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Use Case · Performance & Scalability

Reduce Scalability Bottlenecks

Prevent code patterns that degrade performance, exhaust resources, and become bottlenecks as your systems scale.

Teal foam block with a central hourglass-shaped notch on a pale teal background.
Set the standard >

Define your scalability
patterns once, enforce them org-wide, always.

Set clear rules for how your code handles connections, queries, batching, pagination, concurrency, and other patterns that determine how it behaves under load.

Any synchronous user-facing request operating on a customer-owned collection must keep its workload independent of the collection’s total size. Operations whose cost or latency grows with customer data must use bounded pagination, aggregation, or asynchronous processing instead.

In a dark code editor, a warning banner reads 'Standard violation: request scales with customer data'. The Go code shows a function loading all orders for a specific customer, with a highlighted line 91 featuring an error icon and the note 'Request scales with collection size'. A red box explains why this is a violation, describing the danger of loading all data for a customer-owned collection.
How it works >
Setup: Import your standards from docs, from Pandorian’s library or just type them in plain English
Scope: Decide where, when and how your standards apply across the codebase
Enforce: Run your standards as PR checks on every push, or scan them against your existing code

Enterprise scale coverage.
Enforced everywhere the code goes

Pull Request Checks

Runs on every push so violations of your patterns never reaches main.

Targeted Scans

Scans a repo, service or path on demand when auditing codebase.

Scheduled Scans

Runs a targeted scan automatically on a recurring schedule you define.

Abstract orange 3D bar chart with four ascending blocks suggesting growth on a pale yellow background
Pandorian’s ready-to-enforce guidelines packs >

Scalability bottlenecks
on AWS.

12 Guidelines · Covering connections, queries, batching, concurrency, resources and more.

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Ready to tackle scalability bottlenecks at scale?

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