Best 12 Azure cost optimization tools compared

Pick any two Azure cost optimization tools, and their feature pages will look almost identical. Be it rightsizing, idle resource detection, commitment management, or anomaly alerts, you’ll notice real differences only when you try using them:

• A tool that flags idle resources but can’t tell you which team or product they belong to
• Rightsizing recommendations built on a few days of CPU data that don’t account for end-of-month spikes
• Multi-cloud platforms that nail AWS optimization but treat Azure’s billing model and tagging logic as a secondary concern

With cloud spending at $723 billion in 2025, we can see that a lot of money is going to tools that may or may not be doing their job well. To manage it without breaking the banks, pick the right optimization tool. We reviewed 12 of them and put together this guide to help you pick the right one.

A quick note: Turbo360 is our product, and it’s on this list. We build Azure cost optimization and monitoring tools, so we know this space from the inside. That said, we’ve done our best to keep this review fair. Every tool here is evaluated on the same criteria, and we’ve called out limitations where we see them, including our own.

TL;DR our top picks at a glance

What does Azure cost optimization actually mean?

Azure cost optimization is when you continuously review how your cloud resources are being used and make adjustments to cut unnecessary spend. It doesn’t simply mean slashing budgets. Here, you’re making sure every resource you’re paying for is actually doing something useful, at the right size, in the right tier.

It’s not a one-time cleanup, either. Azure runs on consumption-based pricing. So your costs will change whenever a workload changes, a new service is added, or someone scales something up and forgets to scale it back down.

What problems do these tools solve?

You don’t overspend on Azure because you’re careless. You may end up overspending because cloud environments get complex fast. After a certain point, it becomes hard to keep track of what’s running, who owns it, and whether it still needs to be there.

Cost optimization tools help with a few things:

• Finding idle and orphaned resources like unattached disks, forgotten test environments, and VMs that haven’t done real work in weeks
• Rightsizing recommendations that tell you when a resource is bigger than it needs to be, and what to scale it down to
• Reserved instance and savings plan guidance so you know when it’s safe to commit for a discount instead of paying on-demand rates
• Scheduling and automation to shut down non-production resources outside business hours
• Anomaly detection that flags unusual cost spikes before they snowball into a huge invoice

And this is getting trickier with AI workloads in the mix. Training runs and model experimentation create unpredictable spikes in compute and storage that traditional cost monitoring wasn’t really designed for.

Gartner’s Sid Nag has pointed out that cloud use cases are expanding across hybrid and multicloud setups, which means more services and more cost variables for teams to stay on top of.

Azure cost optimization vs. Azure cost management: what’s the difference?

Azure cost management tells you where the money’s going. It’s the dashboards, the reports, the trend lines. Cost optimization is what you do with that information, for example, resize a VM, delete an orphaned disk, or commit to a savings plan. You need both, but the tools in this list are on the optimization side of that line.

This guide covers Azure cost optimization tools. If you are looking for Azure cost management tools, we recommend reading our dedicated guide linked above.

What to look for in an Azure cost optimization tool?

Before we get into the tools, let’s look at the criteria you need to have in your Azure Cost Optimization tool.

• Rightsizing recommendations: Does the tool look at actual CPU, memory, and runtime trends over time, or does it just flag anything below a threshold? The best recommendations should observe sustained usage patterns and then tell you exactly what to resize to.
• Idle and orphaned resource detection: There are some resources, like unattached disks, unused IPs, forgotten snapshots, or dev environments, that could be idle for months and still incur cost. A good tool detects them early and ranks them by their savings potential.
• Reserved Instance and Savings Plan management: Committing to reservations can cut compute costs by up to 72%, but only if you’re using existing commitments. You need a tool that tracks underused RIs and Savings Plans, spots coverage gaps, and recommends adjustments.
• Automated scheduling: Non-production workloads running 24/7 are one of the most common sources of avoidable cost. A tool that can automatically stop dev and staging environments during off-hours (and bring them back in the morning) saves money every month.
• Business context in recommendations: Raw Azure metrics tell you a VM is running at 12% CPU. But that’s not very useful if you don’t know the team that owns it, the product it supports, or the business impact of resizing. Look for tools that connect all that cost data back to teams, products, or customers, making it actionable.
• Azure-native depth: Azure has its own billing model, reservation logic, tagging hierarchies, and cost allocation structure. Multi-cloud tools will only generalize across providers, and that means they miss features that are specific to how Azure works. If Azure is your primary cloud, then a purpose-built tool will give you more relevant recommendations than one adapted from AWS.
• Action vs. advice: Some tools give you a report. But only some execute changes, like shutting down resources on a schedule, purging unused storage blobs, or changing access tiers. Depending on how much manual work your team can absorb, this distinction matters a lot.

The best 12 Azure cost optimization tools

We’ve gone through each tool on the same criteria we covered above. Some are Azure-native platforms, and some are multi-cloud options. Here are our top picks.

1. Turbo360

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What it does

Turbo360 connects to all your Azure tenants and subscriptions, pulls in the billing data, and allocates costs based on how your organization is structured (by team, product, customer, whatever your tagging schema looks like).

From there, it rightsizes VMs by looking at CPU and memory trends over several weeks, catches idle resources before they pile up on your invoice, and tracks whether your Reserved Instances and Savings Plans are actually being used.

It can also shut down dev and staging environments after business hours on its own and run automated workflows for things like purging old storage blobs.

Strengths

• Full Azure cost lifecycle in one platform
• Continuous idle resource detection
• RI and Savings Plan gap tracking
• Automated off-hours shutdown
• Cost allocation by team, product, customer
• Budget governance with auto-enforcement

Best for: Teams managing complex Azure setups who want cost optimization and monitoring in one place.

What to watch out for: It’s Azure-only, so if you’ve got workloads on AWS or GCP, you’ll need something else for those.

What customers say: “We love the valuable insights the product offers and how efficiently it helps us to resolve platform issues. We can quickly create dashboards from system data, giving you a clear understanding of what’s happening within your system.”

2. Ternary

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What it does

Ternary connects to all three major cloud providers and all that billing data into one place. It rightsizes compute, databases, storage, and Kubernetes; flags idle resources; and manages commitment-based discounts like RIs and Savings Plans.

The recommendations link directly to Jira tickets, so engineering teams pick them up as part of their normal sprint. It doesn’t take automated actions on your infrastructure, though, so there’s no auto-shutdown or auto-rightsizing.

Strengths

• Multi-cloud feature parity
• Bi-directional Jira integration
• Agentless, SaaS, or self-hosted
• Strong unit economics reporting
• ML-powered anomaly detection

Best for: Multi-cloud teams (AWS, Azure, GCP) that want a single FinOps platform with strong reporting and Jira-based workflows.

What to watch out for: Since Ternary doesn’t automate optimization actions directly, your team still handles the execution. For organizations that want hands-off automation (like scheduled shutdowns or automatic rightsizing), that’s a gap worth considering.

What customers say: “Ternary’s software platform is easy to use, simple to set up, and incredibly intuitive. We rarely have any customers who run into problems with their membership dashboard, and the sign-up process takes less than 3 minutes.”

3. Umbrella (formerly Anodot Cost)

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What it does

Umbrella is an AI-driven cost management platform that collects billing data from all three major clouds (along with Kubernetes & SaaS tools). It has a waste detector that automatically identifies all the waste and ranks them by savings impact in your environments by scanning for idle resources, orphaned volumes, outdated snapshots, and underutilized databases.

It can also capture RI/SP combinations as you actually use them to determine which discount coverage you will have the most on the commitment side.

Strengths

• Adaptive ML-powered forecasting
• CostGPT for ad-hoc cost queries
• Priority ranking of waste detection.
• 18-24 months data retention at any granularity
• Multi cloud + Kubernetes visibility

Best for: Multi-cloud FinOps teams looking to forecast and identify waste across AWS, Azure and GCP.

What to watch out for: No automatic execution. You will receive CLI instructions to use when making copies of your scripts, but Umbrella will not close down or change tiers for you. Limited role permissions have also been marked as a limitation by users and can be confusing in larger organizations.

What customers say: “It provides real-time visibility into cloud costs, usage, and performance. This allows organizations to identify and eliminate cost anomalies as they happen.”

4. Holori

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What it does

Holori is a FinOps platform for the AI era. It pulls costs from AWS, Azure, and GCP into a single interactive dashboard. What stands out is the diagram view that visually maps your entire infrastructure.

It also simulates what would happen cost-wise if you moved workloads to a different provider. And if your native tagging is a mess, Holori’s virtual tags let FinOps teams label resources in bulk.

Strengths

• Custom alerts through Slack, Teams, and email
• Shared cost policies to split expenses across teams
• Reusable dashboard templates per department
• Budget monitoring with threshold notifications
• Weekly automated cost reporting

Best for: Multi-cloud teams that want infrastructure visualization alongside cost management.

What to watch out for: The diagram gets hard to read in wider environments. Users have flagged occasional sluggishness with large data sets, and a few features are still listed as “on the roadmap.”

What customers say: “Tracking our cloud costs by customer was super complicated before Holori. Now it’s easy and we can track shared costs as well.”

5. Spot by NetApp (Acquire by Flexera)

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What it does

Spot pairs CloudCheckr’s cost management platform with NetApp’s professional services team. Their experts set up and configure the tool for your environment, scan your infrastructure, and sit down with your team to review recommendations.

They’ll also help remediate issues they find, covering cost, security, and compliance.

Strengths

• Expert-led setup and configuration
• Combined cost, security, and compliance analysis
• Flexible engagement (one-time, monthly, quarterly)
• Mandatory tagging enforcement for cost segregation
• Single dashboard for full infrastructure footprint

Best for: Teams that need professional services alongside their cost optimization tooling.

What to watch out for: The availability of instances depends on the cloud provider and region, so optimization strategies around spot pricing can fluctuate. Also the remediation part is capped at 2 days per engagement; anything beyond that costs extra.

What customers say: “Spot enables us to assign mandatory tags on all deployed resources, which helps in cloud resource cost segregation quickly.”

6. Kubex

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What it does

If your main cost problem is oversized VMs and containers, Kubex is worth a look. It runs ML across your cloud environments (Azure, AWS, GCP) and studies how workloads have been performing over weeks.

Then it tells you which instance type and family to switch to. Your engineers can wire it into Terraform or Azure Resource Manager so the right sizes are selected automatically during deployments.

Strengths

• Effort and compatibility scoring per change
• Wires into CI/CD and IaC pipelines
• Container-level K8s rightsizing
• Agentic AI with MCP interface support
• Generates impact reports for stakeholder sign-off

Best for: Engineering teams looking for compute and Kubernetes rightsizing with CI/CD integration.

What to watch out for: It doesn’t cover network costs. And if you’re managing lots of accounts, there are no saved filter presets. That means you’ll have to re-select the same groups manually each time.

What customers say: “Kubex has brought a level of clarity and control to our cloud resource optimization that frankly feels like a superpower.”

7. ProsperOps

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What it does

ProsperOps takes over your Reserved Instance and Savings Plan portfolio and manages it autonomously. It adjusts your commitment coverage 24/7 as your usage changes. So, rest assured that you’re always getting the best discount without over-committing.

There’s also a resource scheduler that shuts down non-prod environments (EC2, RDS) on a schedule and syncs with the discount engine.

Strengths

• Fully autonomous discount management
• Scheduler syncs with commitment coverage
• Tracks the effective savings rate and lock-in risk
• Multi-cloud (AWS, Azure, GCP)
• Pays for itself from generated savings

Best for: FinOps teams who want commitment management on autopilot across AWS, Azure, and GCP.

What to watch out for: Pricing isn’t transparent upfront, which is why estimating what you’ll pay can be tricky. Here, advanced customization and detailed reporting are limited, too.

What customers say: “ProsperOps has a fairly simple one-time setup, after which we’ve seen monthly savings with no attention required on our part.”

8. Sedai

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What it does

Sedai’s big pitch is safety. It uses patented reinforcement learning to optimize your cloud, and it does it in small, gradual steps so nothing blows up. You can start in Copilot mode, where you approve each change with a click, then move to Autopilot once you trust it.

It rightsizes workloads continuously based on how your apps actually behave, and then compacts your clusters so you’re not paying for empty nodes. It also handles cost attribution and shows you who’s spending what.

Strengths

• Eight US patents on safe autonomous action
• Copilot-to-Autopilot progression
• Cluster compaction after rightsizing
• Updates IaC without crossing guardrails
• Used by Palo Alto Networks, Experian, and HP

Best for: Engineering teams that want autonomous cloud optimization but are worried about breaking production.

What to watch out for: Setting it up on production environments isn’t straightforward. Most teams need hands-on help from Sedai’s team for the initial deployment.

What customers say: “I like how Sedai has continuous cloud cost and can help maximize ROI.”

9. nOps

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What it does

nOps automatically buys and manages your RIs, Savings Plans, and CUDs so you don’t have to. It uses something called adaptive laddering, which means it commits to small, frequent increments rather than big bulk purchases.

It recalculates optimal coverage every hour, which is handy if your workloads are spiky or seasonal. You also get multi-cloud cost visibility, dashboards, and anomaly detection.

Strengths

• Adaptive laddering for flexible commitments
• Hourly coverage recalculation
• FinOps AI agent for cost queries
• Integrates with Slack, Jira, Datadog, Snowflake
• Pays for itself (percentage-of-savings pricing)

Best for: AWS-heavy teams that want commitment management to run on its own, with some Azure and GCP support.

What to watch out for: Some of the more advanced reporting is an add-on. Without it, the reports can feel a bit thin.

What customers say: “They are very transparent and are truly committed to saving you money. Integration is straightforward, and their dashboard is useful.”

10. Lucidity

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What it does

Lucidity is a storage-specific tool. Most organizations pay for roughly 3x the block storage they actually use, and Lucidity goes after that gap. It works across AWS, Azure, and GCP.

Lumen scans every disk in your environment, scores it against actual IOPS, throughput, and latency data, and tells you if it should be on a cheaper tier. It also finds four types of idle disks: unattached, reserved, unmounted, and zero-I/O.

AutoScaler takes it further and autonomously expands or shrinks volumes in real time based on actual usage, with no downtime.

Strengths

• Autonomous block storage scaling
• Four-type idle disk detection
• Conversational AI for storage queries
• Free self-serve assessment tool
• Works across AWS, Azure, and GCP

Best for: Teams whose biggest cost problem is cloud block storage, and less on the compute side.

What to watch out for: It’s narrow by design. If storage isn’t your main cost driver, this tool won’t help much with the rest of your cloud bill.

What customers say: “It’s been a really positive experience partnering with Lucidity. They’re an engineering-centric organization, and their team has led with accountability across each engagement.”

11. Azure Advisor

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What it does

Azure Advisor reviews how resources are being used over time from your telemetry data and identifies VMs that are underutilized and opportunities to buy reservations. Every recommendation includes a proposed action that you can take in the portal. It’s free, a great advantage. However, there are true boundaries.

It does not provide you with a single view of multiple subscriptions, there is no team or product cost allocation, there is no anomaly detection, and there is no automated cleanup. All recommendations require manual effort on your part.

Strengths

• Free and included in the Azure portal
• Addresses cost, security, performance and reliability
• Make recommendations, with suggestions on what to do in-line.
• No setup or installation required
• Personalized per subscription

Best for: Azure teams with existing infrastructure who are looking for a cost estimation solution out of the box.

What to watch out for: It’s difficult to get a complete view of idle resources across multiple subscriptions, and data is often fragmented. No automation for actions taken based on what it finds, and cleanup is manual.

What customers say: “It’s like having a dedicated architect constantly reviewing your setup for free. It flags real issues and gives you easy steps to save money and improve security.”

12. CloudZero

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What it does

CloudZero is built around one idea: cost per anything. It connects your cloud and AI billing data to business dimensions, so you can see what it costs to serve a specific customer, run a specific feature, or support a specific product line. Its allocation engine handles shared costs (think Kubernetes clusters, multi-tenant services, AI model inference).

It covers 50+ cloud and AI providers. Where CloudZero falls short is on the action side; it’s strong on intelligence and attribution, but won’t automatically shut down resources or apply rightsizing changes for you.

Strengths

• Cost-per-customer and cost-per-feature attribution
• Self-training anomaly detection
• Dedicated FinOps Account Manager
• Supports 50+ cloud and AI providers
• Custom dimensions for budgets and reporting

Best for: SaaS companies and engineering teams who need to tie cloud spend back to customers, features, and products.

What to watch out for: Getting detailed usage metrics means building separate Analytics dashboards each time. The standard Explorer view doesn’t go deep enough on its own, which gets tedious.

What customers say: “CloudZero was incredibly flexible, allowing us to bring our own dimensions in and customize our views to get a holistic view of the entire estate.”

How to choose the right tool for your team

Thirteen tools is a lot, we know. So here’s a simpler way to think about it…

Wrapping up

If there’s something we can vouch for, it’s that no single tool is perfect. As our framework suggests, some are great at commitment management, others at rightsizing, and a few try to cover the whole picture.

The right choice depends on what’s actually burning money in your Azure environment.

If you’re not sure… start there.

Is it oversized VMs? Idle resources nobody remembers creating? Commitments that aren’t being used? Is it oversized VMs? Idle resources nobody remembers creating? Commitments that aren’t being used? Pick a tool that solves it from this list.

We built Turbo360 because we kept seeing Azure teams use three or four tools to do what should be one job. If that sounds familiar, give it a spin. There’s a 14-day free trial, which doesn’t require a credit card. So, get started with your free trial and see how much you’re leaving on the table.