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Datadog to Google Sheets integration — real-time, two-way sync

Keep Datadog and Google Sheets in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Datadog and Google Sheets

Connect the tickets, records, and events in Google Sheets to the systems engineering runs in Datadog, kept current in real time and in both directions.

Google Sheets is where customer-facing and operational work happens: the tickets, conversations, contacts, and records a team touches every day. Datadog is where engineering runs the systems behind that work — the issue trackers, message brokers, directories, and monitors that keep services moving. The same items, people, and events matter to both, and when the only link between them is a manual hand-off or an overnight export, each side acts on a stale copy of what the other already knows.

Stacksync syncs Rows, Ranges, Named ranges, Cell values in Google Sheets with Hosts, Monitors, Logs, Events in Datadog field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync maps the overlap, resolves conflicts by rules you set, and keeps every copy current, with no middleware to build and no API limits to babysit.

Common use cases

  • 01 Reconcile finance or billing exports against system-of-record data in one collaborative surface.
  • 02 Prototype an integration by syncing a sheet before committing to a database schema.
  • 03 Pull the Hosts inventory into a CMDB or database for asset tracking, tag hygiene, and cost allocation across teams.
  • 04 Sync Monitors and their alert state into Postgres so reliability teams query alert history and noisy-monitor trends in SQL.

Common sync patterns

One shared record across both systems

Where both systems keep records for the same contacts, items, or users, a correction in either updates the other, ending dual maintenance and keeping IDs aligned for every other flow.

Where Datadog tracks engineering work: requests become issues

A ticket or request raised in Google Sheets opens or updates a matching issue in Datadog, and status, comments, and resolution flow back, so support and engineering work the same item instead of retyping it.

Where Datadog moves messages between services: activity lands on the stream

Records created or changed in Google Sheets publish to the queue or topic in Datadog as they happen, so downstream services react to real events rather than polling for them.

What you can sync between Datadog and Google Sheets

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Datadog objects Google Sheets objects How this pairing syncs
Dashboards Dashboard definitions and widgets via the v1 Dashboards API with full CRUD; exported for backup and audit, or created and updated programmatically from a source of truth. Cell values Untyped by default, so syncs handle type coercion for dates and numbers. Dashboards is specific to Datadog and Cell values to Google Sheets — each maps to any object or custom field on the other side.
Metrics Time-series metrics queried in aggregate windows through the query API and submitted via POST /api/v1/series; individual raw points cannot be extracted beyond retention. Spreadsheets The file-level container a sync connects to, identified by spreadsheet ID. Metrics is specific to Datadog and Spreadsheets to Google Sheets — each maps to any object or custom field on the other side.
Incidents Incident records from the v2 Incidents API with full CRUD, including status and timeline fields; landed in a database for MTTR reporting or created and updated from an external incident workflow. Sheets (tabs) Individual worksheets, typically mapped one-to-one to a synced table. Incidents is specific to Datadog and Sheets (tabs) to Google Sheets — each maps to any object or custom field on the other side.
Service Level Objectives SLO definitions and status history via the v1 SLO API with full CRUD; read out for reliability and error-budget reporting, or provisioned and updated from a reliability config. Rows Treated as records; a header row usually defines field names. Service Level Objectives is specific to Datadog and Rows to Google Sheets — each maps to any object or custom field on the other side.
Hosts Infrastructure host inventory with tags and metadata from the v1 host list API; loaded into a CMDB or warehouse for asset tracking, and hosts can be muted or unmuted via the API. Ranges Addressed in A1 notation for batched reads and writes. Hosts is specific to Datadog and Ranges to Google Sheets — each maps to any object or custom field on the other side.
Monitors Alert definitions with query, thresholds, and current state via the v1 Monitors API, which supports full create, update, and delete; Stacksync reads alert state into a warehouse or provisions and updates monitors from a config source. Named ranges Stable references that keep sync mappings valid when the grid moves. Monitors is specific to Datadog and Named ranges to Google Sheets — each maps to any object or custom field on the other side.

How changes propagate between Datadog and Google Sheets

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Datadog Google Sheets Sub-second propagation

DetectionDatadog notifies Stacksync of record changes through webhook events. Polling with time-windowed search queries on Logs and Events (timestamp cursor).

DeliveryEach detected change is written to Google Sheets through its API, with automatic retries and rate-limit backoff.

Google Sheets Datadog Interval-based propagation

DetectionStacksync polls Google Sheets for changes on an incremental schedule, reading only records changed since the previous pass. Polling.

DeliveryEach detected change is written to Datadog through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Datadog: Per-endpoint limits return HTTP 429 with X-RateLimit-Limit/-Remaining/-Period/-Reset headers. Log ingestion and metric submission are not rate limited; search endpoints such as Logs and Events queries carry quotas that Datadog Support can raise.
  • Google Sheets: Subject to per-minute read and write quotas per project and per user, so large syncs are batched.
What ships with Datadog ⇄ Google Sheets

Connect Datadog and Google Sheets for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Datadog–Google Sheets connection.

Real-time

Two-way sync

Changes in Datadog or Google Sheets instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Datadog or Google Sheets data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Datadog or Google Sheets record.

Observability

Monitoring

Track your Datadog ⇄ Google Sheets sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Datadog and Google Sheets.

How the Datadog and Google Sheets connectors work

Datadog

Integration surface
REST API (v1 and v2)
Authentication
API key (DD-API-KEY) plus an Application key (DD-APPLICATION-KEY) sent as request headers; application keys are tied to the creating user and inherit that user's permissions and authorization scopes.
Change detection
Polling with time-windowed search queries on Logs and Events (timestamp cursor); monitor alerts can also push via the Webhooks notification integration. No modified-date CDC on mutable objects.
Capabilities
read · write · webhooks
Rate limits
Per-endpoint limits return HTTP 429 with X-RateLimit-Limit/-Remaining/-Period/-Reset headers. Log ingestion and metric submission are not rate limited; search endpoints such as Logs and Events queries carry quotas that Datadog Support can raise.

Google Sheets

Integration surface
REST API (Google Sheets API), with file-level change signals available through the Drive API
Authentication
OAuth 2.0 (user consent) or Google service accounts
Change detection
Polling; the Sheets API has no cell-level webhooks, and Drive push notifications only signal file-level changes
Capabilities
read · write
Rate limits
Subject to per-minute read and write quotas per project and per user, so large syncs are batched.
How it works

How to connect Datadog to Google Sheets — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Datadog and Google Sheets with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Datadog connected
    Google Sheets connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Datadog and Google Sheets objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Datadog ⇄ Google Sheets
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Datadog Google Sheets
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Datadog and Google Sheets integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

Learn more about security
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 392 integrations available for Datadog and Google Sheets.

Popular · 8 of 392
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