost savings while maintaining high performance of the cloud environment. Many organizations use migration of local data to enable business scaling, budget savings, and development of new projects without diverting resources to building and maintaining IT infrastructure.

How to start working in the cloud?

Creating a cloud environment is the initial stage. To start working, it is necessary to migrate all working programs and their data to the cloud, integrate programs with existing equipment and processes without significant changes. Cloud migration changes the responsibilities of the IT department, but does not eliminate them completely. It is necessary to train the staff and ensure that the team knows what tasks they are still responsible for and how the new environment works.

Why is it important to accurately estimate cloud migration costs?

Accurate cost estimation helps businesses avoid surprises and ensures they have sufficient budget for the migration and ongoing cloud usage.

What are the main factors that influence cloud migration costs?

The main factors include: Scope of migration (data volume, applications) Chosen cloud service model (IaaS, PaaS, SaaS) Cloud provider selection Migration complexity (existing infrastructure, skillset)

Kubernetes

Hidden Costs in Running Many Cluster Nodes on Kubernetes

Roman Burdiuzha

December 22, 2023

In Kubernetes, are there hidden costs on running many cluster nodes? In Kubernetes, a cluster node is a physical or virtual machine responsible for running containers. The number of nodes in a cluster directly impacts its capacity, scalability, and performance. While adding more nodes might seem like a straightforward solution to handle increased workloads, it's crucial to be aware of the potential hidden costs associated with a high node count. [lwptoc] Not all CPU and memory in your Kubernetes nodes can be used to run Pods. CPU and Memory are divided into: Operating system Kubelet, CNI, CRI Pods Eviction threshold Let's make a quick example. Imagine you have a cluster with a single 1GiB / 1vCPU Node. The following resources are reserved for the kubelet + os: 255MiB of Memory 60 Mi of CPU That's 25% of Memory and 6% of CPU that you can't use. Let's pick GCP's n1-standard-1 instance (1 vCPU, 3.75GB). Google reserves for the kubelet + os: 937MB of Memory 60 Mi of CPU So you can only use ~3GB of Memory for your Pods (~75% of the available). EKS has similar (interesting?) limits. Let's pick an m5.large (2vCPU, 8GiB) Amazon reserves for the kubelet + os: 574MiB of Memory 160 Mi of CPU This time you are lucky. You can use ~93% of the available Memory. Cost is not the only metric when choosing an instance type for your cluster, but it is certainly a factor. Unseen Costs of Kubernetes Cluster Expansion Infrastructure Costs Running numerous cluster nodes inevitably leads to increased infrastructure costs. Each node requires resources such as CPU, memory, and storage, contributing to higher expenses in terms of hardware, maintenance, and power consumption. Organizations must carefully balance the benefits of scalability against the financial implications of maintaining a large number of nodes. Operational Overhead As the number of nodes grows, so does the operational overhead. Managing and monitoring a vast number of nodes becomes a complex task that demands additional resources. Operations teams must invest time and effort into configuring, maintaining, and troubleshooting issues across an expansive node infrastructure, potentially diverting attention from other critical tasks. Network Complexity A Kubernetes cluster with an excessive number of nodes introduces challenges related to network complexity. Communication between nodes becomes more intricate, and network latency may increase, affecting overall application performance. Additionally, maintaining secure communication channels and configuring networking policies become more challenging as the cluster scales. Resource Fragmentation Running a high number of nodes can lead to resource fragmentation, where resources are underutilized due to uneven distribution across nodes. This inefficiency can result in wasted capacity and increased costs. Optimizing resource allocation and ensuring efficient utilization becomes crucial to mitigating this hidden cost. Scaling Considerations While scalability is one of Kubernetes' strengths, it's essential to strike a balance between scaling for performance and being mindful of associated costs. Overprovisioning nodes to meet peak demand may lead to unnecessary expenses during periods of lower activity. Implementing auto-scaling strategies and monitoring workloads can help optimize costs while maintaining performance. Cost CategoryDescriptionInfrastructure CostsHardware, virtual machines, storage, and network expenses for running cluster nodes.Operational OverheadTime and resources spent on configuring, monitoring, and troubleshooting node-related issues.Network Complexity CostsExpenses associated with managing and optimizing communication between nodes.Resource Fragmentation CostsWasted capacity and increased expenses due to uneven resource distribution across nodes.Scaling ConsiderationsPotential costs related to overprovisioning nodes to meet peak demand and auto-scaling strategies.Management ToolsCosts of tools and software used for Kubernetes cluster management and optimization.Training and ExpertiseInvestment in training teams to efficiently manage and operate a Kubernetes environment.Table outlining various aspects of Kubernetes costs: Conclusion In the dynamic world of Kubernetes, understanding the potential hidden costs associated with running many cluster nodes is crucial for making informed decisions. Organizations must carefully evaluate their scalability needs, considering factors such as infrastructure costs, operational overhead, network complexity, resource fragmentation, and scaling considerations. Striking the right balance ensures that the benefits of scalability are maximized without incurring unnecessary expenses, ultimately contributing to a more cost-effective and efficient Kubernetes environment. Ready to optimize your Kubernetes environment? Unlock efficiency and cost-effectiveness with our expert Kubernetes services. Scale smarter, reduce hidden costs – transform your container orchestration today!

DevOps

Transformative Impact of NoOps on Business Cost Reduction and Accelerated Product Development

Fedir Kompaniiets

December 12, 2023

Can the NoOps concept eliminate the need for DevOps engineers entirely in software development? It's quite possible that NoOps will empower developers to handle all aspects of delivering a software product independently. However, let's delve deeper into this somewhat controversial topic. [lwptoc] What is NoOps? NoOps is a way of developing and deploying software where the need for specialized operations (Ops) teams and their tasks is minimized or entirely eliminated. The term "NoOps" comes from the DevOps culture, which emphasizes collaboration and communication between ops engineers and developers to optimize and automate the Software Development Life Cycle (SDLC). In the NoOps approach, developers take on many tasks typically handled by DevOps teams, such as deploying and monitoring programs, managing infrastructure, and ensuring the reliability and security of the system. Two key drivers of NoOps are the increasing automation of IT and the widespread use of cloud computing. NoOps environments rely on automated, policy-based processes, often implemented through initiatives like DataOps, AIOps, and DevSecOps. The main idea behind NoOps is to automate as many processes as possible (provided it's cost-effective), reduce the need for manual intervention, and minimize the risk of human error. Among the advantages of the NoOps approach are: Project Implementation Speed: Projects can be implemented more quickly. Ease of Development Management: Development management becomes more straightforward. Optimized Development Costs: Development costs are optimized due to a reduced workforce. Business Scalability Simplicity: Scaling the business becomes simpler. Can We Do Without DevOps Specialists Now? It might seem like NoOps implies that operational teams are no longer necessary. However, it's essential to note that this approach still requires expertise in areas such as infrastructure design, cybersecurity, and compliance. Rather than eliminating operational teams, NoOps aims to make them more efficient, freeing up time to address high-level tasks and strategic issues. As a result, this approach demands developers to have more experience in areas like infrastructure, networks, deployment, monitoring, and more—at least, that's how it appears at first glance. However, the evolution of software development has always been accompanied by a need or desire to simplify certain things, tools, and processes. So, how does it happen that developers now seem to have more on their plate? In practice, the NoOps approach doesn't mean developers take on all the functions typically handled by DevOps/SRE. Instead, the DevOps team establishes a foundation, documents it, and provides it to software developers. This involves implementing practices and tools that "isolate" the development team from the infrastructure layer and ensure its support. NoOps vs. DevOps Is NoOps a Panacea? Unfortunately, no, so DevOps is very much alive and thriving. One might wonder, why not skip DevOps and go straight to NoOps with all its advantages? Well, to begin with, NoOps is confined to applications that fit into existing PaaS solutions. Many companies still use monolithic legacy applications that require significant updates or complete rewriting to function in a PaaS environment. Additionally, new technologies will emerge that may not have suitable NoOps solutions. Examples of NoOps Platforms In reality, the NoOps concept is not entirely new. Most of us have already heard of or even had the opportunity to use similar services and platforms. One example of a PaaS (Platform as a Service) solution is Heroku. Using this platform, anyone can deploy their software in the cloud with just a few clicks, and for a small application, it can even be free. Another example is DigitalOcean App Platform, a managed PaaS that simplifies the deployment and scaling of applications. Developers can upload their code to the platform, and DigitalOcean takes care of creating the necessary infrastructure, managing containerized deployments, as well as scaling and load balancing. Google App Engine is a fully managed serverless platform for developing and hosting web applications. It automatically scales your application based on traffic and consumed resources. DevOps vs. NoOps FeatureNoOpsDevOpsDefinitionMinimizes or eliminates operational tasks, aiming for fully automated processes.Emphasizes collaboration between development and operations teams to streamline the software development lifecycle.ResponsibilitiesDevelopers take on many operational tasks, reducing the need for a dedicated operations team.Operations and development teams collaborate to address both development and operational aspects.Expertise RequiredDevelopers need more expertise in infrastructure, networking, deployment, and monitoring.DevOps engineers possess a blend of development and operations expertise.Platform ExamplesDigitalOcean App Platform, Google App Engine.Kubernetes, Docker, Jenkins, Ansible.ScopePrimarily suited for applications that fit into existing PaaS solutions.Applicable to a wide range of applications, including monolithic legacy systems.FlexibilityMay not be suitable for all types of applications, particularly those requiring specific infrastructure configurations.Offers flexibility to adapt to diverse application architectures and infrastructure needs.EvolutionSeen as an evolution of DevOps, focusing on increased automation and reduced operational overhead.Represents the collaboration and synergy between development and operations, evolving to meet changing software development needs.Development FocusDevelopers concentrate on the code, with less involvement in operational tasks.Developers work collaboratively across the entire software development lifecycle, addressing both development and operational concerns.ComplexityDeveloping NoOps platforms can be complex, requiring architectural decisions and solving intricate challenges.Involves creating a seamless integration of development and operational processes, managing complex toolchains.Overall GoalAims to streamline and automate processes to reduce friction and increase developer focus on code.Strives for collaboration and efficiency to achieve faster, more reliable software delivery. Conclusion The NoOps approach should not be seen as a disruptor to DevOps; rather, it can be viewed as the next framework, a kind of evolution of DevOps or SRE. On the other hand, it will require engineers to acquire knowledge in areas that were not traditionally part of their expertise, while DevOps engineers will have the opportunity to focus more on their core responsibilities. Developing a NoOps platform itself is a complex task, requiring the adoption of many architectural decisions and the resolution of intricate challenges. The real goal of DevOps is acceleration, cost reduction, and improved quality. NoOps, with its elimination of friction between developers and IT administrators, contributes to further automation and allows developers to concentrate directly on the code. In essence, both NoOps and DevOps serve the overarching objective of enhancing efficiency and collaboration within the software development lifecycle, each offering its unique approach to achieving these goals.

Cloud

What Are the Cloud Cost Models? A Comprehensive Guide

Roman Burdiuzha

August 29, 2023

Unlock the secrets to smart cloud cost management with our comprehensive guide. Learn about different cloud cost models, optimization tips, and tools to make informed decisions. Whether you're a startup or an enterprise, master the art of cost-effective cloud computing. [lwptoc] Ever wondered how companies manage their expenses when using the cloud? It's a bit like choosing a phone plan – you want one that fits your needs without breaking the bank. Different Cost Models in Cloud Computing Cloud computing has revolutionized the way businesses operate, offering scalability, flexibility, and cost-efficiency like never before. Each model comes with its own set of advantages and trade-offs, making it essential to choose the right one for your organization's needs. Here's a breakdown of the primary cloud cost models: Pay-As-You-Go (PAYG) Reserved Instances (RIs) Spot Instances On-Demand Instances Reserved Capacity Serverless and Consumption-based Pricing Here's a table comparing various pricing models for cloud services, including pay-as-you-go, subscription-based, and consumption-based: Pricing ModelDescriptionAdvantagesDisadvantagesPay-as-you-goYou pay for the resources you use on an hourly or per-second basis. No upfront commitments or long-term contracts.- Flexibility to scale up or down as needed- No upfront costs- Pay only for what you use- Potentially higher costs for consistent, predictable workloads- Costs can be variable and harder to predictSubscription-basedYou pay a fixed monthly or annual fee for a set amount of resources or services. Typically includes discounts for longer commitment periods.- Predictable, consistent costs- Discounted rates for longer commitments- Suitable for steady-state workloads- Potential for underutilization or overprovisioning- Less flexibility for variable workloads- Upfront commitment requiredConsumption-basedYou pay based on your actual usage or consumption of resources, typically measured in units like GB, hours, or requests.- Aligns costs with actual usage- Suitable for bursty, unpredictable workloads- No upfront commitments- Costs can be variable and harder to predict- Potential for higher costs with consistent, high usageReserved InstancesYou commit to a specific instance type and configuration for a set period (e.g., 1 or 3 years) and receive a significant discount compared to on-demand pricing.- Substantial cost savings for consistent, predictable workloads- Flexibility to sell or modify reservations- Upfront commitment required- Potential for underutilization or overprovisioning- Less flexibility for variable workloadsSpot InstancesYou bid for spare compute capacity at steep discounts compared to on-demand prices. Instances can be reclaimed with little notice.- Significant cost savings (up to 90% off)- Suitable for fault-tolerant, interruptible workloads- Instances can be terminated with little notice- Not suitable for critical or persistent workloads Pay-As-You-Go (PAYG) Cloud Model The Pay-As-You-Go (PAYG) cloud model is like a "pay only for what you use" approach to cloud computing. In this model, you're billed based on your actual usage of cloud resources, such as virtual machines, storage, and data transfer. There's no upfront commitment or long-term contract. Instead, you're charged on an hourly or per-second basis, depending on the cloud provider. Advantages of PAYG PAYG offers unmatched flexibility. You can easily scale resources up or down to meet changing demands. Need more computing power during a busy season? No problem. PAYG allows you to spin up additional instances as needed and scale them down when the rush is over. Unlike other models like Reserved Instances, PAYG doesn't require any upfront payments or commitments. You start using resources immediately and pay only for what you consume, making it cost-effective for startups and projects with unpredictable workloads. PAYG is an excellent entry point for businesses new to cloud computing. You can experiment, test, and develop without the burden of a long-term financial commitment. This allows you to explore the cloud's potential without major financial risk. Challenges and Considerations Cost Management While PAYG provides flexibility, it can also lead to unexpected costs if resources aren't managed effectively. Teams need to actively monitor usage and optimize their cloud environment to avoid overspending. Unpredictable Costs For organizations with highly variable workloads, it can be challenging to predict monthly expenses accurately. This unpredictability can make budgeting a bit trickier. Limited Cost Savings Although PAYG is cost-effective for short-term projects and experimentation, it may not provide the same level of savings as Reserved Instances for long-term, stable workloads. Real-world Examples Many startups leverage PAYG to launch their services. They can begin small, assess user demand, and then scale their resources as their user base grows, all without a significant upfront investment. E-commerce companies often experience seasonal spikes in traffic during holidays. They can use PAYG to handle increased demand during these periods and then scale back afterward to avoid unnecessary costs. Development and testing environments are ideal candidates for PAYG. Developers can create instances when needed, develop and test their applications, and then terminate resources to stop incurring costs when not in use. Read more: Optimizing Costs and Operations for Cloud-Based SaaS E-Commerce Platform Reserved Instances (RIs) Reserved Instances (RIs) are a strategic cost-saving tool in cloud computing. Unlike the Pay-As-You-Go model, where you pay for resources by the hour or second with no commitments, RIs involve a commitment to a specific instance type and region for a predetermined duration, usually one or three years. This commitment results in significantly reduced hourly rates compared to on-demand pricing. There are two primary types of RIs: Standard RIs These offer the highest level of cost savings but are less flexible. You commit to a specific instance type and operating system within a particular region for the chosen term. They are best suited for stable workloads with predictable resource requirements. Convertible RIs Convertible RIs provide more flexibility. While you still commit to a specific instance type and region, you have the option to change the instance type, family, or operating system during the reservation term. This versatility makes them suitable for workloads that may evolve or need adjustments over time. Benefits of using RIs RIs can result in substantial cost reductions, often up to 75% compared to on-demand prices. This makes them an attractive choice for businesses with steady workloads. RIs guarantee access to cloud resources even during peak times. You have reserved capacity, ensuring your applications run smoothly without interruptions. With RIs, you can accurately predict your long-term cloud costs, making budgeting and financial planning more manageable. Ready to Revolutionize Your Deployment Process? Looking for expert guidance to choose the right cloud cost model? Reach out to Gart, our cloud cost optimization specialist, and make the most of your cloud investments. Cost Optimization Strategies with RIs To make the most of Reserved Instances, consider these strategies: Identify Stable Workloads RIs are most effective when applied to stable workloads with predictable resource needs. Analyze your usage patterns to determine which instances are good candidates. Mix and Match Use a combination of Standard and Convertible RIs to balance cost savings and flexibility. Convertible RIs are useful for workloads that may change over time. Utilize Third-Party Tools Cloud cost management tools can help identify RI purchase recommendations and ensure that RIs are used effectively. Use Cases and Examples Companies with consistently high web traffic can reserve instances for their web servers, ensuring they have the necessary capacity to handle user requests efficiently. Reserved Instances are ideal for database servers that require constant uptime and predictable performance. They provide cost savings while maintaining data availability. Large enterprises running resource-intensive applications can benefit from RIs by reducing ongoing operational costs. E-commerce businesses can reserve instances during peak shopping seasons to handle increased traffic while enjoying substantial cost savings. Use CasePay-As-You-Go (PAYG)Reserved Instances (RIs)Startups✔️ Flexible for growth✔️ Cost savings for stable workloadsVariable Workloads✔️ Easily scale up/down❌ May not suit highly fluctuating workloadsPredictable Workloads❌ Costs can add up✔️ Cost-effective for steady resource needsExperimentation✔️ No upfront costs❌ Requires upfront commitmentSeasonal Traffic✔️ Scale resources✔️ Plan ahead and save on costsDevelopment Environments✔️ Flexibility❌ May not be the most cost-efficientData Analysis✔️ Quick access to power❌ Might overpay for stable analysisPredictable Performance❌ Costs can vary widely✔️ Guaranteed capacity and cost savingsLarge Enterprises✔️ Scalability✔️ Long-term cost predictabilityBig Data Processing✔️ Scale for big tasks✔️ Plan and save on long-running jobsThis table visually compares use cases of the Pay-As-You-Go (PAYG) cloud model and Reserved Instances (RIs) to help you understand which model might be more suitable for various scenarios. Spot Instances Spot Instances are a unique and cost-effective cloud computing model offered by many cloud service providers, including Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. They are designed for workloads that are flexible and can tolerate interruptions. Spot Instances allow you to access spare cloud computing capacity at significantly reduced prices compared to on-demand instances. How Spot Instances Work Spot Instances work on the principle of surplus cloud capacity. Cloud providers often have more resources available than are currently in use. To make use of this excess capacity, they offer it to customers at a much lower cost through Spot Instances. Here's how it works: Users can request Spot Instances, specifying their instance type, region, and maximum price they are willing to pay per hour. Cloud providers determine Spot instance prices based on supply and demand. When your bid price exceeds the current market price, your Spot Instances are provisioned. Spot Instances can be terminated with very little notice, usually with a two-minute warning. This is because if a higher-paying customer requires the resources, the Spot Instances are preempted. The primary advantage of Spot Instances is cost savings. Spot Instances typically cost a fraction of the price of on-demand instances. Organizations can achieve significant cost reductions, especially for workloads that can be interrupted or spread across multiple instances for fault tolerance. Best Practices and Considerations To make the most of Spot Instances while managing their inherent volatility, consider these best practices and considerations: Fault Tolerance Design your applications to be fault-tolerant. Distribute workloads across multiple Spot Instances and regions to mitigate the risk of termination. Auto Scaling Implement auto-scaling and monitoring to automatically launch replacement instances if Spot Instances are terminated. Use Cases Identify workloads that can leverage Spot Instances, such as batch processing, data analysis, rendering, and testing environments. Bid Strategies Be mindful of your bid price. Set it competitively to ensure resource availability while maintaining cost savings. Instance TypesBe flexible with your choice of instance types. Different types may have varying availability and pricing. Use Cases and Industries that Benefit Spot Instances are ideal for data processing, analytics, and machine learning workloads, where large amounts of computational power are required intermittently. Research institutions and scientific projects can use Spot Instances to perform complex simulations and calculations cost-effectively. Rendering, transcoding, and video processing tasks in the media and entertainment industry can benefit from the scalability and cost savings of Spot Instances. Development and testing environments can utilize Spot Instances to keep costs low while providing developers with the resources they need. Financial modeling and risk analysis tasks can take advantage of Spot Instances to perform intensive calculations at a lower cost. More Cloud Cost Models On-Demand Instances With on-demand instances, you pay by the hour or second without any long-term commitment. Advantages: No upfront costs, maximum flexibility. Considerations: Usually more expensive than RIs, not suitable for steady workloads. Reserved Capacity This model involves pre-purchasing capacity for services like databases or storage. Advantages: Guaranteed availability, potential cost savings for predictable workloads. Considerations: Upfront payment, limited flexibility. Serverless and Consumption-based Pricing Serverless computing charges you based on actual usage, making it cost-effective for sporadic workloads. Advantages: Efficient for small, intermittent tasks, and automatically scales. Considerations: May not be suitable for all applications, harder to predict costs. Cost Estimation Tools In the complex world of cloud computing, keeping tabs on your expenses can be challenging. This is where cost estimation tools come into play. These tools are your financial compass in the cloud, helping you navigate costs, optimize spending, and make informed decisions. AWS Cost Explorer: This tool from Amazon Web Services (AWS) provides cost analysis and visualization, helping users understand and control their AWS spending. Google Cloud Cost Management: Google Cloud Platform (GCP) offers a suite of cost management tools, including Cost Explorer and Billing Reports, to help users monitor and optimize their GCP expenses. Azure Cost Management and Billing: Microsoft's Azure offers robust cost management features, including budgeting, forecasting, and spending analysis. CloudHealth by VMware: CloudHealth offers a comprehensive cloud management platform with cost optimization, governance, and security features. It supports multiple cloud providers. FinOps Foundation: While not a specific tool, the FinOps Foundation is a community-driven initiative that provides best practices, standards, and resources for cloud financial management. Here are some additional factors to consider when choosing a cloud cost model: Your budget: How much are you willing to spend on cloud computing? Your workload: What type of workloads will you be running on the cloud? Your flexibility needs: Do you need to be able to scale your resources up or down quickly? Your risk tolerance: Are you willing to take the risk of having your spot instances terminated?

Key Questions to Consider Before Cloud Migration

Local Infrastructure Costs

Direct Costs

Indirect Costs

Cloud Migration Costs

Future Cloud Infrastructure Costs

Optimize Costs

Control Resource Allocation

Comparing cloud provider services

Revaluating assets

Choosing a migration model

Conclusion

FAQ

What is cloud migration?

Why migrate to the cloud?

How to start working in the cloud?

Why is it important to accurately estimate cloud migration costs?

What are the main factors that influence cloud migration costs?

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