Let’s be honest—traditional cloud cost management metrics aren’t cutting it anymore. While “Cloud Spend by Service” dashboards and untagged resource reports served us well in the early cloud days, they’re increasingly inadequate for today’s complex reality. Our customers are managing intricate multi-cloud and hybrid architectures where traditional cost visibility approaches simply fall short.

At CloudBolt, we believe a more advanced, automation-first approach is needed—one that not only enhances visibility but also drives action and delivers measurable financial impact. 

This guide introduces seven strategic cloud cost metrics that embody Augmented FinOps—a new era of cloud financial management where automation, AI-driven insights, and unified visibility work together to transform how organizations optimize cloud spend. 

These aren’t just metrics for tracking costs; they’re designed to: 

Additionally, these metrics lay the foundation for achieving true Unit Economics—where cloud costs are directly tied to business value rather than just technical operations. Later this year, CloudBolt will release a comprehensive guide on Unit Economics, providing deeper insights into this transformative approach.

It’s time to move beyond reactive cloud cost management. Let’s talk about how these metrics can help your organization build a more efficient, predictable, and value-driven cloud strategy.

The 7 cloud cost metrics

Total cost allocation coverage

As cloud environments grow more complex, tracking where cloud spend is going—and who is responsible for it—is essential. Total cost allocation coverage measures the percentage of total cloud costs that are properly attributed to business units, projects, or teams. The higher the percentage, the clearer the financial picture, making it easier to manage budgets, optimize resources, and drive accountability.

Without proper allocation, cloud costs become difficult to control. Untracked or miscategorized spending leads to budget overruns, inaccurate forecasting, and missed optimization opportunities. A strong allocation strategy ensures that every dollar spent is tied to a business purpose, enabling chargeback/showback models, precise budgeting, and better financial decision-making.

Unlike traditional cost tracking, this metric extends beyond public cloud services, extending to private cloud, Kubernetes, and SaaS environments, ensuring a holistic view of cloud investments. By improving total cost allocation coverage, organizations can create transparency, enforce financial discipline, and empower teams to take ownership of their costs.

Formula: Total cost allocation coverage = (Allocated cloud spend / total cloud spend) x 100

where

Follow these steps to calculate and improve total cost allocation coverage:

1. Identify allocated and unallocated costs.

2. Apply the allocation formula.

Total cost allocation coverage = (Allocated cloud spend / total cloud spend) x 100

3. Use FOCUS-aligned data for granular tracking.

For organizations using FOCUS-compliant data, the following SQL query can be used to measure allocation effectiveness across charge periods:

SELECT
    ChargePeriodStart,
    ChargePeriodEnd,
    (SUM(CASE
        WHEN JSON_EXTRACT(Tags, '$.[tag_key]') IS NOT NULL
        THEN EffectiveCost
        ELSE 0
    END) / NULLIF(SUM(EffectiveCost), 0)) * 100 AS AllocationPercentage,
    SUM(CASE
        WHEN JSON_EXTRACT(Tags, '$.[tag_key]') IS NOT NULL
        THEN EffectiveCost
        ELSE 0
    END) AS AllocatedCost,
    SUM(CASE
        WHEN JSON_EXTRACT(Tags, '$.[tag_key]') IS NULL
        THEN EffectiveCost
        ELSE 0
    END) AS UnallocatedCost,
    SUM(EffectiveCost) AS TotalCost
FROM focus_data_table
WHERE ChargePeriodStart >= [start_date]
    AND ChargePeriodEnd < [end_date]
    AND EffectiveCost > 0
GROUP BY ChargePeriodStart, ChargePeriodEnd;

Key adjustments for your organization:

Example:

4. Track and improve over time.

Success benchmarks

Organizations should target these allocation rates based on their FinOps maturity:

Higher allocation coverage ensures that cloud investments align with business goals, improving financial transparency, governance, and accountability.

Budget variance score

Cloud spending is inherently dynamic, making budget adherence a critical component of financial governance. The budget variance score tracks how closely actual cloud costs align with budgeted forecasts, helping organizations improve cost predictability and avoid unnecessary overspending.

When teams consistently overshoot budgets, it signals issues such as inaccurate forecasting, underutilized cost controls, or inefficient resource scaling. On the other hand, significantly underspending could indicate over-provisioning or missed opportunities for strategic cloud investments.

Formula: Budget variance score = 100 – |(actual spend – budgeted spend) / budgeted spend| x 100

where: 

To accurately calculate budget variance score, follow these steps:

1. Define budgeted spend.

2. Compare against actual spend.

Extract actual cloud spending from cloud billing reports for the same time period.

3. Apply the variance score formula.

Measure how much actual spend deviates from budgeted amounts.

Example query:

WITH PeriodSpend AS (
    SELECT
        ProviderName,
        SubAccountId,
        SubAccountName,
        ChargePeriodStart,
        ChargePeriodEnd,
        SUM(BilledCost) AS TotalActualSpend
    FROM focus_data_table
    WHERE ChargePeriodStart >= [start_date]
        AND ChargePeriodEnd < [end_date]
        AND ChargeClass IS NULL  -- Excludes corrections from previous periods
    GROUP BY
        ProviderName,
        SubAccountId,
        SubAccountName,
        ChargePeriodStart,
        ChargePeriodEnd
)
SELECT
    p.ProviderName,
    p.SubAccountId,
    p.SubAccountName,
    p.ChargePeriodStart,
    p.ChargePeriodEnd,
    p.TotalActualSpend,
    b.BudgetAmount,
    ((p.TotalActualSpend - b.BudgetAmount) / NULLIF(b.BudgetAmount, 0)) * 100 AS VariancePercentage,
    GREATEST(0, 100 - ABS(((p.TotalActualSpend - b.BudgetAmount) / NULLIF(b.BudgetAmount, 0)) * 100)) AS BudgetVarianceScore,
    CASE
        WHEN p.TotalActualSpend > b.BudgetAmount THEN 'Over Budget'
        WHEN p.TotalActualSpend < b.BudgetAmount * 0.95 THEN 'Under Budget'
        ELSE 'On Target'
    END AS BudgetStatus
FROM PeriodSpend p
LEFT JOIN budget_reference b  
    ON p.SubAccountId = b.SubAccountId
    AND p.ChargePeriodStart = b.PeriodStart;

4. Analyze budget variance trends.

Success benchmarks

Ideal budget variance score targets depend on an organization’s cloud maturity, risk tolerance, and workload type.

Stable production workloads:

Highly variable or dev/test environments:

Net-new deployments or migrations:

Project-based workloads:

Organizations should regularly benchmark variance scores to identify improvement areas and refine budgeting strategies over time.

Architecture cost accuracy score

Accurate cost estimation is the backbone of financial predictability in cloud environments. The architecture cost accuracy score measures how closely an organization’s estimated cloud costs align with actual cloud spending over time. This metric is crucial for budget planning, resource provisioning, and financial governance, helping organizations refine their forecasting models and prevent unexpected cost overruns. 

Cloud cost estimates often miss the mark due to unaccounted scaling, workload spikes, or misaligned resource provisioning. When estimates are consistently inaccurate, teams may face budget shortfalls, unnecessary over-provisioning, or wasted cloud investments. By improving cost accuracy, organizations gain tighter financial control and ensure that planned workloads align with real-world cloud consumption.

Formula: Architecture cost accuracy score = 100 – |(planned cost – actual cost) / planned cost| x 100

where: 

To calculate architecture cost accuracy score, follow these steps:

1. Define your planned costs.

Retrieve estimated costs for cloud workloads from your ITSM system (e.g., ServiceNow, Jira, or AzDo) or another budgeting system.

2. Compare against actual spend.

Extract real spending data from cloud billing sources over 30, 60, and 90-day intervals.

3. Apply the accuracy score formula.

Measure the deviation between estimated and actual costs.

Example query:

WITH ActualCosts AS (
    SELECT
        f.ResourceId,
        SUM(f.EffectiveCost) as actual_cost,
        MIN(f.ChargePeriodStart) as first_charge_date
    FROM focus_data_table f
    WHERE f.ChargePeriodStart >= DATEADD(day, -60, CURRENT_DATE)
    GROUP BY f.ResourceId
)
SELECT
    e.ResourceId,
    e.estimated_monthly_cost,
    a.actual_cost as actual_30day_cost,
    -- Accuracy Score
    100 - ABS((e.estimated_monthly_cost - a.actual_cost) /
        NULLIF(e.estimated_monthly_cost, 0)) * 100 as accuracy_score,
    -- Variance Analysis
    (a.actual_cost - e.estimated_monthly_cost) as cost_variance,
    -- Status Indicator
    CASE
        WHEN a.actual_cost > e.estimated_monthly_cost * 1.1 THEN 'Significantly Over'
        WHEN a.actual_cost > e.estimated_monthly_cost THEN 'Over Estimate'
        WHEN a.actual_cost < e.estimated_monthly_cost * 0.9 THEN 'Significantly Under'
        WHEN a.actual_cost < e.estimated_monthly_cost THEN 'Under Estimate'
        ELSE 'On Target'
    END as estimation_status,
    -- Deployment Context
    e.deployment_date,
    a.first_charge_date,
    DATEDIFF(day, a.first_charge_date, CURRENT_DATE) as days_since_deployment
FROM estimation_source e
JOIN ActualCosts a
    ON e.ResourceId = a.ResourceId
WHERE DATEDIFF(day, a.first_charge_date, CURRENT_DATE) >= 30;

4. Analyze and improve.

Identify consistent under- or over-estimations and adjust planning processes accordingly.

Success benchmarks

Target scores vary based on workload type and business needs.

Production workloads:

Development/testing environments:

By continuously refining cost estimation models, organizations can improve financial predictability, avoid unnecessary budget reallocations, and ensure cloud investments align with operational needs.

Optimized cloud spend rate

Maximizing cloud efficiency isn’t just about reducing spend—it’s about ensuring that every dollar spent is intentional and optimized. Optimized cloud spend rate measures the percentage of total cloud expenses that benefit from cost-saving strategies, including pricing optimizations (reserved instances, savings plans, enterprise agreements) and resource optimizations (right-sizing, scheduling, automated de-provisioning). 

A highly optimized spending rate indicates that a company is effectively leveraging cost-saving mechanisms to minimize unnecessary expenses. A low rate, on the other hand, signals missed opportunities, such as underutilized savings plans, oversized resources, or inefficient provisioning. Tracking this metric allows organizations to identify gaps in optimization coverage, validate their cost-efficiency strategies, and refine their approach over time.

Formula: Optimized cloud spend rate = (Spend covered by cost-saving mechanisms / total cloud spend) x 100

where: 

To calculate optimized cloud spend rate effectively, follow these steps:

1. Define your total cloud spend.

Aggregate all cloud service costs over a given period.

2. Identify cost-saving mechanisms.

Filter out spend covered by committed use discounts (reserved instances, savings plans, enterprise agreements) and resource optimizations (right-sizing, scheduling).

3. Apply the optimization rate formula.

Use structured queries to measure the proportion of optimized spend against the total cloud spend.

Example query:

SELECT
    ServiceName,
    ResourceType,
    SUM(ListCost) as TotalListCost,
    SUM(EffectiveCost) as TotalEffectiveCost,
    ((SUM(ListCost) - SUM(EffectiveCost)) /
        NULLIF(SUM(ListCost), 0)) * 100 as OptimizationRate,
    SUM(CASE
        WHEN PricingCategory = 'Committed'
        THEN EffectiveCost
        ELSE 0
    END) / NULLIF(SUM(EffectiveCost), 0) * 100 as CommitmentCoverage,
    COUNT(CASE
        WHEN CommitmentDiscountStatus IS NOT NULL
        THEN 1
    END) as OptimizedResources,
    COUNT(*) as TotalResources
FROM focus_data_table
WHERE ChargePeriodStart >= [start_date]
    AND ChargePeriodEnd < [end_date]
    AND ChargeCategory IN ('Usage', 'Purchase')
GROUP BY
    ServiceName,
    ResourceType;

4. Interpret the results.

Compare your optimization rate to industry benchmarks to assess performance.

Success benchmarks

The ideal optimized cloud spend rate varies by workload type:

Production workloads:

Development/testing environments:

Organizations should regularly evaluate and refine their optimization strategies to move up the maturity curve, ensuring cloud spend is proactively optimized rather than reactively managed.

Insight-to-action time

In 2025, automation isn’t just an advantage—it’s a necessity. Insight-to-action time measures how quickly a team identifies a cost-saving opportunity and implements the necessary action. The faster this process, the less waste accumulates, and the more efficiently cloud spending is optimized.

For example, an idle resource costing $1,000 per month—if identified and shut down within two days—saves $940 for that month. But if it takes ten days to act, the savings drop to $660. Across an entire cloud environment, these delays can compound into significant unrealized savings.

By tracking and improving this metric, organizations can eliminate approval bottlenecks, automate remediation, and ensure cost optimizations happen in near real-time—rather than weeks later. Companies that achieve faster Insight-to-Action Times gain a competitive edge in cost control, financial predictability, and cloud efficiency.

Formula: Insight-to-action (days) = Date implemented – date identified

where:

Follow these steps to calculate this metric accurately:

1. Log each cost-saving opportunity.

Create a table or structured tracking system with the following columns:

2. Calculate the time elapsed.

Use this formula to determine the duration between identification and action:

Insight-to-action time (days) = Date implemented – date identified

Example:

3. Track trends over time.

To gain meaningful insights, track and analyze average insight-to-action time across multiple opportunities:

Success Benchmarks

To maximize cost efficiency, organizations should set aggressive yet achievable insight-to-action targets based on their cloud maturity:

As teams improve automation, streamline approval processes, and integrate better FinOps tooling, these benchmarks should be continuously refined—reducing delays and ensuring cost-saving actions happen in near real-time.

Optimization velocity burndown

Cloud cost optimization will not work if it is treated as a one-off effort by the business—it must be an ongoing process with measurable progress over time. Optimization velocity burndown provides a clear, visual representation of how efficiently an organization executes cost optimizations against its goals.

This metric tracks the gap between the target optimization rate (the percentage of identified savings successfully realized) and the actual optimization velocity over a set period. It can also measure progress toward a specific total savings goal. A well-maintained burndown chart enables teams to monitor whether they are on pace, behind schedule, or exceeding their targets. 

For example, if an organization sets a quarterly goal of $250,000 in realized cloud savings and aims for a 10% weekly optimization velocity, this metric helps determine whether they are staying on track—or if adjustments are needed to accelerate cost reductions. If teams consistently fall behind, it may indicate approval bottlenecks, inefficient automation, or a lack of cross-functional alignment. Likewise, strong performance in this metric reflects an organization’s ability to execute optimizations efficiently, turning identified savings into tangible financial impact.

Formula: Optimization velocity burndown = Target optimization rate – actual optimization rate over time

where:

Follow these steps to effectively measure and visualize optimization velocity burndown:

1. Set your optimization goals.

2. Track identified vs. realized savings.

3. Plot the burndown chart.

Example:

The burndown chart visualizes progress by comparing the actual cumulative savings to the target trajectory, highlighting areas where adjustments may be necessary.

Success benchmarks

Organizations should adjust their optimization targets based on cloud maturity and business objectives:

A declining burndown trend indicates strong execution, while a flat or rising trend signals the need for improved automation, streamlined approval workflows, or better cross-team collaboration.

Users engaged with FinOps initiatives

FinOps success isn’t just about tracking cloud costs—it’s about embedding cost awareness and accountability across teams. Users engaged with FinOps initiatives measures the percentage of teams actively participating in cost optimization efforts, providing insight into how well FinOps principles are adopted across the organization.

A high engagement rate indicates that FinOps isn’t just confined to finance or cloud operations—it’s a company-wide discipline where engineering, finance, and leadership work together to optimize costs. In contrast, low engagement suggests that cost management is siloed, leading to missed savings, inefficient provisioning, and a lack of accountability.

Tracking this metric helps organizations identify gaps in FinOps adoption and implement strategies to build a cost-conscious culture, ensuring that teams proactively manage cloud spending rather than treating it as an afterthought.

Formula: Engagement rate = (Number of active users / total potential users) x 100

where:

Follow these steps to track FinOps engagement effectively:

1. Define the total potential user base.

Identify all stakeholders expected to engage in FinOps—this typically includes finance, engineering, and cloud operations teams.

2. Track active participants.

Count the number of users actively participating in FinOps initiatives within a given period (e.g., attending cost review meetings, implementing optimizations, or using FinOps tools).

3. Apply the engagement formula.

Use the formula to calculate engagement: Engagement rate = (Active users / total potential users) x 100

Example:

By tracking engagement over time, organizations can identify trends and adjust their approach to improve adoption. If engagement is low, potential barriers—such as lack of visibility, training gaps, or unclear ownership—should be addressed.

Success benchmarks

Ideal engagement levels vary based on an organization’s FinOps maturity and cloud complexity. General benchmarks include:

A low engagement rate suggests potential gaps in visibility, training, or alignment between cost accountability and operational goals. Organizations should monitor trends and refine communication, incentives, and training programs to improve FinOps participation.

Discover Augmented FinOps: The Future of Cloud Cost Management

Cloud cost tracking isn’t enough—real optimization requires automation. Augmented FinOps brings AI-driven intelligence to cloud financial management, enabling real-time savings and smarter cost control.

Download the Whitepaper

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How to find and utilize these metrics

Calculating and leveraging advanced cloud cost metrics requires more than just tracking numbers—it demands a structured approach that integrates tools, workflows, and collaboration to drive continuous optimization. Organizations that successfully implement these metrics move beyond static reporting to real-time insights and automated actions that reduce waste and improve cloud efficiency. Here’s how to build a workflow that transforms data into impact.

Adopt the right tools for unified visibility and automation

The foundation of effective cloud cost management is a platform that centralizes cost data across all cloud environments—including public cloud, private cloud, Kubernetes, and SaaS. CloudBolt provides this holistic view by aggregating cost, usage, and optimization insights into a single pane of glass.

For organizations earlier in their FinOps journey, native cloud tools like AWS Cost Explorer, Azure Cost Management, and GCP Cloud Billing offer baseline tracking, but they often require manual effort and integrations to create a full financial picture. Scaling FinOps maturity requires automation-first platforms that can detect anomalies, enforce tagging policies, and proactively surface cost-saving opportunities.

Establish workflows for ongoing cost optimization

Once the right tools are in place, organizations must establish repeatable workflows that embed these metrics into everyday cloud financial management. Key steps include:

Automate reporting cycles

Set up weekly or monthly dashboards tracking core metrics like insight-to-action time and optimized cloud spend rate. These reports provide real-time visibility into cost trends, making it easier to spot inefficiencies early.

Enable cross-team collaboration

FinOps isn’t a siloed practice. To ensure cloud cost decisions align with business objectives, organizations should foster communication between finance, engineering, and leadership. For example, engineering teams can share provisioning strategies while finance teams monitor budget adherence—ensuring cloud spending is both efficient and justified.

Integrate and automate key processes

Leverage API-driven integrations with ITSM platforms like ServiceNow or collaboration tools like Slack and Jira to automatically flag cost-saving opportunities. This reduces manual intervention, allowing FinOps teams to act swiftly rather than waiting for budget reviews.

Use AI for real-time anomaly detection

AI-powered tools can continuously monitor cloud spend for unexpected spikes and trigger automated actions. For example, if an underutilized instance exceeds a cost threshold, an automated workflow can resize or shut it down—preventing cost overruns before they happen.

Benchmark performance and refine strategies

Metrics should not be static—they should evolve alongside business needs. By tracking trends in architecture cost accuracy score and optimization velocity burndown over time, organizations can measure improvement, identify bottlenecks, and refine strategies for greater efficiency.

Common pitfalls to avoid

Even with the right metrics in place, organizations often encounter roadblocks that prevent them from realizing their full FinOps potential. Here are the most common pitfalls and how to avoid them.

Tracking too many metrics without focus

While cloud platforms generate vast amounts of cost data, tracking every available metric can lead to analysis paralysis rather than meaningful action. Teams that spread their attention too thin struggle to prioritize optimizations that drive impact.

Instead, organizations should focus on a core set of high-value metrics—like the seven outlined in this guide—that balance financial accountability with operational efficiency. Regularly reviewing your metric portfolio ensures alignment with evolving cloud and business objectives.

Failing to align metrics with business goals

Metrics are only useful if they connect cloud spending to real business outcomes. Without alignment, FinOps risks becoming an isolated cost-reporting function rather than a driver of financial strategy.

For example, tracking budget variance score without linking it to quarterly financial planning results in missed opportunities to proactively course-correct. Metrics should be integrated into business-wide objectives—ensuring that insights lead to strategic decision-making, not just reporting.

Neglecting automation and sticking to manual processes

Cloud cost management at scale cannot be sustained through manual workflows alone. Tagging, anomaly detection, and provisioning adjustments are time-intensive and prone to human error.

Organizations that fail to leverage automation-first FinOps solutions often struggle to scale their cost optimization efforts efficiently. Automating idle resource detection, rightsizing recommendations, and anomaly-based alerts reduces effort and accelerates cost-saving actions.

Ignoring cultural buy-in and cross-team engagement

FinOps isn’t just about data—it’s about driving accountability across teams. Organizations that don’t actively engage engineers, finance teams, and executives will struggle to execute optimizations effectively.

Tracking users engaged with FinOps initiatives provides a clear indicator of adoption and pinpoints where buy-in may be lacking. Regularly communicating wins, sharing savings impact, and embedding FinOps into existing workflows ensures alignment and long-term success.

Overlooking benchmarking and continuous improvement

Metrics lose value if they are treated as static benchmarks rather than evolving tools. Without historical trend analysis or industry comparisons, organizations risk stagnation rather than continuous improvement.

For example, organizations that fail to review their optimized cloud spend rate over time may miss recurring patterns of inefficiency. Establishing a cadence for benchmarking and refining strategies ensures that FinOps remains agile and responsive to changing business and cloud dynamics.

By proactively addressing these pitfalls, organizations can ensure their FinOps practices are scalable, sustainable, and aligned with broader strategic objectives.

A smarter path to cloud efficiency

At CloudBolt, we see a fundamental shift in how organizations approach cloud cost management. The traditional passive monitoring and reactive optimization model is giving way to what we call “automated intelligence”—where cloud cost insights automatically trigger optimizations in real time.

This transformation couldn’t come at a more critical time. Our enterprise customers deal with unprecedented cloud complexity, managing workloads across multiple providers and platforms. The old manual approaches to cost management simply can’t scale with today’s cloud environments, leading to missed optimization opportunities and unnecessary spending.

By adopting the seven strategic metrics outlined in this guide, organizations can move beyond reactive cost monitoring to a proactive, automation-driven strategy that optimizes cloud investments. These metrics—ranging from insight-to-action time to architecture efficiency score—provide the visibility, accountability, and efficiency needed to navigate today’s complex cloud landscape.

The organizations that thrive will be those that embrace automation as the cornerstone of their cloud financial management strategy. The industry’s current focus on better reporting tools and more detailed analytics misses the larger opportunity – using automation to eliminate the gap between identifying savings opportunities and realizing them.

CloudBolt can help you bridge the gap between insight and action. Schedule a demo today to see how automation-driven FinOps can transform your cloud financial management practices.

Take Action on Cloud Cost Optimization

See Augmented FinOps in Action

Stop reacting to cloud costs—start optimizing them in real time. CloudBolt automates cost-saving actions, accelerates insights, and brings AI-driven efficiency to your FinOps strategy.

Schedule a Demo

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The Software as a Service (SaaS) industry continues its robust expansion, significantly reshaping business operations on a global scale. In 2024, the global SaaS market was valued at approximately $209.95 billion, with projections indicating an increase to $231.75 billion in 2025. Looking further ahead, the market is expected to reach $510.67 billion by 2033, reflecting a compound annual growth rate (CAGR) of 10.38% during the forecast period from 2025 to 2033.

As SaaS adoption accelerates, businesses are grappling with the complexities of managing sprawling software portfolios. Without strategic oversight, the rapid proliferation of SaaS can lead to inefficiencies, redundant subscriptions, and unchecked spending. Implementing robust SaaS cost optimization practices ensures that organizations can harness the full potential of their investments while avoiding financial and operational pitfalls.

In this guide, we will explore 7 best practices for SaaS cost optimization, providing actionable insights to help your organization control spending, reduce waste, and align investments with strategic objectives.

The cost of neglecting SaaS optimization

Failing to prioritize SaaS cost optimization can have far-reaching consequences, from budget overruns to operational efficiency. Here’s a deeper look at the potential pitfalls of neglecting this crucial aspect of SaaS management:

1. Unnecessary overpayments

Without regular monitoring, unused or underutilized SaaS licenses can remain active, quietly siphoning funds from your budget. For example, a department might retain licenses for a project-specific tool long after the project ends. These overpayments add up quickly, diverting resources that could otherwise be invested in innovation, employee development, or revenue-generating initiatives. Organizations that lack visibility into their SaaS portfolio risk missing opportunities to reallocate funds where they matter most.

2. Duplication of services

When departments purchase software independently, redundant subscriptions often go unnoticed. For instance, one team might subscribe to a project management app while another uses a different tool with overlapping functionality. These duplications inflate costs unnecessarily and create administrative headaches when managing renewals, support, and integrations. Centralized oversight of SaaS purchases is essential to prevent these inefficiencies and streamline operations.

3. Budget overruns

Untracked SaaS renewals can wreak havoc on financial planning. Many SaaS contracts renew automatically, often at higher rates, leaving organizations with little time to assess whether the tools still provide value. These unexpected price hikes can lead to budget overruns, disrupting financial forecasts and impacting other areas of the business. Proactive renewal tracking and evaluation are critical to maintaining control over your software expenses. 

4. Wasted resources

Unmonitored SaaS usage can result in ongoing payments for tools that no longer align with organizational goals. For example, a company might continue paying for an advanced analytics tool that was adopted during a specific initiative but is now rarely used. These wasted resources represent not just financial loss but also missed opportunities to invest in high-impact areas, such as employee training or customer experience improvements. Regular audits can help identify and eliminate such inefficiencies.

5. Increased complexity

As SaaS portfolios grow, managing multiple vendors, contracts, and renewal timelines becomes increasingly challenging. Without a clear strategy, this complexity can overwhelm teams, leading to delays in decision-making and reduced efficiency. For instance, juggling contracts with dozens of vendors can slow down procurement processes or create confusion about which tools should be prioritized. A lack of streamlined SaaS management can leave businesses struggling to maintain agility in a competitive market.

Top 7 SaaS cost optimization best practices

Addressing these challenges starts with adopting a proactive, strategic approach. By implementing proven best practices, organizations can eliminate waste, streamline operations, and ensure every SaaS investment delivers maximum value.

1. Get complete spend visibility

Understanding where your SaaS budget is allocated is the foundation of cost optimization. Without a clear view of spending, unused subscriptions and overpayments can quickly add up, wasting valuable resources.

Centralizing all SaaS spend data into a single system allows you to monitor subscriptions, track usage patterns, and stay on top of renewal cycles. Regular SaaS audits play a critical role in this process by helping identify unused or duplicate software, as well as tools with overlapping functionality. 

These audits enable organizations to cancel unnecessary licenses, consolidate subscriptions, and merge multiple teams using similar tools—reducing costs and simplifying management. In addition to uncovering redundancies, audits provide valuable insight into renewal dates, contract terms, and pricing. 

This information makes it easier to renegotiate better terms, downgrade plans to align with actual needs, or eliminate underperforming tools altogether. By maintaining complete visibility into your SaaS spending, your organization can make informed decisions that align with business goals, optimize resource allocation, and maximize efficiency.

2. Consolidate overlapping apps and vendors

Relying on multiple providers for similar services can inflate costs unnecessarily and add complexity to management. Consolidating overlapping apps and vendors simplifies operations, reduces administrative overhead, and unlocks opportunities for bulk discounts. For example, merging separate cloud storage subscriptions into a single provider can significantly lower overall spending while streamlining oversight. 

Vendor consolidation also simplifies the management of SaaS contracts and renewals. With fewer vendors to negotiate with, you can secure better terms, reduce invoicing complexities, and improve visibility across your software portfolio. This approach not only reduces administrative workloads but also ensures that resources are used effectively and efficiently. 

By consolidating SaaS apps and vendors, your organization avoids overpaying for underutilized services and benefits from more favorable pricing and streamlines license management, delivering long-term value. 

3. Reclaim unused licenses with workflows

Unused SaaS licenses are a common source of wasted spending, but proactive management can turn this challenge into an opportunity for savings. By continuously monitoring SaaS usage, businesses can identify underutilized licenses and eliminate excess costs. 

For instance, if certain users don’t require advanced features, downgrading their accounts to a basic plan can yield substantial savings. Tracking usage patterns also helps avoid over-purchasing by ensuring your company only pays for what is actively used.

License harvesting workflows play a key role in reclaiming these unused assets. These workflows identify underutilized licenses and reallocate them to employees who need access, optimizing resource use without overspending. 

This approach also ensures employees have the tools they need to work effectively, striking the right balance between availability and cost efficiency. Adjusting subscriptions based on actual usage not only reduces waste but also builds a more cost-effective and agile SaaS portfolio.

4. Automate renewals to avoid surprises

Manually tracking SaaS renewals often leads to costly oversights, such as unexpected charges for unused subscriptions or missed opportunities to negotiate better terms. Automating renewal tracking ensures you stay ahead of deadlines and maintain control over your SaaS portfolio. This proactive approach allows you to focus on optimizing your software investments instead of managing complex renewal schedules. 

Automated renewal reminders enable businesses to evaluate the necessity of each subscription before it renews. For example, if a tool hasn’t been used recently, you can cancel or downgrade it prior to the renewal date, avoiding unwanted costs or price increases. 

Setting up alerts and workflows for renewal management not only reduces manual work but also prevents contracts from being overlooked. By integrating automation into your SaaS strategy, you can take timely actions that minimize waste and ensure cost-effective software spending. 

5. Prevent shadow IT

Shadow IT—the unauthorized purchase or use of software by employees or teams—poses a significant challenge for organizations managing multiple SaaS tools. This unregulated behavior can lead to duplicate applications, hidden costs, increased security risks, and a lack of overall control over your tech stack. Over time, this “SaaS sprawl” creates confusion, compliance risks, and unnecessary expenses that undermine efficiency and inflate costs. 

To effectively address shadow IT, proactive measures are essential. Regular audits can help identify unapproved apps, eliminate redundancies, and ensure resources are allocated effectively. Establishing a clear and straightforward approval process empowers employees to access the tools they need while adhering to company policies.

6. Use a SaaS management platform (SMP)

A SaaS management platform (SMP) is one of the most powerful tools for mastering SaaS cost optimization. By automating tedious tasks such as tracking renewal dates, monitoring usage patterns, and identifying underutilized or unused licenses, an SMP simplifies cost management and reduces administrative burdens. These platforms help organizations reassign or cancel licenses efficiently, ensuring that every dollar spent contributes to actual business needs.

Beyond automation, SMPs foster cross-departmental collaboration by centralizing workflows and enhancing visibility across the SaaS ecosystem. This centralization enables better decision-making and smoother operations, while custom workflows and role-based approval processes prevent unnecessary purchases or unnoticed actions. With an SMP, businesses can save time, control shadow IT, and minimize wasted resources, all while maximizing ROI on their SaaS investments.

Adopting an SMP provides complete visibility and control over your software portfolio, ensuring your organization operates efficiently and cost-effectively in an increasingly SaaS-driven landscape. 

7. Negotiate with price benchmarks

Negotiating SaaS contracts is an essential step in securing better pricing and optimizing your budget. By benchmarking vendor prices, you gain valuable insights into industry standards, ensuring you’re not overpaying. For instance, if your renewal price exceeds the market average, this information can be used as leverage to negotiate a lower rate.

Benchmarking also helps you select pricing models that best align with your organization’s needs. For example, transitioning from a pay-per-user plan to a volume-based pricing model can lead to significant savings if your team size justifies the shift. Regularly reviewing contracts and staying ahead of renewal deadlines prevents unnecessary price hikes and avoids overcommitting to long-term agreements at inflated rates. 

Being proactive in contract discussions ensures you achieve the best possible deal while maintaining flexibility. By leveraging price benchmarks, organizations can align their SaaS spending with strategic priorities, reduce costs, and maximize the ROI of their software investments. 

Emerging trends in SaaS cost optimization

As SaaS adoption continues to rise, organizations are turning to innovative strategies to enhance efficiency and reduce costs. By staying ahead of these developments, businesses can optimize their SaaS investments while positioning themselves for long-term success. 

1. AI-powered insights

Artificial intelligence (AI) and machine learning are revolutionizing SaaS management by providing real-time visibility into inefficiencies and waste. For example, AI-drive tools can identify inactive licenses or overlapping apps across teams, offering actionable recommendations for consolidation and contract renegotiation. These advanced analytics not only reduce manual oversight but also empower businesses to make data-driven decisions that unlock immediate cost savings.

2. Integrated management platforms

Managing SaaS, IaaS, and PaaS tools across departments is increasingly complex, but integrated platforms are streamlining operations. By consolidating workflows, tracking renewals, and providing a unified view of software portfolios, these solutions allow IT and finance teams to collaborate more effectively. A unified approach to oversight reduces redundancies, enhances visibility, and supports better resource allocation, making it easier to manage both SaaS and cloud environments cohesively.

3. Proactive vendor collaboration

Benchmarking tools have become indispensable for negotiating smarter vendor contracts. By comparing pricing, identifying savings opportunities, and exploring favorable terms like volume-based discounts, organizations are better equipped to optimize spending. Data-driven negotiation strategies ensure that businesses secure favorable terms while maintaining flexibility in their software agreements.

4. Sustainability in SaaS

Environmental, social, and governance (ESG) considerations are influencing SaaS purchasing decisions as organizations prioritize eco-conscious practices. Vendors offering energy-efficient infrastructure or carbon-neutral initiatives are becoming more attractive to businesses aiming to align their tech investments with broader sustainability goals. By consolidating tools and eliminating redundancies, organizations can reduce waste while advancing their ESG objectives.

CloudBolt and CloudEagle: Your partners in SaaS optimization

CloudBolt and CloudEagle offer the ideal partnership to help businesses leverage these trends and stay ahead in the evolving SaaS landscape. By combining CloudBolt’s robust cloud management capabilities with CloudEagle’s advanced SaaS optimization platform, organizations can achieve:

Together, CloudBolt and CloudEagle make it easier to implement the best practices outlined in this guide and prepare your SaaS strategy for the future.

Ready to optimize your SaaS stack? Take the next step in your SaaS optimization journey. Schedule a free demo today to see how CloudBolt and CloudEagle can help you simplify SaaS management, reduce costs, and achieve your business goals.

Frequently Asked Questions (FAQ) on SaaS Cost Optimization

1. What metrics should I track for effective SaaS cost optimization?

Tracking the right metrics is essential for identifying areas to reduce costs and improve efficiency. Metrics like license utilization rates, the average cost per user for each app, and app overlap (how many tools perform the same function) offer valuable insights. 

Renewal timelines are also critical, as they help you prepare for upcoming contract evaluations. By consistently tracking these metrics, businesses can build a clear picture of where spending is inefficient and take targeted actions to address it.

2. How do I prioritize which SaaS apps to optimize first?

When prioritizing SaaS apps for optimization, it’s best to start with those that have the highest costs but show the lowest levels of usage. Applications with overlapping features across departments should also be addressed, as consolidating them can lead to immediate cost savings. 

Additionally, focusing on tools with upcoming renewal dates gives you an opportunity to renegotiate terms or explore alternatives before committing to another contract cycle. For example, if two project management tools serve similar purposes, consolidating them into one platform reduces redundancy and streamlines workflows.

3. Are there risks in consolidating SaaS vendors?

Consolidating SaaS vendors offers many benefits, such as reduced complexity and cost savings, but it can also introduce risks. Relying too heavily on a single provider may create dependency, limiting your flexibility if the vendor raises prices or fails to meet expectations. 

To mitigate these risks, evaluate vendors thoroughly for scalability, reliability, and support. Negotiating contracts with flexible terms or escape clauses provides a safety net, and identifying alternative solutions ensures your business can adapt if issues arise.

4. What’s the difference between SaaS cost optimization and SaaS management?

SaaS cost optimization specifically focuses on reducing waste and maximizing the return on investment from SaaS tools. This includes eliminating unused licenses, consolidating overlapping apps, and renegotiating contracts for better pricing. 

SaaS management, on the other hand, encompasses broader responsibilities, such as maintaining security, ensuring compliance, and managing the lifecycle of all SaaS applications. While optimization is a key component, SaaS management involves a more holistic approach to the organization’s software ecosystem.

As businesses increasingly adopt cloud technologies, managing these environments has become more complex. To optimize resources, reduce costs, and accelerate service delivery, cloud automation and orchestration are essential components of modern IT strategies. 

This guide explores the distinct roles of cloud automation and orchestration and presents best practices to drive real business outcomes through these processes.

Cloud Automation and Orchestration: An Overview

Defining Cloud Automation

Cloud automation refers to the use of software tools, scripts, and workflows to perform specific tasks within a cloud environment without manual intervention. These tasks can include provisioning servers, configuring networks, managing storage, and deploying applications. By automating routine processes, cloud automation enables IT teams to scale operations more efficiently, reduce errors, and free up resources to focus on higher-value tasks.

Cloud Automation Diagram

Defining Cloud Orchestration

Cloud orchestration goes a step further by coordinating multiple automated tasks into comprehensive workflows that span across environments. While automation focuses on individual tasks, orchestration brings together these tasks, arranging them in a sequence that fulfills broader operational goals. For example, deploying a multi-tier application across a hybrid cloud environment might involve automating various tasks like setting up servers, configuring security protocols, and balancing network traffic. As IT environments grow more complex, orchestration allows organizations to maintain consistency, scalability, and performance across diverse cloud setups.

Cloud orchestration generally refers to combining numerous automations across any cloud necessary to achieve a broader goal.

What is cloud orchestration

Benefits of Cloud Automation

Cost Reduction

Cloud automation minimizes operational costs by streamlining processes like server provisioning, application deployment, and security management. Automated systems dynamically allocate resources, reducing underutilization and optimizing performance without manual intervention. This dynamic, real-time management reduces costs while maintaining optimal resource usage, a critical factor in modern cloud environments where agility is key.

For example, CloudBolt has enabled institutions, like a major U.S. university, to manage their cloud resources across multiple environments efficiently by automating resource provisioning, centralizing management, and enabling self-service access to critical IT resources. This automation reduced shadow IT, empowered faculty and students with flexible IT resources, and drove meaningful cost savings.

Scalability

Automation empowers organizations to scale their operations quickly as business needs evolve. Automated workflows allow cloud resources to be provisioned, adjusted, and decommissioned in response to real-time demand, preventing overprovisioning and reducing resource waste. By automating these adjustments, businesses can scale seamlessly, growing their cloud infrastructure alongside their organizational needs without manual intervention or downtime.

In the case of the university, CloudBolt’s solution helped the IT team scale cloud resources in response to increased demand from faculty and students. By offering self-service capabilities and on-demand provisioning, CloudBolt enabled efficient resource allocation during peak periods, which helped the university maintain a responsive and agile infrastructure.

Speed

Automation drastically accelerates the speed at which routine tasks are performed so operations that previously took hours or days take only minutes to be completed. Automating processes such as application deployment and resource configuration boosts overall business agility, allowing organizations to bring new services to market faster. This efficiency is crucial in industries where rapid innovation and responsiveness are competitive advantages.

Benefits of Cloud Orchestration

Improved Efficiency

Cloud orchestration ensures that automated tasks are not only performed efficiently but also in a coordinated manner. By streamlining complex workflows across various cloud environments, orchestration reduces bottlenecks and optimizes resource use. 

In hybrid and multi-cloud setups, advanced orchestration solutions allow for real-time resource coordination and load balancing, minimizing downtime and ensuring seamless operations across platforms. This holistic approach improves performance and maximizes resource utilization, making sure that every part of the infrastructure contributes to overall efficiency.

Enhanced Security

Orchestration plays a key role in maintaining security across cloud environments by ensuring that security protocols are consistently applied across automated workflows. This reduces the risk of breaches while meeting regulatory requirements. By automating security workflows through orchestration, organizations maintain real-time governance, minimizing vulnerabilities while enhancing operational flexibility.

Governance and Compliance

Operating across multi-cloud environments brings governance and compliance challenges. Orchestration enforces policies uniformly, aligning each automated task with company standards and regulatory needs. Advanced orchestration platforms help companies dynamically manage these requirements, minimizing compliance risks and streamlining audits.

Cloud Automation and Orchestration Use Cases

The combined power of cloud automation and orchestration is particularly evident in real-world applications, where they address complex challenges and enhance operational efficiency across various scenarios.

Multi-Cloud Resource Management

In multi-cloud environments, organizations often need to manage resources across various platforms like AWS, Azure, and Google Cloud. Cloud automation simplifies resource provisioning, while orchestration synchronizes workflows across platforms, dynamically balancing workloads and reducing downtime. By implementing an orchestration layer that provides unified visibility and intelligence across multi-cloud environments, businesses can optimize their operations and reduce silos that arise in complex infrastructures.

CI/CD Pipelines

Continuous Integration and Continuous Deployment (CI/CD) pipelines rely heavily on automation to manage repetitive tasks like code deployment, testing, and integration. However, as these processes scale, orchestration becomes essential for managing the flow of code between development and production environments. Orchestration coordinates testing, feedback, and deployment steps to streamline updates and reduce errors. 

Disaster Recovery

Disaster recovery depends on efficient, automated processes to minimize downtime. Automation helps by regularly backing up critical data and resources, while orchestration coordinates the complex recovery steps to minimize downtime. An orchestrated approach manages failover procedures, such as restoring data and rerouting traffic, so organizations can resume operations quickly after disruptions.

The integration of automated disaster recovery with intelligent orchestration means that organizations can minimize human intervention and react more quickly to recover from critical system failures.

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Common Challenges in Cloud Automation

Implementing cloud automation and orchestration can significantly enhance operational efficiency, but it also comes with its own set of challenges. Understanding these challenges and knowing how to address them is crucial for successful deployment and ongoing management.

Complexity of Legacy System Integration

Cloud automation often involves integrating existing infrastructure with modern cloud environments, which can be complex. Legacy systems may not be flexible enough to integrate seamlessly with cloud-based tools, requiring specialized expertise and potentially significant effort. Organizations must invest in proper planning, testing, and possibly upgrades to ensure smooth integration.

Tool Compatibility and Integration

In multi-cloud or hybrid environments, automating workflows with various cloud tools often requires seamless integration across platforms. If the right automation tools are not selected or configured properly, organizations can face significant compatibility issues that can slow down processes and create inefficiencies. Choosing automation platforms with open integration capabilities and strong APIs can help mitigate this challenge.

Skill Gaps

Cloud automation requires specialized knowledge, especially when working with more advanced tools or dealing with complex cloud environments. There is often a shortage of qualified professionals who can implement and maintain these systems effectively. Upskilling existing teams and partnering with vendors that offer robust training and support are key strategies to bridge this gap.

Common Challenges in Cloud Orchestration

Complexity of Multi-Cloud and Hybrid Environments

Orchestrating workflows across multiple cloud environments requires managing dependencies between different systems and maintaining seamless coordination. This complexity can increase as the number of cloud platforms and services grows, making it harder to monitor and manage all interactions effectively. Careful planning and the use of sophisticated orchestration tools designed for multi-cloud environments can help mitigate these challenges.

Security and Compliance Risks

Orchestrating tasks across different environments increases the risk of security breaches if not properly managed. Sensitive data moving between cloud platforms needs to be secured at all stages. Organizations must adopt security best practices such as encryption, secure APIs, and compliance monitoring to reduce risks. Automating these processes, along with strong security orchestration tools, can help consistently meet governance and compliance requirements.

Lack of Visibility and Monitoring

With multiple tasks and systems working together, maintaining visibility and tracking the progress of orchestrated workflows can become difficult. Without proper monitoring tools in place, organizations risk losing track of workflows, which can lead to delays or errors. Orchestration platforms with built-in monitoring and analytics capabilities provide the visibility required so tasks are executed correctly and on time.

Best Practices for Implementing Cloud Automation and Orchestration

Implementing cloud automation and orchestration requires careful planning and a strategic approach. By following best practices, organizations can transition smoothly, minimize risks, and maximize the benefits of these powerful technologies. For a comprehensive step-by-step approach, our Ready to Run eGuide offers a structured guide to implementing automation best practices.

Start Small and Scale

When introducing cloud automation and orchestration, it’s wise to start with simpler tasks before tackling more complex processes. Automating and orchestrating basic operations, such as routine backups or simple server provisioning, allows your team to test and refine strategies in a controlled environment. 

A phased approach not only minimizes risk but also promotes efficiency as automation scales. AI-driven automation platforms, like CloudBolt’s Augmented FinOps, can optimize this approach by proactively identifying opportunities, allowing businesses to scale intelligently and without unnecessary manual intervention.

Select the Right Tools

Choosing the right tools is crucial for successful cloud automation and orchestration. The tools should integrate with existing infrastructures, provide robust APIs for seamless integration, and scale with the organization’s needs. Platforms that leverage advanced AI/ML-driven insights can continuously optimize cloud environments, ensuring operational efficiency and cost savings in real-time.

Build a Strong Foundation with People and Processes

Effective cloud automation and orchestration requires skilled teams and defined processes. Investing in training prepares team members to handle the technical and operational nuances of automation. Additionally, defining clear roles and responsibilities minimizes overlap, increases accountability, and keeps automation workflows running smoothly. By mapping out existing workflows to identify where automation can enhance efficiency, organizations can reduce errors and establish a sustainable, scalable framework. Building this foundational layer creates resilience in cloud automation efforts, setting the stage for seamless scaling as business needs evolve.

Implement Full Lifecycle Automation

To fully realize the benefits of cloud automation and orchestration, businesses should aim to implement full lifecycle automation. This approach automates the entire cloud resource lifecycle—from initial provisioning to ongoing management and eventual decommissioning. By automating at every stage, resources are continually optimized for both performance and cost, eliminating waste and reducing operational overhead.

Lifecycle automation also empowers IT teams to be more proactive. AI-driven platforms can anticipate demand changes, predict resource needs, and adjust configurations automatically, ensuring smooth operations without manual intervention. With full lifecycle automation, businesses can unlock the power of continuous, efficient cloud management, allowing them to focus on strategic initiatives rather than routine tasks.

Align Automation with Real Business Outcomes and Financial Metrics

Cloud automation should be designed not just for operational efficiency but also as a strategic driver of business value. By aligning automation efforts with measurable financial outcomes, organizations shift automation from a purely technical initiative to a source of tangible ROI. Setting clear financial goals—such as cost savings, improved resource utilization, and overall ROI—enables teams to measure the impact of automation on the organization’s bottom line. 

Integrating FinOps metrics, like cloud spend per team or per service, helps pinpoint where automation delivers the highest return, providing a data-driven basis for refining strategies. Regularly reviewing these metrics ensures that automation remains adaptable to changing business needs and continues to deliver value. By grounding cloud automation initiatives in real business outcomes, organizations can more effectively demonstrate the financial and strategic benefits of their cloud investments.

Elevate Your Cloud Automation and Orchestration with CloudBolt

CloudBolt’s Augmented FinOps solution is uniquely positioned to enhance your cloud automation and orchestration efforts. By integrating advanced AI/ML-driven insights with full lifecycle automation, CloudBolt transforms how you manage cloud resources, ensuring that every automated task is not only executed efficiently but also contributes to a broader, strategic objective.

CloudBolt Optimization Dashboard

With CloudBolt’s Augmented FinOps, you can:

By adopting CloudBolt’s Augmented FinOps, you empower your organization to move beyond simple automation, achieving a level of orchestration that drives real business value. This holistic approach to cloud management not only addresses today’s challenges but also prepares your organization for the future, where intelligent automation and orchestration are key to staying competitive.

Don’t wait—transform your cloud operations today. Schedule a demo to experience how CloudBolt can elevate your automation and orchestration strategy to new heights.

Frequently Asked Questions (FAQs)

What is the difference between cloud automation and cloud orchestration?

Cloud automation is the process of using software tools and scripts to perform repetitive tasks within a cloud environment, such as provisioning servers or deploying applications, without requiring manual intervention. It streamlines individual tasks and enhances efficiency. Cloud orchestration, however, takes automation to the next level by coordinating multiple automated tasks into unified workflows. For instance, orchestration ensures that tasks like provisioning, security checks, and load balancing occur in the correct sequence, enabling complex processes like multi-tier application deployment to run seamlessly across hybrid or multi-cloud environments.

Why are cloud automation and orchestration important?

These technologies are critical for managing modern IT environments efficiently. Cloud automation reduces manual workload, eliminates errors, and accelerates routine tasks, while orchestration ensures these automated tasks work together toward strategic objectives. Together, they enable businesses to optimize resource usage, reduce costs, and improve agility, allowing them to adapt quickly to changes in demand or market conditions. For example, e-commerce companies can dynamically adjust their resources to handle high traffic during sales events, ensuring customer satisfaction and minimizing downtime.

What are the main challenges of implementing cloud automation and orchestration?

Organizations often encounter obstacles such as integrating legacy systems with modern cloud platforms, which may lack compatibility or flexibility. Tool compatibility across different cloud providers can also create roadblocks in multi-cloud or hybrid setups. Furthermore, skill gaps in IT teams often hinder the adoption and maintenance of automation and orchestration solutions. Security risks and compliance challenges, particularly when managing workflows across multiple cloud environments, add another layer of complexity that organizations must address through robust planning and technology selection.

How do cloud automation tools integrate with existing IT systems?

Modern cloud automation tools are designed with flexibility and integration in mind. They often feature robust APIs and connectors that allow seamless interaction with legacy systems, public cloud platforms, and third-party applications. For example, an automation platform can pull data from an organization’s on-premises infrastructure, analyze it in a cloud environment, and deliver results back to the original system. Organizations should prioritize selecting tools with open architecture and support for widely-used protocols to simplify integration and future-proof their IT investments.

What are some best practices for cloud automation and orchestration?

To successfully implement cloud automation and orchestration, organizations should start by automating simple tasks such as backups or server provisioning. Gradually scaling to more complex workflows allows teams to identify and address challenges early. Selecting the right tools that align with the organization’s current infrastructure and future needs is essential, as is investing in team training to build necessary skills. Establishing clear governance and compliance guidelines helps ensure consistency and security across all automated processes.

Can cloud automation reduce operational costs?

Yes, cloud automation significantly reduces operational costs by optimizing resource allocation, minimizing manual effort, and lowering the likelihood of errors. For example, automated scaling ensures resources are provisioned only when needed, avoiding overprovisioning. This is particularly useful in dynamic industries like media streaming or online retail, where demand fluctuates unpredictably. By aligning resource usage with real-time requirements, businesses can achieve substantial cost savings while maintaining performance.

How does AI enhance cloud automation and orchestration?

AI and machine learning bring intelligence to automation and orchestration, enabling systems to proactively identify inefficiencies, optimize resource usage, and adapt to changing workloads. AI-powered platforms can analyze historical usage patterns to predict future demands, automatically scaling resources to prevent performance bottlenecks. Additionally, AI enhances security by detecting anomalies in real time and automating responses to mitigate risks. These capabilities not only improve operational efficiency but also help organizations make data-driven decisions faster.

What industries benefit most from cloud automation and orchestration?

Industries with complex IT demands and rapid growth benefit the most from these technologies. For instance, financial services can use automation to handle high-volume transaction processing securely. Healthcare organizations leverage orchestration to manage patient data across cloud platforms while maintaining compliance. In education, universities automate resource provisioning for students and faculty, as demonstrated by a U.S. university that implemented CloudBolt to centralize resource management and reduce shadow IT costs. Retailers also benefit by dynamically scaling resources during seasonal spikes in demand.

What is full lifecycle automation in cloud management?

Full lifecycle automation refers to the automation of every stage of a resource’s lifecycle, from provisioning and configuration to scaling, optimization, and decommissioning. This approach minimizes waste and reduces manual effort throughout the resource’s lifecycle. For example, AI-driven platforms can anticipate changes in demand, adjust configurations proactively, and retire unused resources, ensuring cost-effective and efficient operations. Full lifecycle automation not only optimizes resource usage but also empowers IT teams to focus on strategic initiatives.

How can CloudBolt help with cloud automation and orchestration?

CloudBolt offers advanced solutions like Augmented FinOps, which combines AI-driven insights with robust automation capabilities. This platform allows organizations to automate repetitive tasks, coordinate complex workflows, and align cloud management with business objectives. For example, CloudBolt’s ability to integrate seamlessly with both legacy systems and modern cloud platforms enables IT teams to adopt automation without disrupting existing operations. These capabilities empower businesses to scale efficiently, control costs, and drive innovation in hybrid and multi-cloud environments.

Throughout this series, we’ve emphasized that automation is more than just technology—it’s about the people, processes, and principles creating a solid foundation for success. In the Crawl and Walk phases, we discussed establishing and scaling automation by focusing on these critical elements.

Now, in the Run phase, your organization is ready to refine and enhance its automation strategy. But the challenge here is not just about maintaining automation—it’s about ensuring your efforts are sustainable, scalable, and aligned with long-term business goals. In this final installment, we’ll explore how to embed continuous improvement, strategic alignment, and advanced technologies into your automation framework for sustained success.

Create a Culture of Continuous Improvement and Innovation

At the Run stage, automation should foster a culture of continuous improvement and innovation. Leading organizations apply continuous improvement frameworks like Kaizen or Six Sigma to automation processes. The Kaizen approach encourages all employees to make minor, incremental enhancements to processes, while Six Sigma provides a more formal, data-driven framework for reducing variation and improving efficiency. Blending these methodologies creates an environment where innovation and improvement become part of the everyday work culture.

Actionable Tip
Dedicate specific “innovation days” where teams have the freedom to brainstorm and test new automation ideas. This fosters a proactive problem-solving culture, where employees continuously look for ways to optimize and future-proof automation.


Innovation isn’t just about solving immediate problems; it should also focus on long-term growth and efficiency. Encourage teams to take a proactive approach to problem-solving by anticipating challenges and identifying opportunities for further automation. This could involve conducting regular what-if scenarios to explore potential future challenges or setting up dedicated innovation labs where teams can experiment with new automation ideas.

Align Automation with Strategic Objectives

As the organization’s long-term business goals evolve, so must automation initiatives. One way to maintain strategic alignment is to integrate dynamic planning processes where automation initiatives are regularly reviewed and adjusted to match evolving objectives. Static, multi-year automation plans can quickly become outdated in today’s fast-paced environment. Instead, focus on developing adaptive roadmaps that account for shifts in market dynamics, internal priorities, and emerging technologies.

Actionable Tip
Conduct quarterly strategic reviews to ensure your automation efforts remain aligned with the organization’s evolving objectives. Use these reviews to recalibrate initiatives, reprioritize projects, and incorporate feedback from key stakeholders.


Automation should be dynamic and flexible, ready to adjust to new business goals as they arise. Whether the company shifts focus to new markets, expands product lines, or responds to external pressures, automation must evolve alongside these changes. Regularly revisiting automation outcomes and strategic goals helps keep your efforts in sync with the bigger picture.

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Develop a Continuous Feedback Loop

To keep automation relevant and effective, organizations need a robust feedback loop. Collect feedback not only from individuals working on automation projects but also from cross-functional teams who may interact with these processes. Teams working on automation projects can review each other’s workflows and provide constructive feedback, fostering knowledge sharing and cross-functional collaboration.

However, not all feedback is created equal. Prioritize data-driven feedback backed by performance metrics to ensure that the most actionable insights are applied. By integrating feedback with data analysis, teams can focus on improvements that deliver the highest ROI.

Actionable Tip
After gathering feedback, hold regular "feedback resolution meetings" to communicate what actions have been taken in response. This shows employees that their input leads to tangible improvements, which builds trust and engagement in the automation process.


The key to effective feedback is closing the loop—ensuring that feedback not only leads to action but is communicated back to the team. Once employees see that their feedback leads to real changes, they will likely further engage and trust in the automation process.

Leverage Advanced Analytics

At this stage, automation should no longer rely on reactive data analysis. Instead, organizations should move toward predictive and prescriptive analytics to avoid potential issues and optimize workflows in real time. Predictive analytics allows teams to forecast future trends based on historical data, helping to identify bottlenecks before they occur or to anticipate resource needs in advance. 

Prescriptive analytics goes one step further, providing actionable recommendations on adjusting processes for optimal results. For example, these tools can automatically suggest adjustments to cloud resources or workflow changes based on real-time data, guiding teams toward the best outcomes for efficiency and cost-effectiveness.

Actionable Tip
Introduce prescriptive analytics tools that deliver recommendations on how to improve automation workflows. These tools can suggest resource reallocation or workflow adjustments, helping teams stay ahead of potential issues and maximize efficiency.


Risk Management

With increased automation comes increased risk. As automation takes over more processes, the potential for operational disruptions or security vulnerabilities grows. A comprehensive risk management strategy is essential to mitigate these risks. Start by developing a downtime recovery plan that outlines the steps to take in the event of system failures. This plan should include both immediate responses and long-term recovery strategies.

Equally important are security audits. Conduct regular assessments to ensure your automation systems comply with the latest security standards and regulatory requirements, such as GDPR or CCPA. Proactive risk management not only safeguards operations but also ensures that automation initiatives remain compliant and sustainable in the long run.

Actionable Tip
Assemble a dedicated risk management team responsible for monitoring automation workflows for security vulnerabilities, compliance risks, and operational threats. Regularly update your risk protocols to address new challenges as they arise.


Conclusion

The Run phase of automation is about ensuring your efforts are sustainable, scalable, and continuously improving. By fostering a culture of continuous innovation, aligning automation with strategic business objectives, leveraging advanced analytics, and managing risks effectively, you set your organization up for long-term success. 

By following the principles outlined in the Crawl, Walk, and Run phases, your organization can achieve a seamless, sustainable automation journey that drives efficiency, innovation, and competitive advantage well into the future.

Thank you for following this three-part series on successful automation. If you’re ready to take your automation efforts to the next level, CloudBolt’s Augmented FinOps solution can guide you every step of the way—from automating repetitive tasks to achieving real-time optimization and strategic cloud cost alignment. Download our Ready to Run: A Guide to Maturing Your FinOps Automation ebook, and book a demo to see it in action and discover how our platform can accelerate your journey to the Run stage of FinOps automation.

In our previous post, we explored how to lay the groundwork for automation by focusing on the essential processes and principles that must be in place before introducing technology. As your organization progresses to the Walk phase, the focus now shifts from laying the groundwork to scaling these initiatives. 

Scaling automation isn’t simply about deploying more technology. It’s about creating a supportive environment that embraces automation while managing the changes it brings. Without the right cultural support and change management, even the best automation tools can fall flat. Let’s take a closer look at the steps you need to take to scale automation effectively.

Effectively Communicate Automation’s Value

Embedding automation into the very fabric of your operations requires a shift in mindset across the organization. While resistance is natural—especially if employees are concerned about job security or changes to their workflows—leaders must champion automation efforts and communicate its value clearly and consistently. Automation isn’t just about replacing jobs; it’s about freeing up time for more strategic activities, such as data analysis, optimization, and creative problem-solving.

One of the most effective ways to build confidence in automation is by sharing data-driven success stories from within the organization. These stories should illustrate automation’s tangible impact on key business metrics, such as a 20% reduction in manual processing time or a 30% increase in cloud cost efficiency

Actionable Tip: Create a centralized success tracker where teams can log and share improvements driven by automation. Review this data quarterly to celebrate wins and identify areas for further enhancement.

By showcasing internal wins, you build momentum for broader adoption and demonstrate how automation directly contributes to your organization’s goals. 

Managing Change

Scaling automation requires a comprehensive change management plan that outlines how workflows will change, who will be affected, and what support will be provided during the transition. Without a clear roadmap, automation initiatives can cause confusion and inefficiencies. 

Start by clearly defining the objectives of your automation efforts and mapping out specific changes. Next, establish a realistic timeline that allows for gradual change so employees have enough time to adjust and leadership can monitor the impact. Finally, allocate both human and financial resources to support a smooth shift.

Actionable Tip: Assign change champions within each department to act as liaisons between employees and leadership. These champions reinforce communication and ensure employees have a dedicated point of contact to address concerns.

Empowering key employees to champion automation increases buy-in and provides a clear point of reference for team members during the transition.

Training and Upskilling

As automation scales, the complexity of tools and processes often increases, requiring specific technical skills and domain knowledge to operate them efficiently. To address this, organizations should implement targeted training programs and provide ongoing support to ensure employees are equipped with the knowledge and skills needed to operate automation tools efficiently.

One of the most effective ways to manage the increasing complexity of automation is through tiered training programs that cater to different levels of expertise. By offering role-based training, organizations can ensure that employees receive the specific knowledge they need based on their position and interaction with the tools. For example, operations staff may need more hands-on technical training, while leadership might benefit from understanding how to use automation data for strategic decision-making.

Actionable Tip: Encourage employees to use sandbox environments to experiment with automation settings without impacting live processes. This builds confidence in their skills and allows for hands-on learning.

To further motivate your team and enhance their expertise in cloud automation, consider encouraging them to pursue industry-recognized certifications, like AWS Certified Solutions Architect – Professional, which focuses on automation and cloud architecture. Companies can offer financial support by covering exam fees, providing paid study time, and tying certifications to career advancement opportunities like promotions or leadership roles. Additionally, recognizing and rewarding employees who achieve certifications fosters a culture of continuous learning and motivates others to follow suit.

Measuring Impact

Measuring automation’s long-term impact goes beyond tracking basic KPIs. While metrics like efficiency gains, cost savings, and resource optimization are important, evaluating how automation aligns with strategic goals and drives business transformation is critical.

For example, ask yourself: Is automation enabling teams to shift focus toward higher-value tasks? Is it improving decision-making through real-time insights? Could automation be optimized in other areas to reduce time-to-market or enhance customer satisfaction?

It’s also essential to track leading indicators—such as reduced manual touchpoints or improved process accuracy—that signal the effectiveness of automation before larger business outcomes are realized. Leading indicators give early insights into whether your automation initiatives are set up for success or need adjustment.

Actionable Tip: Set up real-time dashboards that track both immediate KPIs and leading indicators tied to long-term business objectives. Conduct quarterly reviews of these metrics to assess progress and recalibrate efforts if needed.

Iterative Improvement

Automation is not a set-it-and-forget-it solution. Successful organizations take a continuous improvement approach, always looking for ways to optimize and refine their automated workflows. This mindset ensures that automation remains efficient, adaptable, and aligned with changing business needs.

Post-implementation reviews can be especially effective as they provide dedicated time for teams to assess what worked well and what needs improvement. Experimentation and iteration allow teams to refine their automation efforts gradually, which can lead to significant performance gains over time.

Actionable Tip: Encourage teams to adopt a "fail fast, learn faster" approach. Implement regular post-automation retrospectives, where the focus isn't just on what worked, but on rapid testing of new hypotheses to improve efficiency. For instance, introduce A/B testing for automated workflows or run small-scale pilots of new iterations before full-scale rollouts. Tracking performance gains after each tweak helps drive incremental improvements over time.

Conclusion

Scaling automation isn’t just about deploying more tools—it’s about creating a culture that embraces automation and managing the changes that come with it. You create an environment where automation can thrive by clearly communicating the value of automation, managing change effectively, upskilling your workforce, and fostering continuous improvement.

In the final installment of this series, we’ll explore the Run phase, where continuous improvement in automation aligns with your organization’s long-term strategic objectives. Stay tuned for Part 3 as we explore how to fully integrate automation into your operations.

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Automation is often synonymous with technology—tools, software, and platforms that promise to streamline operations and boost efficiency. However, successful automation is more than just the tools; it’s about the people who implement it and the processes it enhances. This blog series focuses on the non-technical elements of automation—the people, processes, and principles that form the bedrock of any successful strategy.

In this first installment, we’ll explore how to lay the groundwork for automation by focusing on essential processes and principles. True automation success doesn’t start with the latest tools but with building a solid foundation that ensures your organization is ready for the journey ahead.

Assess Current Capabilities

Before diving into automation, evaluate your current processes. This is a crucial first step. Map out workflows and identify bottlenecks, inefficiencies, and repetitive tasks prone to error. Are there gaps in your current documentation? Inconsistent workflows across departments? By understanding these shortcomings, you can prioritize which processes to automate first. Building automation on a weak foundation risks compounding inefficiencies, not solving them. 

Actionable Tip:
Tools like Lucidchart or Visio can help create visual representations of workflows, detailing each step, decision point, and responsible party. Once you have clarity, use these insights to shape automation goals that address inefficiencies.

After evaluating, pinpoint gaps that could prevent successful automation. These might include outdated technology, inconsistent workflows, or a lack of standardized procedures. Addressing these gaps early ensures that automation is built on solid ground.

Finally, establish clear, measurable objectives for your automation initiatives using the SMART framework (Specific, Measurable, Achievable, Relevant, Time-bound). For instance, you might aim to reduce manual data entry by 50% within six months. Having well-defined objectives provides direction and allows you to measure the success of your automation efforts.

Document and Standardize Processes

Detailed process documentation is the backbone of effective automation. Everyone involved should understand workflows, ensuring consistency across the board. Without thorough documentation, automation can lead to confusion and inefficiencies. To start, you can create process maps that detail each step in your workflows, including inputs, outputs, decision points, and responsible parties. This level of detail not only aids in automation but also helps identify any areas that need improvement before automation begins.

Actionable Tip:
Prioritize standardization if your processes are siloed or ad hoc across teams. This ensures automation is applied universally and helps keep everyone aligned. 

Equally important is standardizing processes across teams. This ensures that automation efforts are consistent, regardless of who executes them. It also reduces the risk of errors and makes scaling automation across the organization easier. For example, if different departments handle customer data differently, standardizing these processes ensures that automation can be applied universally, leading to more reliable outcomes. Standardization also simplifies training and onboarding, as new employees can quickly learn the standardized processes.

Ready to Run: A Guide to Maturing Your FinOps Automation

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Cross-Functional Collaboration

Automation initiatives often touch multiple departments, from IT to operations to finance, so it’s essential to involve representatives from all relevant teams early. This collaboration helps ensure that automation aligns with the organization’s broader objectives and has the support of all stakeholders. When departments work in silos, it’s easy for automation efforts to become fragmented or misaligned with overall business goals so encourage open communication, regular check-ins, and cross-functional teams to ensure that everyone is on the same page. 

Actionable Tip:
Use tools like Asana, Slack, or Microsoft Teams to facilitate real-time communication, project tracking, and issue resolution. Regular check-ins ensure alignment and help address concerns as they arise.

Pilot Testing

Before rolling out automation across the entire organization, it’s wise to start with small-scale pilot tests. These tests allow you to identify potential issues and gather feedback before scaling up. For example, you might start by automating a single repetitive task, such as invoice processing, and then expand automation efforts based on the pilot’s success.

Actionable Tip:
You may want to run a mock scenario to simulate how the process improvements would work and identify any adjustments before fully committing resources. 

After you’ve completed the small-scale testing, gather honest feedback about what worked well and what didn’t and use it to refine your processes. Iterative testing and feedback loops help optimize automation before full deployment, minimizing costly errors or disruptions during the broader rollout.

Conclusion

Building a strong foundation is the most critical step in the automation journey. By thoroughly assessing your current capabilities, documenting and standardizing processes, fostering cross-functional collaboration, and conducting pilot tests, you prepare your organization for automation success. These steps ensure that your automation efforts are built on a well-prepared foundation, minimizing risks and maximizing benefits.

In the next blog, we’ll explore the Walk phase—scaling automation with a focus on culture and change management. We’ll discuss how to create a supportive environment that embraces automation and manages the changes it brings. Stay tuned for Part 2 of this essential series on successful automation!

In a world where advancements in technology and innovation are moving at breakneck speed, FinOps is crawling at a snail’s pace. Whether it’s curating reports, tagging resources, or forecasting cloud spend, many FinOps teams currently rely heavily on manual processes. This limited and outdated approach prevents FinOps from delivering the business value it should and can.

If your team is struggling with manual workflows, our Ready to Run: A Guide to Maturing Your FinOps Automation eGuide provides actionable strategies to transition from manual processes to full automation, driving efficiency and greater ROI. 

But first, let’s explore why manual FinOps processes are no longer enough.

The Problem with Manual FinOps Processes

At first glance, manual processes may seem manageable, especially for smaller cloud environments or early-stage FinOps teams. But as cloud usage grows, the limitations of manual FinOps quickly become apparent:

If any of this sounds familiar, it’s time to start thinking about automation. 

Ready to Run: A Guide to Maturing Your FinOps Automation

Assess your automation maturity and unlock strategies for scaling your FinOps practice.

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How Automation Transforms FinOps

FinOps automation is about more than just speeding up processes—it’s about empowering teams to act faster, make smarter decisions, and ultimately drive greater ROI from cloud investments. Here are three key areas where automation can make an immediate impact:

1. Real-Time Insights

Manual FinOps processes mean relying on historical data to make decisions, which can be outdated by the time teams act on it. Automation provides real-time visibility into cloud usage, costs, and performance, enabling FinOps teams to act quickly and decisively. This immediate access to current data helps organizations proactively manage their cloud environments, preventing unnecessary spend before it happens and empowering teams to course-correct when anomalies arise.

2. Cost Optimization at Scale

Automation tools continuously monitor cloud resources and make real-time adjustments to optimize usage without requiring human intervention. Whether it’s rightsizing instances or decommissioning idle resources, automation ensures that cloud environments are always running at peak efficiency. This proactive approach to cost optimization helps FinOps teams keep spending under control, even as cloud usage scales and becomes increasingly complex. The result is not just reduced costs but also the ability to handle optimization at a scale that would be impossible with manual processes.

3. Standardized Workflows

Without automation, different teams may use their own methods to manually manage cloud costs, leading to inconsistencies and potential errors. Automation enables standardized workflows that ensure consistency, accuracy, and accountability across the organization. These workflows establish a unified approach to cloud cost management, reducing the risk of oversight and providing a single source of truth for all teams to rely on. This standardization helps streamline decision-making and fosters cross-department collaboration, ultimately creating a more efficient FinOps culture.

Start Your Automation Journey Today

The longer FinOps teams rely on manual processes, the more they risk falling behind in today’s fast-paced cloud landscape. Automation is the key to scaling your operations, driving greater efficiency, more accurate forecasting, and a stronger strategic impact. 

Ready to accelerate your FinOps journey? Download Ready to Run: A Guide to Maturing Your FinOps Automation to understand where your team stands in its automation maturity and unlock strategies to transform your operations.

In January 2024, CloudBolt laid out an ambitious vision for Augmented FinOps—a paradigm shift in how organizations manage their cloud investments. Our goal was clear: to integrate AI/ML-driven insights, achieve full lifecycle cloud optimization, and expand FinOps capabilities beyond public clouds. Today, we’re proud to announce that we have laid the bedrock of this vision with the launch of our game-changing platform and its latest innovations: Cloud Native Actions (CNA), the CloudBolt Agent, and the Tech Alliance Program—with even more transformative developments on the horizon.

Cloud Native Actions (CNA)

At the heart of our new platform lies Cloud Native Actions (CNA), a solution designed to transform the traditionally manual and reactive nature of FinOps into a fully automated, ongoing optimization process. CNA continuously optimizes cloud resources, preventing inefficiencies before they occur and accelerating the speed of optimization efforts. With CNA, FinOps teams can automate complex cloud processes, significantly increasing efficiency and reducing the time spent on manual tasks.

CNA’s core benefits include:

In short, CNA moves organizations from reactive cloud cost management to a proactive, continuous optimization model, keeping cloud resources operating at peak efficiency.

CloudBolt Agent

Another cornerstone of CloudBolt’s recent innovation is the CloudBolt Agent, which extends the power of our FinOps platform to private cloud, Kubernetes, and PaaS environments. The agent allows enterprises to unify their cloud environments under one optimization strategy, facilitating seamless application of cloud-native actions across different infrastructures. By providing intelligent automation and real-time data collection, the CloudBolt Agent eliminates the silos that often prevent effective multi-cloud management.

Key benefits of the CloudBolt Agent:

By unifying cloud management, the CloudBolt Agent empowers enterprises to realize the full potential of hybrid and multi-cloud environments, driving ROI and improving operational efficiency.

Tech Alliance Program

Finally, CloudBolt is expanding its reach through the Tech Alliance Program, a strategic initiative designed to enhance the FinOps experience by building a network of integrated solutions. This growing ecosystem reinforces CloudBolt’s commitment to driving value and innovation for FinOps teams—delivering key components of our larger vision while opening up new possibilities for what comes next.

The Tech Alliance Program focuses on:

With the Tech Alliance Program, CloudBolt connects customers with a rich ecosystem of best-in-class solutions that complement FinOps practices and maximize the value derived from cloud investments.

Augmented FinOps is Here

Today’s launch marks a significant step in CloudBolt’s mission to deliver the next generation of FinOps solutions. With Cloud Native Actions, the CloudBolt Agent, and a growing network of partners through the Tech Alliance Program, we’re not just responding to the needs of today’s FinOps teams—we’re shaping the future of cloud financial management. For more details, check out our official press release.

To further explore how AI, automation, and next-gen tools are transforming FinOps, we invite you to join us for an exclusive webinar featuring guest presenter Tracy Woo, Principal Analyst at Forrester Research, on October 22, 2024. Register now for FinOps Reimagined: AI, Automation, and the Rise of 3rd Generation Tools and learn about the future of FinOps.

If you want to see our platform in action, our team would be happy to show you how the new Cloud Native Actions, CloudBolt Agent, and Tech Alliance Program can help your organization optimize cloud investments. Request a demo today!

We are thrilled to announce that CloudBolt has listed its Cloud Management Platform (CMP) and Cloud Cost & Security Management Platform (CSMP) in the AWS Marketplace for the U.S. Intelligence Community (ICMP). 

ICMP, a curated digital catalog from Amazon Web Services (AWS), allows government agencies to easily discover, purchase, and deploy software solutions from vendors that specialize in supporting federal customers. Our advanced solutions are now accessible to help agencies maximize value while maintaining compliance with strict security standards. 

This listing represents a significant milestone in our mission to empower federal agencies by providing the tools necessary to manage complex cloud environments—whether public, private, hybrid, or air-gapped—with the efficiency and governance they need to meet their mission-critical objectives. 

For more details, you can read our full press release here