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Belgium 20-10-2026 Squad Only Virtual English

Deciding What Runs Where: Cloud, Edge, On-Prem, or Hybrid; How to place workloads based on performance, cost, sovereignty, resilience, and AI requirements.

Cloud decisions are becoming more selective. The challenge is deciding where each workload should run based on cost, performance, control, resilience, sovereignty, and business need. Three pressure points usually drive the decision. - Cost visibility becomes harder when usage grows across cloud services, data platforms, and AI workloads. - Performance and latency matter more when systems need fast access to data or support operational processes. - Sovereignty and resilience become critical when data location, continuity, vendor dependency, and exit options enter the discussion. The working question is simple: how do we place workloads where they create the most value while keeping the hybrid landscape manageable? If these trade-offs are on your agenda, let’s compare how others are handling similar choices.

Belgium 10-11-2026 Squad Only Virtual English

Choosing the Right Data Platform Without Creating New Silos; How to balance speed, flexibility, semantics, governance, and long-term maintainability.

Data platforms are meant to simplify access and support better use of data. The challenge is choosing and governing the platform landscape in a way that creates consistency, reuse, and long-term value. Three pressure points usually appear. - Platform choice becomes difficult when teams have different needs for speed, flexibility, cost, and control. - Business meaning needs protection: customer, revenue, product, risk, and FTE need shared definitions across tools. - Ownership and governance need to be clear, so platforms grow with accountability and discipline. The working question is simple: how do we give teams the data capabilities they need while keeping the platform landscape understandable, governed, and reusable? If these questions are familiar, let’s compare approaches with others facing the same data landscape.

Belgium 13-11-2026 Squad Only Physical English

Building the Business Case for New IT Capabilities; How to justify investment when value is strategic, shared, or only visible over time.

Many IT capabilities are essential and difficult to fund through a simple project ROI. The challenge is showing why architecture, governance, resilience, cybersecurity maturity, data foundations, and AI readiness deserve investment before the gap becomes expensive. Three pressure points make the case harder. - Shared value means the benefit often sits across several teams, while the budget sits in one place. - Timing creates friction because the cost is immediate while the value appears over time. - Risk translation is needed so business and finance leaders understand the consequence of delaying the investment. The working question is simple: how do we turn foundational IT capabilities into credible investment cases that link cost, risk, business value, and future flexibility? If you are building these cases internally, let’s compare how others are positioning value, risk, and timing.

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Airbnb Optimizes Usage and Costs by Using Savings Plans and Actionable Cost Data on AWS

To help it achieve its goals, Airbnb looked to Amazon Web Services (AWS), its cloud provider, for data and infrastructure solutions. Using support from AWS and multiple AWS services, Airbnb developed strategies to manage capacity, optimize storage and compute capacity, and build a custom cost and usage data tool. The solutions help Airbnb reduce costs, deliver actionable business metrics, and pursue data-informed efficiency projects across its teams.

Opportunity | Architecting Cost Efficiency to Grow Sustainably

Airbnb’s journey to facilitating connection and community through travel began in 2007 when its first two hosts—and founders—welcomed three guests to their San Francisco home. Since then, the company’s hosts have welcomed over one billion total guest arrivals, with listings across more than 220 countries and regions.

From its early days as a company, Airbnb has powered its business using cloud services from AWS—a strategy that supports its rapidly expanding workloads as well as its need for agile compute and storage solutions. The company decided to invest in transforming its data and usage strategy on AWS. Because Airbnb operations involve hundreds of services and an agile technical culture, the company needed a strategic, centralized, and relatively frictionless approach to leaner purchasing.

Early in Airbnb’s journey, the company used a cost allocation visualization engine, AWS Cost Explorer, which has an easy-to-use interface that helps customers visualize, understand, and manage their AWS costs and usage over time. Later, to make use of its internal data infrastructure and extend the cost visualization capabilities of its data warehousing stack, Airbnb took advantage of data from the AWS Cost & Usage Report, which contains a comprehensive set of AWS cost and usage data and is available at an hourly, daily, or monthly level of granularity, as well as at the management or member account level.

"Using Savings Plans has been a significant improvement to Airbnb’s cloud management process. It’s helped reduce our operational workload while also driving meaningful cost savings for our business.”

Ari Siegel
Senior Finance Manager, Airbnb

Solution | Driving Cost Efficiency Using Insights and Pricing Solutions

Relying on its data warehouse, Airbnb uses the AWS Cost & Usage Report to run a custom pipeline that produces a dynamic view of Airbnb’s cost data and facilitates analytics. Airbnb’s pipeline ingests cost and usage files from Amazon Simple Storage Service (Amazon S3), which offers industry-leading scalability, data availability, security, and performance. To process files, Airbnb uses Amazon EMR, a cloud big data environment for processing vast amounts of data using open-source tools, making it possible for developers to run big data applications and petabyte-scale data analytics faster. Airbnb uses its pipeline to discount and amortize the data and then further customize it to support analytics and produce actionable insights and metrics.

To save on its use of Amazon Elastic Compute Cloud (Amazon EC2), which provides secure, resizable compute capacity in the cloud, Airbnb became an early adopter of Savings Plans, a flexible pricing model offering lower prices compared to Amazon EC2 On-Demand Instances in exchange for a specific usage commitment. Airbnb migrated its Amazon EC2 Reserved Instances to Savings Plans and discontinued its On-Demand Instance usage, resulting in cost savings. “Using Savings Plans has been a significant improvement to Airbnb’s cloud management process. It’s helped reduce our operational workload while also driving meaningful cost savings for our business,” says Ari Siegel, senior finance manager at Airbnb.

Airbnb also manages and saves on storage costs using Amazon S3 Intelligent-Tiering (S3 Intelligent-Tiering), a cloud storage class that delivers automatic cost savings by moving objects between four access tiers when access patterns change. By using S3 Intelligent-Tiering to manage storage locations for objects used by Airbnb’s data warehouse, Airbnb reduced storage costs by approximately 27 percent. Additionally, for replicated data stored for backup, the company uses Amazon S3 Glacier storage classes—a range of storage classes that users can choose from based on the data access, resiliency, and cost requirements of their workloads. Airbnb relies on the AWS Cost & Usage Report for hourly insights into data storage spending on Amazon S3.

Airbnb also manages costs within its logging infrastructure using Amazon OpenSearch Service, which makes it easy to perform interactive log analytics, near-real-time application monitoring, website searches, and more. To help lower costs, Airbnb employed UltraWarm storage for Amazon OpenSearch Service, which provides a cost-effective way to store large amounts of read-only data on Amazon OpenSearch Service. The solution contributed to a 60 percent reduction in Airbnb’s Amazon OpenSearch Service costs.

Outcome | Maturing Operations and Empowering Teams

Airbnb’s finance and technology teams employed a broad range of AWS resources to build cloud efficiency and optimize operations. To work toward data-driven purchasing, the teams also expanded their consultation and engagement using AWS. And by delivering process and visibility improvements, the company helped empower individuals and teams to adopt cost management goals.

Technologies

AWS Cost & Usage Report (CUR)

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