Once embedded analytics is live, usage can grow quickly. Teams love access to data, and what starts as a handful of queries can turn into thousands per hour as adoption spreads. To keep performance high and costs under control, you need a plan for scaling. Without one, you may see slow load times or surprise cloud bills. Here are the key considerations for engineers and operations teams.
Performance best practices
Pre‑aggregate and cache – create materialized views and cache common queries to avoid repeatedly scanning large tables. Pre‑ aggregated tables speed up heavy calculations, while a query cache serves repeat requests instantly. Our article on managing performance and caching offers practical tips.
Control concurrency – limit the number of simultaneous queries to prevent spikes from degrading performance. Tune concurrency slots and allocate extra compute when needed. Some platforms allow setting concurrency quotas per tenant so one customer doesn’t impact another.
Monitor and optimize – track CPU, memory and query latency. Identify heavy users and optimize their dashboards. Use observability tools to flag slow queries and schedule maintenance windows for heavy ETL jobs.
Scaling your infrastructure
Right‑size your cluster – run load tests and size compute based on expected query volume, data size and concurrency. Consider both peak and average workloads. Read our infrastructure sizing guide for details.
Use autoscaling – choose serverless or elastic options where compute automatically expands or contracts to match demand. This way you don’t pay for idle resources, yet you can handle spikes gracefully. Autoscaling is particularly useful when usage patterns fluctuate throughout the day.
Plan for cost efficiency – monitor warehouse credits and storage costs. Storage can grow quickly with pre‑aggregated tables, so archive old data or use tiered storage. Our cost efficiency primer discusses usage‑based billing models and how to budget effectively.
With the right architecture and tuning, you can deliver sub‑second responses even at scale while keeping cloud bills predictable. Start by measuring your current query patterns, then tune caches, concurrency and compute sizes incrementally. For more guidance, explore our resources on performance and caching and scaling infrastructure.
Maintaining user experience
Scaling isn’t just about cost. It’s also about preserving a great user experience as your audience grows. Slow dashboards erode trust and reduce adoption. Communicate with product teams about expected latencies and plan ahead for big feature launches or marketing campaigns that could drive traffic spikes.
