Guide to Microsoft Fabric Cost & Budget

Microsoft Fabric: Streamlining Costs, Budgets, and Usage Insights

Unlock the full potential of Microsoft Fabric with smart budgeting and cost management strategies.

A Comprehensive Guide to Microsoft Fabric Cost, Budget, and Usage Patterns

In today’s data-driven world, managing operational costs efficiently is critical for any organization. Microsoft Fabric provides a robust platform for storing, processing, and analyzing data, but understanding its cost structure is essential to making the most of the resources available. This guide provides a detailed look at how to manage costs in Microsoft Fabric by understanding the key components—compute, storage, and automation—while offering actionable strategies for optimizing usage and staying within budget.

1. Understanding Microsoft Fabric's Licensing Models

Microsoft Fabric offers two primary licensing models that directly impact costs:

Pay-As-You-Go (PAYG): This model allows businesses to scale resources up or down based on immediate demand. It is perfect for organizations with unpredictable workloads, as charges are only incurred when resources are actively used. However, PAYG can be more expensive in the long run if not managed efficiently due to its flexibility.
Reserved Capacity: In contrast, this model offers a significant discount—often up to 41%—for organizations that can predict their resource needs over time. Reserved Capacity is ideal for businesses that have consistent, ongoing workloads, allowing them to lock in lower rates while ensuring resources are available at all times.

Choosing the right model depends on your organization’s workload patterns. PAYG is ideal for short bursts of high activity, while Reserved Capacity provides more value for long-term, consistent operations.

2. Separation of Compute and Storage Costs

One of the unique aspects of Microsoft Fabric is the ability to separate compute and storage costs. This flexibility allows organizations to optimize each aspect of their resource needs based on the specific demands of their workloads.

Compute Costs:

Compute costs are driven by the amount of processing power used. The more compute-intensive the task, the higher the cost. For example, large data analysis projects, real-time data processing, and complex reporting may require higher levels of compute power.

Storage Costs:

Storage costs are based on the amount of data physically stored in the system. Fabric charges for storage continuously, making it critical to manage how much data is being retained and ensure that unnecessary data is purged or compressed to keep storage costs down.

This separation allows businesses to fine-tune their spending by allocating more budget toward compute resources when necessary, or focusing on efficient storage strategies when data volume is the primary concern.

3. Managing Storage in Microsoft Fabric

Microsoft Fabric provides multiple storage types, each designed for different use cases:

OneLake Storage: The default storage option in Fabric, OneLake is cost-efficient but does not offer disaster recovery. This is ideal for temporary or easily replaceable data, with pricing starting at $0.023 per GB/month.
OneLake BCDR: Offering Backup, Cloning, and Disaster Recovery (BCDR) functionality, this option ensures that critical data is protected with built-in recovery mechanisms. This comes at a slightly higher cost of $0.0252 per GB/month.
OneLake Cache: Specifically designed for KQL cache storage and retaining Data Activator data, OneLake Cache costs $0.24 per GB/month. It is essential for organizations requiring quick, real-time access to data that needs to be cached for performance reasons.

Choosing the right storage option can drastically affect both the operational efficiency and the cost of running Microsoft Fabric. Organizations should evaluate their storage needs based on data recovery requirements, performance expectations, and budget constraints.

4. Optimizing Compute Capacity

Microsoft Fabric offers several Service-Level Units (SLUs), known as SKUs, that provide different levels of compute capacity. These SKUs scale to meet a variety of workloads, from small projects to massive enterprise-level data operations.

For example:

F2: Suitable for small workloads, offering up to 300 million rows per table, with a maximum of 3 GB of memory.
F64: Designed for more complex workloads, allowing for up to 1,500 million rows per table and 25 GB of memory.
F2048: For the largest enterprise needs, supporting up to 24,000 million rows per table and 400 GB of memory.

Selecting the right SKU for your workloads is crucial to managing costs effectively. Smaller workloads may not require high-tier SKUs, and over-provisioning can lead to unnecessary spending. Conversely, under-provisioning can lead to performance bottlenecks that affect operational efficiency. Monitoring compute usage and adjusting the SKU accordingly helps avoid wasted resources.

Also, if there’s need to scale up when you need more computing power, you can scale up the capacity for a certain period. For example, in one scenario, we scheduled refresh time for some semantic models in the same time frame. The F2 capacity is not enough to complete all the refresh, then we used logic apps to schedule capacity up to F64 time for 1 hour and now the operation runs smoothly without having to pay for the full reservation cost for F64 capacity. Also, the cost is the deduction of F2 reserve cost from F64 cost for that particular time.

Also, here’s an example of another scenario according to current cost structure:

As we can see running F16 for daily 9 hours on PAYG saves you money comparing running on reservation. In this case, you’ll have to run approximately 15 hours to have a better return on your bucks:

Scaling up and down option is available in azure portal if you want to manually change the capacity each time.

5. Automating Cost Management with Logic Apps

One of the most powerful tools for optimizing Microsoft Fabric usage is the implementation of Logic Apps. These automation tools allow organizations to control when compute and storage resources are used, ensuring resources are only active when needed.

Key Automation Features:

Scheduled On/Off Times: Logic Apps can automatically turn compute resources on and off at specific times. For example, compute resources can be turned on at the beginning of the workday (8 AM) and turned off when not in use (5 PM), preventing unnecessary charges during idle hours.
Dynamic Scaling: Logic Apps can automatically adjust compute capacity based on real-time demand. During periods of high usage, resources can be scaled up to meet the need, and scaled down during low-demand periods. This dynamic scaling ensures that resources are optimized based on actual usage rather than manual estimation.

By automating these tasks, organizations can save a significant amount of money on compute and storage costs, making Logic Apps a valuable tool for cost-conscious businesses.

Here is an example of a power bi report backed by logic apps to dynamically scale up and down the capacity.

6. Using PowerShell for Backup and Cost Automation

PowerShell scripts can be used to automate many tasks within Microsoft Fabric, including backup management. Automated backups help to reduce the operational overhead associated with managing data, while ensuring that critical data is protected and that resources are only used when necessary.

Benefits of Automating Backups:

Cost Reduction: Backups can be scheduled to run during off-peak hours, ensuring that they do not interfere with critical processing tasks. This not only reduces the risk of performance degradation but also optimizes the use of compute resources, lowering costs.
Data Protection: Automation ensures that backups are run regularly and that no critical data is missed. PowerShell can be configured to handle large-scale backup processes, integrating seamlessly with Logic Apps to further streamline the process.

By automating both backup schedules and data management tasks, organizations can ensure that they are using their resources efficiently while protecting their data.

7. Optimizing Costs with Microsoft Fabric Copilot

After enabling these Preview Features our first job is to assign the report with the right capacity. And of course, Cop

Microsoft Fabric Copilot features are powerful tools that automate data analysis, report generation, and other resource-intensive tasks. However, it is important to understand that not all Copilot features are available across all Fabric licenses.

Businesses need to assess their specific requirements and determine which Copilot functionalities are available based on their current licensing tier. This ensures that they are not overspending on unnecessary tools or missing out on features that could streamline their operations.

Example of Copilot Features:

Power BI Copilot: Assists with generating data reports and visualizations with minimal input, saving time and compute resources.
Copilot in Fabric: Automates routine tasks within the platform, reducing manual intervention and optimizing resource usage.

Carefully selecting the appropriate Copilot feature ensures that businesses are maximizing the value of their Fabric environment.

ilot requires Fabric F64 or P1 capacity.

8. Practical Use Cases for Managing Fabric Costs

Here are some real-world strategies for managing Microsoft Fabric costs:

Pay-As-You-Go for Spikes: If your organization experiences unpredictable demand, using PAYG ensures that you only pay for the resources you need, when you need them. For instance, if there are sudden bursts of activity, PAYG allows for rapid scaling without upfront costs.
Reserved Capacity for Predictable Workloads: For consistent, long-term projects, Reserved Capacity provides significant savings by locking in lower rates. This is ideal for organizations that can forecast their compute and storage needs over time.
Automating Scaling with Logic Apps: Automatically scaling compute capacity during peak periods ensures that your organization is only using the resources it needs at any given time. For example, you can scale compute up during the workday and down during off-hours to save on costs.
Automating Backups with PowerShell: By automating backups and other routine tasks with PowerShell, you can ensure that data is always protected without manually managing these processes. This reduces both time and resource costs.

9. Key Performance Indicators (KPIs) for Monitoring Usage and Costs

To manage costs effectively, it is essential to monitor key performance indicators (KPIs) within Microsoft Fabric. The Capacity Metrics App provides valuable insights into:

CU Utilization Over Time: Monitoring how much compute capacity (CU) is being used allows businesses to identify areas where they are either over- or under-utilizing resources.
Throttling Instances: Identifying when compute resources are being throttled helps to pinpoint bottlenecks that may be caused by over-provisioning or insufficient capacity.
Top 10 Storage Consumers: Knowing which datasets or workspaces are consuming the most storage can help you decide where to implement cost-saving strategies, such as data compression or purging unused data.

By keeping a close eye on these metrics, organizations can make informed decisions about where to allocate resources and how to optimize their usage.

Managing costs in Microsoft Fabric requires a deep understanding of the platform’s licensing models, compute and storage costs, and the automation tools available to optimize resource usage. By leveraging Logic Apps, PowerShell scripts, and Copilot functionalities, businesses can ensure they are getting the most value from their resources while keeping costs under control.

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