The Lakehouse Optimizer

The cloud financial management tool for Databricks users

Identify unnecessary jobs, inefficient data pipelines, and suboptimal resource utilization.

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TANGIBLE SUCCESS

Clients save 30% on TCO &
improve performance by 50%

See value in
3 easy steps

Monitor
Databricks utilization

Discover recommendations

Take action,
reduce costs

The Lakehouse Optimizer provides you…

Intelligent forecasting:

Receive financial predictability and stability of your organization’s spend

Unity Catalog migration assessment

Evaluate the current state of your Databricks environment to determine its readiness for migration to Unity Catalog and identify the necessary work for the transition.

Executive insights engine:

Ability to allocate cost and measure performance by department, project, and initiative

Intelligent recommendations:

Receive specific, actionable recommendations tailored to your organization’s environment

Pool contention reporting:

Understand how to minimize latency for new workloads and maximize throughput

Autoscaling insights:

Identify inefficiencies and optimal autoscaling policy configurations

Common challenges → Big wins

LHO's practical impact on your business

Engineering leader receives an unexpectedly high bill

Scenario
The VP of Engineering receives a bill for last month’s Databricks usage that's much higher than expected, threatening the annual budget just a few months into a 12-month contract.
LHO solution
LHO breaks down cost drivers, identifying specific projects or inefficiencies causing the spike. It provides recommendations to optimize resource usage, reduce costs, and set up budget controls to prevent future overspending.

Monitoring budget against forecasted spend

Scenario
The FinOps manager is responsible for ensuring that Databricks spend aligns with the company’s financial forecasts. Midway through the quarter, they notice that spending is trending higher than anticipated and need to course-correct before it impacts the overall budget.
LHO solution
LHO provides real-time insights into current spend versus forecast, helping the FinOps manager identify areas where costs are exceeding projections. It offers actionable recommendations to optimize resource allocation and adjust usage patterns, keeping the spend within the forecasted budget.

Cost management and optimization

Scenario
A data engineering team is tasked with reducing cloud spending on Databricks. They need to track resource usage across multiple projects and departments and identify areas where costs can be reduced without impacting performance. *Ask: how easy is it for the customer to find this detail?
LHO solution
LHO provides detailed cost breakdowns and insights, allowing the team to see exactly where money is being spent and offering recommendations for optimizing resource usage, such as right-sizing clusters, improving job configurations, and avoiding idle resources.

Performance tuning of data pipelines

Scenario
A data platform team notices that certain pipelines are taking longer to run, leading to delays in data processing and analytics reporting. They need to identify and resolve performance bottlenecks.
LHO solution
LHO helps by analyzing pipeline performance, identifying inefficient queries, underperforming jobs, or resource bottlenecks, and providing actionable insights on how to optimize these components for better performance.

Engineering leader receives an unexpectedly high bill

Scenario
The VP of Engineering receives a bill for last month’s Databricks usage that's much higher than expected, threatening the annual budget just a few months into a 12-month contract.
LHO solution
LHO breaks down cost drivers, identifying specific projects or inefficiencies causing the spike. It provides recommendations to optimize resource usage, reduce costs, and set up budget controls to prevent future overspending.

Monitoring budget against forecasted spend

Scenario
The FinOps manager is responsible for ensuring that Databricks spend aligns with the company’s financial forecasts. Midway through the quarter, they notice that spending is trending higher than anticipated and need to course-correct before it impacts the overall budget.
LHO solution
LHO provides real-time insights into current spend versus forecast, helping the FinOps manager identify areas where costs are exceeding projections. It offers actionable recommendations to optimize resource allocation and adjust usage patterns, keeping the spend within the forecasted budget.

Cost management and optimization

Scenario
A data engineering team is tasked with reducing cloud spending on Databricks. They need to track resource usage across multiple projects and departments and identify areas where costs can be reduced without impacting performance. *Ask: how easy is it for the customer to find this detail?
LHO solution
LHO provides detailed cost breakdowns and insights, allowing the team to see exactly where money is being spent and offering recommendations for optimizing resource usage, such as right-sizing clusters, improving job configurations, and avoiding idle resources.

Performance tuning of data pipelines

Scenario
A data platform team notices that certain pipelines are taking longer to run, leading to delays in data processing and analytics reporting. They need to identify and resolve performance bottlenecks.
LHO solution
LHO helps by analyzing pipeline performance, identifying inefficient queries, underperforming jobs, or resource bottlenecks, and providing actionable insights on how to optimize these components for better performance.
Monthly bill management

Engineering leader receives an unexpectedly high bill

Scenario
The VP of Engineering receives a bill for last month’s Databricks usage that's much higher than expected, threatening the annual budget just a few months into a 12-month contract.
LHO solution
LHO breaks down cost drivers, identifying specific projects or inefficiencies causing the spike. It provides recommendations to optimize resource usage, reduce costs, and set up budget controls to prevent future overspending.
Monitor budget

Monitoring budget against forecasted spend

Scenario
The FinOps manager is responsible for ensuring that Databricks spend aligns with the company’s financial forecasts. Midway through the quarter, they notice that spending is trending higher than anticipated and need to course-correct before it impacts the overall budget.
LHO solution
LHO provides real-time insights into current spend versus forecast, helping the FinOps manager identify areas where costs are exceeding projections. It offers actionable recommendations to optimize resource allocation and adjust usage patterns, keeping the spend within the forecasted budget.
Cost Management

Cost management and optimization

Scenario
A data engineering team is tasked with reducing cloud spending on Databricks. They need to track resource usage across multiple projects and departments and identify areas where costs can be reduced without impacting performance. *Ask: how easy is it for the customer to find this detail?
LHO solution
LHO provides detailed cost breakdowns and insights, allowing the team to see exactly where money is being spent and offering recommendations for optimizing resource usage, such as right-sizing clusters, improving job configurations, and avoiding idle resources.
Performance tuning

Performance tuning of data pipelines

Scenario
A data platform team notices that certain pipelines are taking longer to run, leading to delays in data processing and analytics reporting. They need to identify and resolve performance bottlenecks.
LHO solution
LHO helps by analyzing pipeline performance, identifying inefficient queries, underperforming jobs, or resource bottlenecks, and providing actionable insights on how to optimize these components for better performance.
Michael Hallak, Director of Product, Blueprint Technologies

Michael Hallak

Director of Product Sales

Right-size compute resources and optimize storage costs to eliminate waste in your environment with the Lakehouse Optimizer.

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Blueprint Technologies are AWS partners
Blueprint Technologies work within Google Cloud environments to solve cloud and infrastructure solutions.

Featured project stories

Read how LHO has powered our customer solutions

WEBINAR SPOTLIGHT

Achieving unified governance for data and AI

Unity Catalog migration powered by LHO

Is migrating to Unity Catalog on your to-do list? This webinar will leave you with a comprehensive understanding of how to efficiently migrate and optimize your lakehouse for good.

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Frequently asked questions

The Lakehouse Optimizer is available for a 30-day Free Trial in the Azure Marketplace to deploy on your own.

You can follow this guide for assistance. If you would rather have a guided experience, Blueprint can help you through your AWS or Azure deployment to get you up and running.

With LHO you can see not only your spend, but understand if its healthy or unhealthy, while getting transparency across the organization for the attributed spend. You can even drill all the way down to individual autoscaling events or code block execution of an individual job run for a workflow executed and see both Azure and Databricks costs represented.

The Lakehouse Optimizer is most commonly used by managers to receive alerts about critical issues, such as nearing budget limits, unexpected cost spikes, or unusual spending patterns. These alerts help managers quickly identify and address potential problems.

For developers, the Lakehouse Optimizer is often used while writing data pipelines. As they write code, LHO guides them in properly configuring clusters and selecting the right resources. This ensures that the code is optimized for the resources needed and that the appropriate tools are used for each task.

Absolutely.
The Lakehouse Optimizer offers features that help you identify relevant data and optimize your jobs or workflows. It provides detailed recommendations, total cost analysis, and other insights that guide you in making the necessary adjustments for improved performance and efficiency.

If you’re focused on specific jobs or clusters, start by reviewing the ones you’re responsible for and see what insights the Lakehouse Optimizer offers. Check if there are any recommendations for optimizing performance or reducing costs.

For those overseeing broader operations, it’s helpful to begin with a high-level view of your tenant or workspace. This will give you a clear picture of where spending is concentrated within Databricks and your cloud provider, providing a strong starting point for further analysis and optimization.

The Unity Catalog Migration Assessment evaluates your current Databricks environment to determine its readiness for migration to Unity Catalog. It also identifies the specific steps required for a successful transition. With Blueprint’s proven expertise, we have achieved a 100% success rate in Unity Catalog migrations.

Databricks Center of Excellence 

Your one-stop Databricks partner

Databricks Data & AI Governance Partner of the Year 2024
Databricks Data and AI Summit 2022 Americas Partner Velocity Award

Ready to try it out for free? Contact us!

Intelligent forecasting:

Receive financial predictability and stability of your organization’s spend

Unity Catalog Migration Assessment:

Evaluate the current state of your Databricks environment to determine its readiness for migration to Unity Catalog and identify the necessary work for the transition.

Executive insights engine:

Ability to allocate cost and measure performance by department, project, and initiative

Intelligent recommendations:

Receive specific, actionable recommendations tailored to your organization’s environment

Pool contention reporting:

Understand how to minimize latency for new workloads and maximize throughput

Autoscaling insights:

Identify inefficiencies and optimal autoscaling policy configurations