Real-time
Two-way sync
Changes in Datadog or GitHub instantly reflect in both systems. No stale data, no manual imports.
Developer tools ⇄ Business productivity
Datadog to GitHub integration — real-time, two-way sync
Keep Datadog and GitHub 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 GitHub
Connect the tickets, records, and events in GitHub to the systems engineering runs in Datadog, kept current in real time and in both directions.
GitHub 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 Labels and Milestones, Repositories, Issues, Pull Requests in GitHub with Incidents, Service Level Objectives, Hosts, Monitors 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 Mirror repository, PR, and workflow-run data into a Postgres database for engineering-metrics reporting.
- 02 Sync organization and team membership with an identity or HR system to automate access reviews and offboarding.
- 03 Load Events and Incidents into a warehouse to correlate deploys, alerts, and outages on one timeline for post-incident review.
- 04 Pull the Hosts inventory into a CMDB or database for asset tracking, tag hygiene, and cost allocation across teams.
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 GitHub 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 GitHub 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 GitHub
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 | GitHub objects | How this pairing syncs | |
|---|---|---|---|
| Logs Log events searched via the v2 Logs search endpoint by time window and submittable through the log intake API; commonly streamed to a warehouse for retention beyond Datadog's storage period. | Commits Read-only history used to link code activity to tickets and releases. | Logs is specific to Datadog and Commits to GitHub — each maps to any object or custom field on the other side. | |
| Events The event stream (deploys, alerts, comments) searched via the v2 Events endpoint and posted via POST /api/v1/events; used to correlate deploy and incident timelines or to publish deploy and pipeline events into Datadog. | Releases Tagged versions synced into changelogs, CRMs, or customer-notification systems. | Events is specific to Datadog and Releases to GitHub — each maps to any object or custom field on the other side. | |
| 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. | Workflow runs (Actions) CI results synced into incident and reporting systems. | Dashboards is specific to Datadog and Workflow runs (Actions) to GitHub — 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. | Organizations and Teams Membership data synced with identity systems and HR directories for access reviews. | Metrics is specific to Datadog and Organizations and Teams to GitHub — 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. | Users Author and assignee identities matched to internal directories. | Incidents is specific to Datadog and Users to GitHub — 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. | Labels and Milestones Classification fields mapped to statuses and sprints in external trackers. | Service Level Objectives is specific to Datadog and Labels and Milestones to GitHub — each maps to any object or custom field on the other side. |
How changes propagate between Datadog and GitHub
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 GitHub 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 GitHub through its API, with automatic retries and rate-limit backoff.
GitHub Datadog Sub-second propagation
DetectionGitHub notifies Stacksync of record changes through webhook events. Webhooks with a broad event catalog covering issues, pull requests, pushes, and releases.
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.
- GitHub: Authenticated REST requests are limited to 5,000 per hour per user; GitHub Apps scale limits per installation.
What ships with Datadog ⇄ GitHub
Connect Datadog and GitHub for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Datadog–GitHub connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Datadog or GitHub 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 GitHub record.
Observability
Monitoring
Track your Datadog ⇄ GitHub 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 GitHub.
How the Datadog and GitHub 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.
GitHub
- Integration surface
- REST API and GraphQL API
- Authentication
- OAuth 2.0, fine-grained personal access tokens, or GitHub App installation tokens
- Change detection
- Webhooks with a broad event catalog covering issues, pull requests, pushes, and releases; polling for backfill
- Capabilities
- read · write · webhooks
- Rate limits
- Authenticated REST requests are limited to 5,000 per hour per user; GitHub Apps scale limits per installation.
How it works
How to connect Datadog to GitHub — 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.
- 01
Connect your apps
Authenticate Datadog and GitHub with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Datadog
connected
GitHub
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Datadog and GitHub 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.
objects · Datadog ⇄ GitHubCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Datadog GitHubCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Datadog and GitHub integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Datadog and GitHub: authenticate both systems, choose the objects to sync (such as Datadog's Logs and Events), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Yes — Stacksync ships production-grade connectors for both Datadog and GitHub. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
-
Change detection on Datadog: 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. On GitHub: Webhooks with a broad event catalog covering issues, pull requests, pushes, and releases; polling for backfill. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
-
On the GitHub side: Labels and Milestones, Repositories, Issues, Pull Requests, plus custom fields where GitHub exposes them. On the Datadog side: Incidents, Service Level Objectives, Hosts, Monitors. Stacksync auto-detects both schemas and converts types between the two systems.
-
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
-
Common patterns for Datadog and GitHub: One shared record across both systems; Where Datadog tracks engineering work: requests become issues; Where Datadog moves messages between services: activity lands on the stream. 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.
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.
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:
Related integrations
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