Streamlining AWS Cloud Spend for Innovation Investments

Cloud Spend 101: What is it, and why does it matter?

Cloud spend is the amount of money an organization spends in AWS and across all cloud platforms. A common belief is that moving to the cloud will significantly decrease your total cost of ownership (TCO) quickly, easily, and almost by default. Unfortunately, reaping the infrastructure cost savings of AWS is not that simple, but it certainly is obtainable. To achieve a lower TCO while simultaneously boosting productivity and gaining operational resilience, business agility, and sustainability, you must strategize your migration and growth within AWS.

The most common mistake made when migrating from on-prem environments to the cloud is going “like-for-like.” Basically, creating a cookie-cutter image of what existed on-prem in the new cloud environment. Because they are two completely different types of infrastructure, organizations end up way over-provisioned using unnecessary and expensive On-Demand Instance pricing.

Ideally, you want a well-developed game plan before migration starts to avoid losing money in the cloud. With the advice and support of a trusted cloud partner, a comprehensive strategy takes your organization from design to implementation to optimization. That puts you in the best position to stay on top of costs during every step of migration and once you’re established in AWS. Cost savings realized in the cloud can be reinvested in innovation that expands business value and grows your bottom line.

The 6 pillars of cloud spend optimization.

While it’s best to have a comprehensive strategy before migrating to the cloud, cloud spend optimization is an ongoing necessity in any cloud environment. With hundreds of thousands of different options for cloud services today, choosing the right tools is overwhelming and leaves much room for missteps. At the same time, there are also a lot of opportunities available. Regardless of where you are in your cloud journey, the six pillars of cloud spend optimization provide a framework for targeted interventions.

#1: Reserved Instances (RIs)

RIs deliver meaningful savings on Amazon EC2 costs compared to On-demand Instance pricing. RIs aren’t physical instances but a billing discount for using On-Demand Instances in your account. Pricing is based on the instance type, region, tenancy, and platform; term commitment; payment cadence; and offering class.

#2: Auto-Parking

A significant benefit of the cloud is scalability, but the other side of that is individual control. Often, an organization’s team members forget or are not prompted or incentivized to terminate resources when they aren’t being used. Auto-Parking schedules and automates the spin-up/spin-down process depending on hours of use to prevent paying for idle resources. This is an especially helpful tool for development and test environments.

#3: Right-Sizing

Making sure you have exactly what you need and nothing you don’t requires an analysis of resource consumption, chargebacks, auto-parked resources, and available RIs. Using those insights, organizations can implement policies and guardrails to reduce overprovisioning by tagging resources for department-level chargebacks and properly monitoring CPU, memory, and I/O (input/output).

#4: Family Refresh

Instance types, VM series, and Instance Families all describe the methods cloud providers use to package instances depending on the hardware. When instance types are retired and replaced with new technology, cloud pricing changes based on compute memory and storage parameters – this process is referred to as “Family Refresh.” Organizations must closely monitor instances and expected costs to manage these price fluctuations and prevent redundancies.

#5: Waste

Inherent in optimization is waste reduction. You need the checks and balances we’ve discussed to prevent unnecessary costs and reap the financial benefits of a cloud environment. Identifying waste and stopping the leaks takes time and regular, accurate reporting within each business unit. For example, when developers are testing, make sure they’re only spinning up new environments for a specific purpose. Once those environments are no longer used, they should be decamped to avoid waste.

#6: Storage

Storage catalyzes many organizations to move to the cloud because it’s a valuable way to reduce on-prem hardware spend. Again, to realize those savings, businesses must keep a watchful eye on what is being stored, why it’s being stored, and how much it will cost. There are typically four components impacting storage costs:

  1. Size – How much storage do you need?
  2. Data transfer (bandwidth) – How often does data move from one location to another?
  3. Retrieval time – How quickly do you need to access the data?
  4. Retrieval requests – How often do you need access to the data?

Depending on your answers to these questions, there are different ways to manage your environment using file storage, databases, data backup, and data archives. Organizations can estimate storage costs with a solid data lifecycle policy while right sizing and amplifying storage capacity and bandwidth.

Private Pricing Agreements

Another way to control your AWS spend is with a PPA or a Private Pricing Agreement – formally known as an EDP or Enterprise Discount Program. A PPA is a business-led pricing agreement with AWS that considers a specific term and commit amount. Organizations that are already in the cloud and love the service can use their expected growth over the next three or five years to get a discount for committing to that amount of time with AWS. In addition to expected compute services, reservations for reserved instances, and existing savings plans, the business also includes software purchases from the marketplace in the agreement to get further discounts.

Choosing a cloud optimization partner.

It’s easy to know what to do to control spend, but it’s a whole other beast to integrate cloud optimization into business initiatives and the culture of both IT teams and finance teams. Of course, you can go it alone if you have the internal cloud expertise required for optimization, but most businesses partner with an external cloud expert to avoid the expenses, risk, and time needed to see results. Attempting these strategies without an experienced partner can cost you more in the long run without achieving the ROI you expected.

In fact, when going it alone, businesses gain about 18% savings on average. While that may sound satisfying, companies that partner with the cloud experts at 2nd Watch average 40% savings on their compute expenses alone. How? We aim high, and so should you. Regardless of how you or your cloud optimization partner tackles cloud spend, target 90% or greater coverage in reserved instances and savings plans. In addition to the six pillars of optimization and PPAs, you or your partner also need to…

  • Know how to pick the right services and products for your business from the hundreds of thousands of options available.
  • Develop a comprehensive cloud strategy that goes beyond just optimizing cost.
  • Assess the overall infrastructure footprint to determine the effectiveness of serverless or containerization for higher efficiency.
  • Evaluate applications running on EC2 instances to identify opportunities for application modernization.

Take the next step in your cloud journey.

2nd Watch is a great choice for cloud spend optimization with AWS because we specialize in this area. With our extensive experience and in-depth knowledge of AWS services and pricing models, we can help you maximize your AWS investments. Our comprehensive solutions include cost analysis, budgeting, forecasting, and ongoing monitoring. We have a proven track record of delivering significant cost savings for our clients across various industries.

We leverage automation and advanced tools to identify cost-saving opportunities, eliminate waste, and optimize your AWS resources. This ensures efficiency and allows you to focus on innovation and growth. We provide continuous optimization and support, proactively identifying potential cost-saving measures and recommending adjustments based on your changing business needs.

With us, you’ll gain transparency into your AWS spend through detailed reports and analytics. This visibility empowers you to make informed decisions and manage your budgets effectively. Choose 2nd Watch for cloud spend optimization with AWS and experience the expertise, solutions, and track record that will help you achieve cost savings while driving innovation and growth.

2nd Watch saves organizations hundreds of thousands of dollars in the cloud every year, and we’d love to help you reallocate your cloud spend toward business innovation. Our experienced cloud experts work with your team to teach cloud optimization strategies that can be carried out independently in the future. As an AWS Premier Partner with 10 years of experience, 2nd Watch advisors know how to maximize your environment within budget so you can grow your business. Contact Us to learn more and get started!







Cloud Economics: Empowering Organizations for Success

Cloud economics is crucial for an organization to make the most out of their cloud solutions, and business leaders need to prioritize shifting their company culture to embrace accountability and trackability.

When leaders hear the phrase “cloud economics,” they think about budgeting and controlling costs. Cost management is an element of cloud economics, but it is not the entire equation. In order for cloud economics to be implemented in a beneficial way, organizations must realize that cloud economics is not a budgetary practice, but rather an organizational culture shift.

The very definition of “economics” indicates that the study is more than just a numbers game. Economics is “a science concerned with the process or system by which goods and services are produced, sold, and bought.” The practice of economics involves a whole “process or system” where actors and actions are considered and accounted for. 

With this definition in mind, cloud economics means that companies are required to look at key players and behaviors when evaluating their cloud environment in order to maximize the business value of their cloud. 

Once an organization has fully embraced the study of cloud economics, it will be able to gain insight into which departments are utilizing the cloud, what applications and workloads are utilizing the cloud, and how all of these moving parts contribute to greater business goals. Embodying transparency and trackability enables teams to work together in a harmonious way to control their cloud infrastructure and prove the true business benefits of the cloud. 

If business leaders want to apply cloud economics to their organizations, they must go beyond calculating cloud costs. They will need to promote a culture of cross-functional collaboration and honest accountability. Leadership should prioritize and facilitate the joint efforts of cloud architects, cloud operations, developers, and the sourcing team. 

Cloud economics will encourage communication, collaboration, and change in culture, which will have the added benefit of cloud cost management and cloud business success. 

Where do companies lose control of their cloud costs?

When companies lose control of cloud costs, the business value of the cloud disappears as well. If the cloud is overspending and there is no business value to show for, how are leaders supposed to feel good about their cloud infrastructure? Going over budget with no benefits would not be a sound business case for any enterprise in any industry. 

Out-of-control cloud spending is quite easy, and it usually boils down to poor business decisions that come from leadership. Company leaders should first recognize that they wield the power to manage cloud costs and foster communication between teams. If they are making poor business decisions, like prioritizing speedy delivery over well-written code or not promoting transparency, then they are allowing practices that negatively impact cloud costs. 

When leaders push their teams to be fast rather than thorough, it creates technical debt and tension between teams. The following sub-optimal practices can happen when leadership is not prioritizing cloud cost optimizations:

  • Developers ignore seemingly small administrative tasks that are actually immensely important and consequential, like rightsizing infrastructure or turning off inactive applications. 
  • Architects select suboptimal designs that are easier and faster to run but are more expensive to implement.
  • Developers use inefficient code and crude algorithms in order to ship a feature faster, but then fail to consider performance optimizations to execute less resource consumption.
  • Developers forgo deployment automation that would help to automatically rightsize.
  • Developers build code that isn’t inherently cloud-native, and therefore not cloud-optimized.
  • Finance and procurement teams are only looking at the bottom line and don’t fully understand why the cloud bill is so high, therefore, creating tension between IT/dev and finance/procurement. 

When these actions compound, it leads to an infrastructure mess that is incredibly difficult to clean up. Poorly implemented bad designs that are not easily scalable will require a significant amount of development time; therefore, leaving companies with inefficient cloud infrastructure and preposterously high cloud costs.

Furthermore, these high and unexplained cloud bills cause rifts between teams and are detrimental to collaboration efforts. Lack of accountability and visibility causes developer and finance teams to have misaligned business objectives. 

Poor cloud governance and culture are derived from leadership’s misguided business decisions and muddled planning. If leaders don’t prioritize cloud cost optimization through cloud economics, the business value of the cloud is diminished, and company collaboration will suffer. Developers and architects will continue to execute processes that create high cloud costs, and finance and procurement teams will forever be at odds with the IT team.

What are the benefits of cloud economics?

Below are a few common business pitfalls that leaders can easily address if they embrace the practice of cloud economics:

  1. Cost Savings: The cloud eliminates the need for upfront hardware investments and reduces ongoing maintenance and operational costs. Organizations only pay for the resources they use, allowing for cost optimization and scalability.
  2. Infrastructure Efficiency: Cloud providers can achieve economies of scale by consolidating resources and optimizing data center operations. This results in higher infrastructure efficiency, reducing costs for businesses compared to managing their own on-premises infrastructure.
  3. Agility and Speed: The cloud enables rapid deployment and provisioning of resources, reducing the time and cost associated with traditional IT infrastructure setup. This agility allows businesses to quickly adapt to changing market demands and launch new products or services faster.
  4. Global Reach and Accessibility: Cloud services provide a global infrastructure footprint, allowing businesses to easily expand their operations into new regions without the need for physical infrastructure investments. This global reach enables faster access to customers and markets.
  5. Scalability and Elasticity: Cloud services offer the ability to scale resources up or down based on demand. This scalability eliminates the need for overprovisioning and ensures businesses have the necessary resources to handle peak workloads without incurring additional costs during idle periods.
  6. Improved Resource Utilization: Cloud providers optimize resource utilization through virtualization and efficient resource management techniques. This leads to higher resource utilization rates, reducing wasted capacity and maximizing cost efficiency.
  7. Business Continuity and Disaster Recovery: Cloud services provide built-in redundancy and disaster recovery capabilities, reducing the need for costly backup infrastructure and complex recovery plans. This improves business continuity while minimizing the financial impact of potential disruptions.
  8. Innovation and Competitive Edge: The cloud enables rapid experimentation and innovation, allowing businesses to quickly test and launch new products or services. This agility gives organizations a competitive edge in the market, driving revenue growth and differentiation.
  9. Focus on Core Business: By offloading infrastructure management to cloud providers, businesses can focus more on their core competencies and strategic initiatives. This shift in focus improves productivity and resource allocation, leading to better economic outcomes.
  10. Decentralized Costs and Budgets: Knowing budgets may seem obvious, but more often than not, leaders don’t even know what they are spending on the cloud. This is usually due to siloed department budgets and a lack of disclosure. Cloud economics requires leaders to create visibility into their cloud spend and open channels of communication about allocation, budgeting, and forecasting.
  11. Lack of Planning and Unanticipated Usage: If organizations don’t plan, then they will end up over-utilizing the cloud. Failing to forecast or proactively budget cloud resources will lead to using too many unnecessary and/or unused resources. With cloud economics, leaders are responsible for strategies, systems, and internal communications to connect cloud costs with business goals.
  12. Non-Committal Mindset: This issue is a culmination of other problems. If business leaders are unsure of what they are doing in the cloud, they are less willing to commit to long-term cloud contracts. Unwillingness to commit to contracts is a missed opportunity for business leaders because long-term engagements are more cost-friendly. Once leaders have implemented cloud economics to inspire confidence in their cloud infrastructure, they can assertively evaluate purchasing options in the most cost-effective way.

What are the steps to creating a culture around cloud economics?

Cloud economics is a study that goes beyond calculating and cutting costs. It is a company culture that is a cross-functional effort. Though it seems like a significant undertaking, the steps to get started are quite manageable. Below is a high-level plan that business leaders must take charge of to create a culture around prioritizing cloud economics:

1. Inform: Stage one consists of lots of data collecting and understanding of the current cloud situation. Company leaders will need to know what the trust costs of the cloud are before they can proceed forward. Creating visibility around the current state is also the first step to creating a culture of communication and transparency amongst teams and stakeholders.

2. Optimize: Once the baseline is understood, leadership can analyze the data in order to optimize cloud costs. The visibility of the current state is crucial for teams and leadership to understand what they are working with and how they can optimize it. This stage is where a lot of conversations happen amongst teams to come up with an optimization action plan. It requires teams and stakeholders to communicate and work together, which ultimately builds trust among each other.

3. Operate: Finally, the data analysis and learnings can be implemented. With the optimization action plan, leaders should know what areas of the cloud demand optimization first and how to optimize these areas. At this point in the process, teams and stakeholders are comfortable with cross-collaboration and honest communications amongst each other. This opens up a transparent feedback loop that is necessary for continuous improvement. 


The entire organization stands to gain when cloud economics is prioritized. A cost-efficient cloud infrastructure will lead to improved productivity, cross-functional collaboration between teams, and focused efforts towards greater business objectives. 

Ready to take control of your cloud costs and maximize the value of your cloud infrastructure? Contact 2nd Watch today and let our team of experts help you implement cloud economics within your organization. As a trusted partner for enterprise-level services and support, we have the expertise to assist you in planning, analyzing, and recommending strategies to optimize your cloud costs and drive business objectives. Don’t let cloud spending go unchecked. Take charge of your cloud economics by reaching out to a 2nd Watch cloud expert now

Mary Fellows | Director of Cloud Economics at 2ND Watch

How Business and IT Should Partner to Build a Data Strategy

Any functioning company has a vision, goals, and direction. A successful company follows a strategy – set forth by its executives – to realize its vision, achieve its goals, and determine its direction. Executing executive strategy requires cross-functional collaboration amongst teams across the organization.

Having a data strategy is crucial to achieving your greater business goals. To set attainable and tangible business objectives, you need to utilize data. Your IT department will implement and oversee the technologies powering your data strategy; therefore, business processes and goals must factor in IT resources and capabilities. Your organization’s business unit should work closely with your IT team to build an effective data strategy.  

Utilizing Data Analysis to Pursue Strategies

When it comes to business goals, each goal should have a quantitative KPI or metric that is extracted from data and analytics. Of course, this is easier said than done! Even the simplest of business questions can spawn dozens of data threads needed for analysis. For example, if you are looking to track business profitability, you’ll have to look at key components such as revenue, COGS, and overhead. Each of these data sources must be broken down even further to fully understand the several metrics that make up the greater question of profitability. The ultimate goal of having a data strategy is to define all the inputs required to calculate key metrics and incorporate them into your production processes.

Your Data Strategy Checklist

Before engaging in any data management project, it’s important to outline your to-do list. Below is a checklist with the foundational steps to building out a data strategy:

  • Scope the project (what business problem are you trying to solve?)
  • Generate a work breakdown structure for strategy.
  • Create a timeline with milestones.
  • Define teams and individual role definitions.
  • Determine how you collaborate with others.
  • Schedule meetings (kick-off, status, sprint planning, and steering meetings). 
  • Begin research of your technology stack.
  • Budget for your data strategy project.
  • Kick off with the team!

Let’s Get Started!

As you work toward building a data strategy, there are four deliverables you should focus on: a current state understanding, a future state architecture, a gap analysis, and a road map.

Current State Understanding

Your data strategy should reinforce and advance your overall business strategy, which refers to the processes you use to operate and improve your business. To grow, you must establish your baseline to measure your growth. To gain an understanding of your current state, review your current data architecture, data flows, and source systems by:

  • Collecting existing diagrams and analyzing existing discovery
  • Verifying source systems (you have more than you think!)
  • Diagramming and visualizing
  • Having a logical model (what are the existing business domains?)

Future State Architecture

Once you’ve established a baseline, imagine where you’d like the future state architecture. Your future state architecture should support the data platform at your company, including a logical model of the data warehouse and technology decisions. To determine your future state, define your data threads, which requires you to identify your source systems and domains. 

Gap Analysis

What changes need to happen to move your company from the current state to the desired future state? Establish your technical framework and identify the gaps. This framework should be built for moving, curating, and delivering data to your business use cases. 

Road Map

Roading mapping is the most time-consuming and the most important deliverable. Your data strategy roadmap will outline how and when to implement your data vision and mission. This will help you manage change and ensure that IT goals are aligned with business goals. A well-thought-out roadmap reveals true dependencies so you can adjust as priorities shift. There are several important steps to building out a road map, which we will cover below. 

Step 1: Build and estimate a backlog.

Your backlog should be based on your intended future state and what business deliverables you want to generate.

Questions to answer:

  • What data threads need to be engineered?
  • How are you going to deliver the inputs to the artifact?
  • How are you going to productionalize the result to create the action?

Step 2: Define your vision and interim goals.

Before you can embark on any project, you’ll need to establish your end goals and the goals along the way.

Questions to answer:

  • What does success look like?
  • What priorities should you target?

Step 3: Identify your KPIs.

Determine the data and metrics that will be the most useful for operational and strategic decisions.

Questions to answer:

  • Who needs what information?
  • How valuable is that information to guide your decisions?

Step 4: Understand everything about your data.

This means understanding your sources of data, data relationships, and data quality issues.

Questions to answer:

  • What data are you sourcing from?
  • What data issues can be resolved by code versus process changes?
  • How can you map this data to a new, clean, holistic data model for reporting and analytics?

Step 5: Recommend a selection of technologies and tools.

Technologies and tools will be the means to your end, so be sure to conduct a thorough evaluation process. 

Questions to answer:

  • What architecture considerations are required to best use your technology stack and ecosystem?
  • What orchestration tools will you need?
  • What additional tools will you need to consider in the future as the platform matures?

Step 6: Design a high-level solution architecture.

Use this architecture on your data marts, leading to quicker access to data and faster insights. 

Questions to answer:

  • How should raw data, data collection, data storage, and access be structured for ease of use?
  • How frequently – and with what method – should this data be refreshed?
  • Who will own and support this in the future?

Step 7: Generate a specific backlog of tasks for implementing o9 development.

Questions to answer:

  • How will you build out the end-to-end foundation?
  • How will you coordinate with groups to gain the most immediate benefit?

Step 8: Develop a go-forward plan with a budget, milestones, and a timeline.

These components of your roadmap will make your future state a reality.

Questions to answer:

  • When can you complete this project?
  • How will you allocate the work?
  • How much will it all cost?
  • What internal and external resources are needed to put everything into action?

A Timeline of Your Data Strategy Road Map

At 2nd Watch, our approach is based on a 5- to 7-month data strategy timeline. Our data experts and consultants think about implementing a data strategy in phases. 

Phase 1: Foundation and process – 3 to 4 months

  • Set up your ETL and audit framework.
  • Ingest your primary data set into a persistent storage layer.
  • Engineer a business model for Phase 1 scope.
  • Create a data dictionary, source to target, and support documentation for scaling the platform.
  • Develop business use cases based on Phase 1 scope.
  • Establish a strategic foundation for ongoing maturity and add future data sources.
  • Assign a data engineer and architect to support model development.

Phase 2: Development analytics – 2 to 3 months

  • Ingest your primary data sources for development.
  • Add integration dataflows to increase and expand the business layer for Phase 2 scope.
  • Identify SMEs and data champions to drive QA and identify new report requirements.

Phases 3 and 4: Secondary sources

  • Ingest all other data sources to supplement data warehouse development.
  • Add integration dataflows to increase and expand the business layer for Phase 3 and 4 scope.
  • Integrate new dataflows into existing reporting and create opportunities for new audiences and enterprise level roll-ups.

Phase 5 and beyond: Support

  • Continue to model data for Phases 5 and beyond.
  • Expand advanced analytics capabilities for predictive and clustering models.
  • Eliminate downstream dependencies on legacy systems to allow sunsetting applications.
  • Integrate additional data consumers and data applications for expanded functionality.

2nd Watch’s consultants work with your team to understand your business goals and design a tech strategy to ensure success throughout the organization. From planning to technology selection to user adoption, our team’s data advisory services enhance business optimization via data-driven insights for the long haul. Contact us today to learn how 2nd Watch can build a modern data foundation for your business intelligence and predictive analytics to ensure your organization can make better decisions now and in the future.