I designed this co-sell motion to show how Cursor supercharges Datadog's monitoring stack with agentic automation, turning alerts into automated fixes without leaving the IDE.
Cursor helps enterprises maximize ROI from their existing solutions. This motion is repeatable across any Datadog customer.
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Datadog detects an anomaly in production. P99 latency on the checkout endpoint has spiked well beyond the configured threshold.
ALERT: P99 Latency Spike Detected
/api/checkout • P99: 2,340ms (threshold: 500ms) • Triggered 3m ago
Error Rate
4.7%
+380% from baseline
Throughput
1,240 req/s
Within normal range
Affected Users
~2,100
In last 3 minutes
The on-call engineer opens the checkout handler in Cursor with full codebase context. The relevant file is immediately accessible.
1import { validateCart } from './validation';2import { calculatePricing } from './pricing';3import { PaymentGateway } from '@/services/payment';4import { InventoryService } from '@/services/inventory';56export async function handleCheckout(req: Request) {7const cart = await req.json();8const validated = await validateCart(cart);910// BUG: Sequential await causes latency spike under load11const pricing = await calculatePricing(validated);12const inventory = await InventoryService.check(validated.items);13const payment = await PaymentGateway.preauth(pricing);1415if (!inventory.available) {16return Response.json({ error: 'Out of stock' }, { status: 409 });17}1819const result = await PaymentGateway.capture(payment.id);20await InventoryService.reserve(validated.items);2122return Response.json({ orderId: result.orderId });23}
Cursor scans the entire codebase, traces related code paths, and identifies the root cause of the latency spike in seconds.
Scanning codebase
47 files analyzed
Tracing code paths
3 related paths found
Identifying root cause
Sequential await pattern
Generating fix
Promise.all() parallelization
Cursor generates a targeted fix that parallelizes the independent operations while preserving the dependency chain.
Before
-// Sequential: each await blocks the next-const pricing = await calculatePricing(validated);-const inventory = await InventoryService.check(validated.items);-const payment = await PaymentGateway.preauth(pricing);
After
+// Parallel: all independent operations run concurrently+const [pricing, inventory] = await Promise.all([+calculatePricing(validated),+InventoryService.check(validated.items),+]);++// Payment depends on pricing, so it runs after+const payment = await PaymentGateway.preauth(pricing);
The original code awaited three operations sequentially: pricing calculation, inventory check, and payment pre-authorization. However, pricing and inventory are independent of each other, so they can run concurrently using Promise.all(). Payment pre-auth depends on the pricing result, so it must still run after. This change eliminates one full round-trip of latency under load.
4 min
Time to generate fix
~65%
Latency reduction
2.3 hrs
Average manual debug time saved
Datadog surfaces the anomaly the moment it starts. No waiting for user reports or manual log analysis.
Cursor analyzes the full codebase context and generates targeted fixes in minutes, not hours.
Cursor can generate tests for the fix and identify similar patterns elsewhere in the codebase before they cause incidents.
Reduction in Mean Time to Resolution
When detection and intelligent code analysis work together, incident resolution transforms from hours to minutes.