ORY – Open-Source Identity and Access Management Explained

Enable password-free authentication now to reduce credential risk and streamline access across apps.

ORY is a modular, open-source platform for managing users, sessions, and permissions. It brings together components like a identity service, a token server, and a policy gate to control access to resources. Connect ORY to your existing directories, databases, and APIs, then rely on standard flows to authenticate, obtain consent, and authorize requests. The stack scales from a single-app setup to multi-service ecosystems without vendor constraints.

Start small and grow. Deploy the identity component, the token engine, and the policy gateway as a triad. Use a test client to verify sign-in and token issuance, then extend to multiple apps and diverse clients. The OAuth2/OIDC-compatible flows integrate with your login pages and external providers, giving you centralized control over sign-ins, consent prompts, and session lifetimes across services.

To operate safely at scale, separate concerns with clear layers and adopt a policy-first approach. Configure the identity layer to persist user data, enable structured claims in tokens, and define access rules in the gateway. The platform supports modular adapters, observability through logs and metrics, and straightforward upgrades that preserve compatibility across versions.

If you want to tailor the stack, consult the official docs and community examples. ORY provides ready-to-run containers and a robust API-first design, so you can adapt the solution to your architecture while keeping code quality and security at the forefront.

ORY Core Components: Kratos, Hydra, and Oathkeeper in Practice

Choose Kratos first to establish identity and password management for self-hosted deployments; it built to run without external dependencies and scales to enterprise-grade requirements. This open-source core handles sign-up, login, password recovery, and multi-factor flows that you can customize with jsonnet to fit your environment.

Layer Hydra to issue and validate tokens via OAuth2 and OpenID Connect. Hydra supports clients, consent flows, and token strategies; it can be deployed in a managed or self-hosted environment and integrates with Kratos as the identity provider. The end-to-end flow: user authenticates with Kratos, Hydra issues tokens, and Oathkeeper enforces policies. This approach supports strong authorization patterns and token lifecycles, delivering an enterprise-grade security posture for your services.

Oathkeeper acts as a reverse proxy and policy engine; it uses rules to allow or deny requests, attaches claims from Kratos/Hydra, and can route to services without exposing internal endpoints. It can be self-hosted or used as part of a managed environment; you can прикрутить it to your existing API gateway, and it also provides JSON-based rule definitions. For faster iteration, use jsonnet to compose Oathkeeper rules across environments; supports environment-specific overlays, so your policies stay aligned as you scale.

The github repository for the orys stack consolidates кода, samples, and docs, helping your team move from proof-of-concept to production-ready setups without reinventing the wheel. Your developers can reuse built templates, plug in your password policies, and extend middleware with functional adapters that fit your stack. This ecosystem keeps things cohesive, so your end-to-end flow remains auditable and reproducible.

Deployment patterns emphasize separation of concerns: Kratos handles identity data and user journeys, Hydra manages tokens and consent, and Oathkeeper enforces access control at the gateway. This division enables you to scale horizontally, run a managed cloud variant, or stay self-hosted without vendor lock-in. By design, each component supports enterprise-grade requirements such as strong auditing, deterministic revocation, and pluggable password policies that you can tune per team or service.

Practical steps to get started: spin Kratos in a dedicated environment, connect Hydra as the OAuth2/OIDC provider, and configure Oathkeeper with rules that reference Kratos claims. Use jsonnet to maintain environment-specific configurations, validate with end-to-end tests, and store sensitive data in a hardened secret store. If you need guidance, explore the orys approach on GitHub and adapt templates to your own stack; this helps you прикрутить a secure identity layer quickly while keeping compliance overhead manageable.

For ongoing operations, monitor token lifecycles, implement rotation policies, and enable logging across all components. Build a lightweight local environment first, then migrate to a production-ready setup with a clear rollback plan. The combination is built to be open-source, без зависимости от сторонних services, and able to transition into a managed deployment if you need faster time-to-market or centralized governance. Your team gains a unified, end-to-end solution that remains customizable, documented, and ready for enterprise-grade demands.

Self-Service Identity Flows in ORY Kratos: Sign-up, Login, and Recovery

Recommendation: enable three separate self-service identity flows – sign-up, login, and recovery – as отдельный parts of your auth stack. This provides clean создание of identities, reduces вопросы from users, and keeps data consistent across apps. Define a clear момент for each flow and write сценариями that map real user interactions to UI prompts. Use settings to tune email verification, MFA options, rate limits, and UI copy. The ORY Kratos self-service engine provides a solid base, and when paired with Hydra it can issue OAuth2 tokens after successful login. learn from live usage to refine prompts and flows, and rely on предусмотрена protections against abuse. For multilingual teams, expose English and Russian prompts and offer UI text that adapts to locale.

Design and configuration

Sign-up flow: collect essential traits such as email, password, and optional name; enforce a strong password policy and require email verification. Include optional methods like WebAuthn or OTP. Login flow: support session cookies or tokens from Hydra; provide a fallback password login and implement rate limiting to prevent brute-force attempts. Recovery flow: present a secure, link-based reset and, if needed, a set of questions to verify identity. Use основых controls to ensure only legitimate users gain access, and provide separate body blocks for each step to keep flows modular. Build tools to test each path and introduce monaten prompts to guide users without friction. The telo of each flow should be clean, with clear error messages and actionable next steps.

Operations and monitoring

OAuth2 and OpenID Connect Configuration with ORY Hydra

Recommendation: Run ORY Hydra in a managed, secure environment and implement the authorization_code flow with PKCE for every public application. Enable OpenID Connect, wire the login and consent flows to your passwordless authenticator, and enforce TLS. This approach builds trust attraverso il network and supports a mondo di subscribers. It supports functional интеграции (интеграции) and ensures информации exchange across система e application boundaries.

Register each application as a Hydra client. For public apps, set public true and token_endpoint_auth_method to none, define redirect_uris, and limit grant_types to authorization_code and refresh_token. Require scopes openid, profile, email, and, if you need it, offline_access for refresh tokens. Use the admin API to read and manage clients, and rotate keys to sustain trust attraverso il network.

Configure the ID token to include атрибуты such as sub, name, and email; use the userinfo endpoint to supply additional атрибуты. Map identity source attributes to OpenID Connect claims so each subscriber sees a consistent audit trail nel system. This enables precise attributes handling and improves interoperability across mondo of services and read-oriented APIs.

Security and deployment: run Hydra with a durable PostgreSQL database in a managed environment, enable TLS, and sign tokens with RS256 using a JWKS. Rotate keys regularly and set access_token TTLs to a short window (for example 15 minutes) while using longer refresh_token lifetimes with rotation. Enable revocation and token introspection for resource servers to verify tokens, maintaining trust attraverso network boundaries. This need aligns with best practices for scalable systems and ensures admin visibility into token lifecycles.

Scenarios (сценариями): 1) A passwordless login flow where the user authenticates via a magic link or WebAuthn, then Hydra issues tokens after consent. 2) A backend application uses client_credentials to access an API, with the API performing read of token claims via introspection. 3) A device or service running in a network exchanges tokens for API access. Each path relies on PKCE, strict redirect URIs, and minimal personal data in the system to protect информации. These flows demonstrate how you can реализовать secure, user-friendly access across mondo of users and devices.

Operational notes: automate client provisioning via the admin API, keep a narrow set of атрибуты in the ID token, and rely on the userinfo endpoint for additional data as needed. Maintain clear logging for auditing, and document how это setup supports пользователем access control, policy decisions (if you pair Hydra with a policy engine), and ongoing integrations with partner systems (интеграции). This approach helps you meet security, compliance, and user experience goals in a multi-tenant environment.

Defining and Enforcing Access Policies with ORY Oathkeeper

Apply a default-deny posture and codify your rules in a version-controlled ORY Oathkeeper setup; connect to your identity provider with OIDC for clean sign-ins; enforce policies at the edge for every request using open-source tooling.

Define a resource-centric policy model: each rule targets a resource path or pattern, a HTTP method, and a subject match against token claims. Use authenticators such as JWT or OAuth2 introspection, then pair with a precise authorizer (for example, role-based or scope-based) to decide access. Attach mutators to forward user context to upstream services without leaking internal claims, preserving user privacy while enabling downstream apps to tailor responses.

Illustrative patterns help teams move fast: for admin access to a headless content platform, create a rule that matches /admin/** and requires subject.claims.role equals “admin” plus a valid token. For a newsletter service, restrict write operations to authenticated organization staff and allow read access to all users. For account endpoints, enforce that the user_id in the request matches the subject, preventing cross-user access to personal data.

Sessions and token freshness matter: validate tokens on every request, enforce short-lived access tokens, and refresh gracefully with appropriate mutators that set or remove headers for downstream services. Monitor timeouts and expiry to maintain a smooth user experience, while keeping access decisions auditable and reproducible.

Deployment guidance keeps policies reliable: store rules in a dedicated repo, apply a policy-as-code workflow, and run automated tests that simulate real user data from multiple organizations and headless apps. Use CI to lint configurations and ensure that newsletter, message, and account endpoints behave as intended under varied roles and token states.

Admin governance scales with your organization: predefine organizational boundaries, assign admins to manage policies per group, and require reviews before promoting changes. Distinct teams can own separate rule sets for users in different organizations while relying on a single, coherent access-control plane built on open-source components.

Operational hygiene closes gaps: implement centralized logging of policy decisions, integrate alerts for repeated denials, and maintain an audit trail that traces who changed which rule and why. This approach helps you verify that data access complies with organizational policies and regulatory requirements, including how user data is accessed and protected across diverse frontends and services, such as messaging or content delivery.

Saved Searches for ORY Audit Logs: Creating, Saving, and Reusing Queries

Create a saved search for ORY Audit Logs that targets verification events and device context, using a base_url for the log API and a clearly defined time window. This single query becomes the foundation for end-to-end tests, automated checks, and regular обзор of authentication flows.

1. Define scope and inputs. Pin the search to a base_url like https://logs.example.com/api/v1/audit and include fields such as timestamp (время), event_type, action, resource, actor_id, and device. Use an api-first mindset to describe the query contract, so it can be reused by other teams and integrated into jsonnet configurations. Include verification-related fields to capture подтвердждения on access decisions.

2. Build the query logic. Filter by event_type = “audit” and by verification = true, then join logs from kratos events with device metadata. Add a time range filter (например last 24h) to support регулярный checks. Add keyword search (search) for terms like “login” or “session_create” to tighten the results. Keep the query extensible so you can layer additional filters without breaking existing dashboards.

   • Include fields: время, device, actor_id, action, resource, result, and verification.
   • Support end-to-end tests (end-to-end tests) by exporting the query in a compact form that can be fed to test runners.

3. Save and name the query. Use a clear, consistent naming scheme (e.g., Audit-Verifications-kratos-device). Add a short description in the раздел to explain the purpose, scope, and data sources. Store the definition alongside other разделы observability assets so the team can发现 a common baseline quickly.

4. Automate creation with jsonnet. Represent the saved search as a jsonnet file that defines base_url, the filter blocks, and a human-readable name. Include options for разных environments (cloud-native deployments, staging, production) to support scaling on multiple servers. This approach helps реализовать IaC patterns and keeps configurations versioned in source control.

5. Reuse across dashboards and alerts. Link the saved search to dashboards for Kratos workflows, to alerting rules for suspicious activity, and to newsletters (newsletter) for security announcements about new verification patterns. Use a join strategy to connect audit logs with user provisioning events to provide full context.

6. Practical use-cases and examples. Monitor verification failures during sign-in flows and link them to specific users and devices. Add a second layer to catch failed attempts coming from specific endpoints (base_url) and from particular clients (e.g., mobile vs desktop). Track the time-to-verification metric (время до подтверждения) to spot latency spikes.

7. Performance and scaling notes. For cloud-native systems, keep queries lightweight and cache results when possible. Plan for scaling by distributing load across multiple servers and keeping the saved search definition stateless. Periodically prune outdated time windows and archive long-term data to keep response times predictable.

8. Maintenance and governance. Create a short обзор of saved searches in a dedicated хранение (store) section. Regularly review mappings for fields like device and verification to align with evolving Kratos schemas. Ensure access controls prevent exposure of sensitive data in saved search results.

9. Implementation tips. Start with a minimal saved search that covers verification events by device, then incrementally add fields (resource, actor_id) and filters (time, outcome). Document changes in the раздел and update jsonnet definitions to reflect updates. This discipline helps teams collaborate and scale across environments.

10. Quick-start checklist. Create a base saved search, enable a lightweight dashboard, test with a handful of real events, and verify that the results include подтвердждения for key actions. After validation, share the approach in the next newsletter entry to align teams on the api-first strategy and ensure consistency across the system.

By adopting a structured approach to Saved Searches for ORY Audit Logs, you gain repeatability, visibility across orkestrated services, and a clear path for verification in kratos-driven flows. The combination of jsonnet-driven definitions, cloud-native scaling, and end-to-end test coverage helps teams move from creation to reuse with confidence, while keeping документацию and разделы aligned and easy to navigate.

Observability: Capturing Logs and Metrics for ORY Deployments

Configure a unified observability stack: Prometheus metrics, Loki logs, and Tempo traces across hydra, kratos, and oathkeeper to ship data to a central backend. In their world, this yields full visibility into passwordless flows, oidc interactions, and multi-tenancy deployments. Use install scripts or a docker-compose setup and include dockertest in your CI to validate that logs, metrics, and traces are collected during a minimal scenario. примеру: trigger a frontend login flow and verify correlation across services. Собирать structured logs with a consistent schema helps you filter by tenant and operation, keeping буду notes for future debugging.

Adopt a practical log strategy: emit JSON lines from each ORY component, include fields like timestamp, level, service_name, tenant_id, request_id, trace_id, and message. Add дополнительныe context for errors and upstream status, but redact secrets and tokens. For example, capture the frontend path, user_id, and oidc state to enable cross-service tracing, while keeping the data lightweight enough to avoid bloating the log stream. Include пример and примеру entries to illustrate typical events during a login or token exchange, and reference почитать guides when extending the schema.

Instrument metrics and traces to complement logs: expose /metrics on Hydra, Kratos, and Oathkeeper, and feed them into Prometheus. Use Grafana dashboards to monitor latency, error rates, and token issuance counts, especially for passwordless workflows and multi-tenancy boundaries. Track frontend round-trips, message flow between services, and downstream dependencies; monaten configurations help you align sampling and retention across teams. The next sections outline a concrete table of fields and the following scenario to validate the setup in a real environment, such as a dockertest-based install after adding new components to the applications stack.

Following сценарий provides a practical validation path: the next steps include deploying Hydra with passwordless and oidc flows, enabling observability endpoints, and running a small test suite with dockertest. After добавили the monitoring sidecar, почитать guides on how to tune retention, and adjust alerts for the key indicators, вы сможете собрать a reliable picture of their applications health during every login attempt. The goal is to have a fully observable stack that correlates frontend messages with backend responses and token issuance events, enabling teams to respond quickly to incidents and to improve the overall user experience.

Recommended Observability Checklist

Install a centralized backend (Prometheus + Loki + Tempo) and expose metrics and logs from hydra, passwordless flows, and oidc endpoints.

Annotate deployments to include tenant_id, application_id, and environment labels for multi-tenancy visibility.

Enable structured logging in JSON with a consistent schema and avoid piping sensitive data; keep message fields concise but informative.

Scenarios and Next Steps

Use dockertest to simulate a complete login scenario, then collect the following for the next iterations: refine log schemas, extend metrics coverage, and validate cross-service traces.

Production Readiness: HA, Scaling, Secrets, and Key Management

Enable multi-node hydra behind a robust load balancer and connect to a replicated Postgres cluster with automatic failover. This setup delivers HA, predictable recovery, and smooth identity and access flows after outages. Use a separate (отдельный) secrets store and a centralized key management workflow; the rotation policy is предусмотрена to keep signing keys secure. The following practices are verified in production: health probes, rolling upgrades, and automated recovery playbooks. примечание: align the configuration with бизнес-логики access controls and policies, and ensure support for phone-based MFA and multi-language prompts (including mandarin) in your identity flows. After an incident, the system should continue to serve tokens with the same level of trust, keeping downtime low and latency stable. developer-friendly tooling and clear runbooks help others adopt the setup quickly, while keeping drinks breaks brief during long drills. пример scenarios will be useful for validating real-world use.

Secrets and Key Management

Store signing keys in a secure vault (such as Vault, AWS KMS, or GCP KMS) and expose a JWKS endpoint for token verification. Implement automatic rotation with a safe overlap window so Hydra can validate tokens issued with both old and new keys. A dedicated rotation cadence (например, rotate every 90 days) reduces risk and keeps revocation timely. The management workflow should задать clear ownership, audit access, and enforce least privilege; кокон of keys and secrets must be отделён from application code. The following actions are примеры of best practices: verify key material integrity on every rotation, reuse previous keys for a brief recovery window, and publish rotation events to your support channels (others) for observability. фокусируйтесь на identity trust, retention policies, and cross-region consistency, чтобы сценариями охватить локализацию, in particular mandarin locales, and phone-based MFA prompts. примечание: maintain automated alerts for unusual key usage and provide a verification path for token validation failures. реализовать automated tests that simulate key rollover and token renewal, and задать thresholds for rotation latency to avoid downtime.

Automation, Scaling, and Recovery

Operate Hydra as stateless services behind a scalable load balancer; scale horizontally by adding instances and sharing a single, strongly replicated database. Use feature flags and API gateways to manage business logic (access rules) without redeploying services. Implement automated backups, point-in-time recovery, and regular disaster-recovery drills; after drills, update runbooks and recovery playbooks accordingly. Ensure a developer-friendly workflow by providing clear CLI tips, API documentation, and example scripts to reproduce scenarios (пример) for local testing. Recovery workflows should be tested with a variety of сценариями (сценариями) to validate edge cases like token revocation, key rollover, and region failover. track monitoring metrics such as request latency, error rates, and token validation times to detect regressions early, and keep support teams aligned with incident playbooks. Примечание: document ownership for each component, assign ownership for access control decisions, and keep a live runbook that covers both on-call actions and post-incident reviews. after incidents, review root causes and adjust thresholds, automation, and alerting to reduce future MTTR and improve overall resilience.