Omkar Kesarkhane
1ec3b5d0dc
## Problem
Saving a browser check with an invalid step showed only the toast **"Fix
the highlighted fields before saving"** — no step expanded, no field
highlighted. Two separate faults produced that symptom.
### 1. In create mode, nothing reached the journey at all
`OStepper` runs in **wizard mode** here (no `expanded` prop, default
`false`), so `OStep` renders its panel behind `v-if="isActive"` —
**`BrowserJourney` exists only while `currentStep === 1`**. Create
mode's only Save button lives in the `currentStep === 2` footer, so
`journeyRef.value` was `undefined` when `persist()` ran:
```ts
currentStep.value = 1; // not flushed yet
journeyRef.value?.validateStepSelectors?.(); // no-op
journeyRef.value?.setStepFieldErrors?.(result.error.issues); // no-op
toast({ variant: "error", … }); // the only survivor
```
A `nextTick` would not have been enough: a **freshly mounted**
`BrowserJourney` starts with an empty error map, so an imperative push
cannot survive the remount. Edit mode worked because it has a Save on
the Journey step — which is why this read as create-mode-only.
### 2. Even when they arrived, only 2 of 7 rules expanded anything
Auto-expand lives in `validateJourneySteps()`, which knows two rules.
The other five — `stepNameRequired`, `retiredAction`, the navigate URL,
`typeTextRequired`, `expectedRequired` — live in the zod schema and
reached the journey through `setStepFieldErrors()`, which recorded the
message and returned. `getRowStatusColor()` ignored them too, so
"highlighted" was literally false for those rules.
## Fix
- **Issues are parent-owned state passed as the `fieldIssues` prop**,
applied by an `immediate` watcher. Mount order stops mattering — issues
raised while the journey is unmounted wait, and rows open whenever it
next renders (including the Details-error + journey-error case, where
the author lands on Configure and finds the journey already expanded on
switching tabs).
- **Both paths route through `revealErroredSteps()`** — opens every
errored row in journey order, clears an active filter (a filtered-out
row isn't rendered, so expanding it shows nothing), scrolls to the
first. `getRowStatusColor()` reads schema errors too.
- **Stale errors clear as the author edits.** The editor emits no
per-field event for name/value/expected, so those stayed red over
corrected input and kept re-opening a correct row.
- **Stale errors clear on a successful save** — `setStepFieldErrors` was
only ever called on the failure branch.
- **Duplicate error toast gone.** `persist()` no longer calls Path A at
all; the schema already emits both of its rules as field issues.
Removed as dead: `setStepFieldErrors` from `defineExpose`, and the
`silent` option added mid-fix for the duplicate toast.
## Tests
846 passing. Validation had large untested surfaces — which is how
coverage decayed without a single failure. Closed here:
- monitor-level `name`/`url`/`locations` and the **entire gate schema**,
neither ever exercised (`form()` supplies valid values; the view spec
replaces the schema module with a stub)
- `validateJourneySteps`' auto-expand — **untested since the first
commit**
- the `expectedErrorMessage` binding, `.trim()` on type text and
expected, the `\S+$` part of the navigate regex, `element_not_visible` /
`page_title` / `element_attribute`, and the `scroll`/`screenshot`
retired actions
The view spec's `OStep` stub was `v-if="$parent.$parent || true"` — it
rendered **every** panel, keeping `journeyRef` alive on the Configure
step, which is why this spec could not have caught fault 1. It now
mirrors wizard mode, and a create-mode save with a journey error is
asserted end to end.
**Every rule verified by mutation** — disabled at source, suite re-run,
reverted. **33 mutations, all caught.** Three initially ran green and
led to stronger tests: `min(1)` on `url` only governs *which message*
appears (the protocol refine rejects `""` anyway), nothing reached
`\S+$`, and `validateJourneySteps`' expand had no test at all.
## Not fixed — filed for follow-up
Found in the same sweep, deliberately out of scope:
- **`select` / `press` / `upload` accept a blank value.** `v2Value()`
maps all of them to the wire, so they save, run, and **pass** — the
false-green `typeTextRequired` exists to prevent. `type` isn't special;
it just got a rule.
- **A zero-step journey saves.** No `.min(1)`, and the first-step check
treats an empty array as valid.
- **`element_attribute` has no attribute rule**, and no error binding
for that field.
- **`timeout` / `settle.budget_ms` warn but never block.** Needs
`Advanced` to become controlled first, or the rules land inside a
collapsed section and reproduce this same bug one level deeper.
- **Continue and Replay use the 2-rule gate**, not the schema — so a
journey with a blank type text replays and false-greens.
- **A whitespace-only monitor name is accepted** (`.min(1).trim()` vs
the step rule's `.trim().min(1)`), so a check named three spaces saves
and displays blank.
Full write-up with the regression timeline, the mutation table, and why
each layer's tests stayed green is in
`docs/synthetics/002-journey-step-validation-audit.md` (untracked —
`docs/` is gitignored in this repo).
## Verification
- `npx vitest run src/components/synthetics src/views/synthetics` → 43
files, **846 passed**
- `npm run type-check` → clean
- `npx eslint` on changed files → 0 errors (4 pre-existing warnings,
none introduced)
- `npx prettier --check` → clean
Open source Datadog alternative for logs, metrics, traces, and frontend monitoring. Modern observability platform: 10x easier, 140x lower storage cost, high performance, petabyte scale.
Cloud · Documentation · Slack · Quickstart
OpenObserve (O2) is a cloud-native observability platform for logs, metrics, traces, analytics, Real User Monitoring (RUM), and AI/LLM observability. It's a cost-effective alternative to Datadog, Splunk, and Elasticsearch for teams that need full observability without the complexity or cost — with Parquet columnar storage and an S3-native design that cuts storage costs by up to 140x.
Table of Contents
- Why OpenObserve?
- Quick Start
- Product Tour
- Architecture
- Comparisons
- Production Ready
- Security & Compliance
- Enterprise Edition
- Community & Support
- Contributing
- FAQ
- License
- SBOM
Why OpenObserve?
A single platform for all of your observability signals. Here's why teams choose OpenObserve:
| Benefit | Description |
|---|---|
| 140x lower storage cost | Parquet columnar storage + S3-native architecture dramatically reduce costs vs Elasticsearch |
| Single binary deployment | Up and running in under 2 minutes — no complex cluster setup required |
| OpenTelemetry native | Built on the OpenTelemetry standard — no vendor lock-in |
| Unified platform | Logs, metrics, traces, RUM, dashboards, alerts, and incidents in one tool |
| High performance | Better query performance than Elasticsearch on a quarter of the hardware |
| SQL + PromQL | Query logs and traces with SQL, metrics with SQL or PromQL — no proprietary query language |
| Built in Rust | Memory-safe, high-performance, single binary |
Cost comparison: OpenObserve vs Elasticsearch
Quick Start
OpenObserve Cloud (fastest way)
Get started in minutes without managing infrastructure. The free tier includes up to 50 GB/day of ingestion.
🐳 Docker
docker run -d \
--name openobserve \
-v $PWD/data:/data \
-p 5080:5080 \
-e ZO_ROOT_USER_EMAIL="root@example.com" \
-e ZO_ROOT_USER_PASSWORD="Complexpass#123" \
public.ecr.aws/zinclabs/openobserve:latest
Then open http://localhost:5080 and log in with the credentials above.
For other installation methods, see the quickstart documentation. For clustered deployments, see the High Availability deployment guide.
Product Tour
OpenObserve ships with a powerful, unified web UI for every signal — logs, traces, metrics, dashboards, RUM, alerts, incidents, pipelines, and AI observability.
🏠 Unified Overview
A single home for your workspace — active incidents, service health (error rate, latency, requests), anomalies, and recent events at a glance.
📊 Logs
Centralized log management with full-text search, SQL queries, quick filters, and a visual query builder. Instantly search across all your logs, build dashboards from log data, and set up alerts — all on Parquet columnar storage for 140x lower storage cost than Elasticsearch. Read more →
🔍 Distributed Tracing
Powered by OpenTelemetry, tracing helps you follow requests across services and pinpoint performance bottlenecks. Explore the full request flow with waterfalls, flame graphs, and Gantt charts; click any span to drill into the trace. Read more →
🕸️ Service Graph
Visualize service-to-service dependencies and request flow across your system, with per-edge request counts and health-based coloring (healthy, degraded, warning, critical) to spot problem hotspots at a glance.
📈 Metrics
Explore metrics from your infrastructure and applications, then query them with SQL or PromQL. Browse thousands of metrics with faceted filters, preview them inline, combine multiple queries with formulae, and visualize the results with 19+ chart types. Read more →
📉 Dashboards
Build custom dashboards from any signal with 19+ built-in chart types and 200+ visualization variations, a drag-and-drop panel builder, template variables, and geo maps. Read more →
👀 Frontend Monitoring (RUM)
Real User Monitoring with Core Web Vitals, error tracking, performance analytics, and full session replay — so you can see exactly what your users experience. Read more →
🔔 Alerts
Get notified when something unusual happens on any signal — logs, metrics, or traces. Define thresholds, scheduled or real-time alerts, and notification channels, with alert history and anomaly detection to catch issues early. Read more →
🚨 Incidents
Correlate related alerts into incidents and track them through their lifecycle — open, acknowledged, and resolved — with severity and dimension context for faster response.
🔀 Pipelines
Enrich, redact, reduce, or normalize data at ingest time with a visual editor. Build stream-processing flows — including logs-to-metrics conversion — from source, transform (VRL functions and conditions), and destination nodes. No external tools required. Read more →
🤖 AI Observability
Monitor your GenAI and LLM applications: track cost, tokens, latency percentiles, and error rates across models, with agent graphs, session traces, and evaluation/quality scoring.
✨ O2 AI Assistant
An in-product assistant that writes your SQL, VRL, and PromQL and walks you through logs, traces, metrics, and incidents — turning natural-language questions into queries, dashboards, and alerts.
For the full feature list, see the documentation.
Architecture
OpenObserve achieves 140x lower storage costs and high performance through a modern, cloud-native architecture:
- Parquet columnar storage — efficient compression and fast analytical queries
- S3-native design — inexpensive object storage with intelligent caching
- Built in Rust — memory-safe, high-performance, single binary
- Partitioning, indexing, and smart caching — reduces search space by up to 99% for most queries
- Native multi-tenancy — organizations and streams as first-class concepts with complete data isolation
- Stateless architecture — rapid scaling and low RPO/RTO for disaster recovery
Scale & Deployment
- Thousands of concurrent users can query a single cluster simultaneously
- Single binary scales to terabytes — unique in the observability space
- High Availability mode scales to petabytes for the most demanding workloads
- Multi-region deployments with cluster federation via Super Cluster architecture (Enterprise)
- Federated search across regions and clusters (Enterprise)
High Availability & Disaster Recovery
Deploy in High Availability mode with clustering for mission-critical workloads requiring maximum uptime. OpenObserve's stateless architecture with S3-backed storage enables very low Recovery Point Objective (RPO) and Recovery Time Objective (RTO): stateless nodes restart rapidly, and durability is guaranteed by S3's 99.999999999% (11 nines).
Read the architecture documentation → · Read the enterprise deployment guide →
Comparisons
OpenObserve vs Datadog
| Aspect | OpenObserve | Datadog |
|---|---|---|
| Deployment | Self-hosted or Cloud | SaaS only |
| Pricing model | Per-GB (free up to 200 GB/day) | Per-host + per-GB |
| Open source | Yes (AGPL-3.0) | No |
| OpenTelemetry | Native OTLP | Supported |
| Query language | SQL + PromQL | Proprietary |
| Vendor lock-in | None | High |
OpenObserve vs Elasticsearch
| Aspect | OpenObserve | Elasticsearch |
|---|---|---|
| Storage cost | 140x lower | High (hot/warm/cold tiers) |
| Setup complexity | Single binary | Complex cluster management |
| Query language | SQL | Lucene/KQL |
| Hardware requirements | ~1/4 the resources | High memory/CPU |
OpenObserve vs Splunk
| Aspect | OpenObserve | Splunk |
|---|---|---|
| Licensing | Open source | Expensive enterprise licensing |
| Deployment | Single binary or HA cluster | Complex |
| Query language | SQL + PromQL | SPL (proprietary) |
| Cost | Predictable, low | Unpredictable, high |
OpenObserve vs Grafana/Loki/Prometheus Stack
| Aspect | OpenObserve | Grafana Stack |
|---|---|---|
| Components | Single platform | Multiple tools (Grafana + Loki + Prometheus + Tempo) |
| Management | One binary | Multiple deployments |
| High cardinality | Full support | Loki struggles with high cardinality |
| Query performance | Fast on large volumes | Loki slow on large data |
Production Ready
OpenObserve is battle-tested in production environments worldwide:
- Thousands of active deployments across diverse industries
- Largest deployment: 2+ PB/day ingestion
- Single binary scales to terabytes — unique in the observability space
Security & Compliance
Security Features
- Secure by design with hardened container images
- Data encryption at rest and in transit
- Sensitive Data Redaction (SDR) — automatically redact sensitive data at ingestion and query time (Enterprise)
- Single Sign-On (SSO) — OIDC, OAuth, SAML, LDAP/AD integration (Enterprise)
- Role-Based Access Control (RBAC) — granular permissions (Enterprise) — Learn more →
Compliance Certifications
- ✅ SOC 2 Type II certified
- ✅ ISO 27001 certified
- ✅ GDPR compliant
- ✅ HIPAA ready (BAA available with Enterprise contracts)
OpenObserve meets the stringent security and compliance requirements of regulated industries including finance, healthcare, and government.
Enterprise Edition
OpenObserve is a true open source project. The open source edition is feature-complete and production-ready — logs, metrics, traces, dashboards, alerts, pipelines, and everything you need to run observability at scale. It will always remain actively maintained and free to use without restrictions.
For organizations that need enterprise-grade features and support, an Enterprise edition adds:
Enterprise features
- Single Sign-On (SSO) — OIDC, OAuth, SAML 2.0, LDAP/AD, and major identity providers (Okta, Azure Entra, Google, GitHub, GitLab, Keycloak)
- Advanced RBAC — granular role-based access control with custom roles — Learn more →
- Audit trails — comprehensive immutable audit logs with configurable retention
- Federated search — query across multiple clusters and regions with Super Cluster
- Sensitive Data Redaction (SDR) — automatically redact PII at ingestion and query time
- Advanced encryption — AES-256 SIV cipher keys with Google Tink KeySet and Akeyless integration
- Query & workload management (QoS) — control query resource usage and priorities in multi-tenant environments
Support & SLAs
- Dedicated support with contractual SLA guarantees and priority response times
- Technical account management, architecture review, and deployment assistance
- Migration support from existing tools, plus training and onboarding
Pricing
- Free tier: up to 50 GB/day of ingestion (~1.5 TB/month), including full commercial use (registration required at 50 GB/day)
- Volume discounts and multi-year contracts available
- View the complete feature comparison →
For enterprise inquiries and custom deployments, contact our sales team.
Community & Support
The best way to get help, share ideas, and connect with other OpenObserve users is through our community channels.
🔗 Join us on Slack
Our Slack community is the most active place for installation and configuration help, sharing best practices, discussing the roadmap, and connecting with the core team.
📱 Join the OpenObserve community on WeChat
Other ways to connect
- 💬 GitHub Discussions — longer-form discussions and Q&A
- 🐛 GitHub Issues — report bugs or request features
- 📖 Documentation — guides, tutorials, and API references
Contributing
We welcome contributions from the community! Whether you're fixing bugs, adding features, improving documentation, or sharing feedback, your help makes OpenObserve better for everyone.
To get started, read our Contributing Guide, which covers setting up your development environment, code standards, submitting pull requests, and reporting issues.
FAQ
How does OpenObserve achieve 140x lower storage costs?
Through a combination of Parquet columnar storage (efficient compression) and an S3-native architecture (inexpensive object storage). See the cost comparison chart in the Why OpenObserve? section.
What are the limitations?
All data in OpenObserve is immutable — once ingested, it cannot be modified or deleted (only entire retention periods can be dropped). This is by design and is a feature for logs and compliance use cases, ensuring data integrity and audit trails.
Is this production-ready?
Yes. OpenObserve runs in production across thousands of deployments worldwide, including environments processing in excess of 2 PB/day. See our customer stories for real-world examples.
How does query performance compare to Elasticsearch?
OpenObserve delivers better performance than Elasticsearch for most workloads, with faster search and significantly faster analytics — while using about a quarter of the hardware. The columnar Parquet format is particularly effective for complex aggregations and analytics.
Is there a steep learning curve?
No. OpenObserve is designed to be intuitive from day one:
- Familiar query languages — SQL for logs and traces, PromQL for metrics; no proprietary query language to learn
- Easy-to-use GUI — an intuitive interface with a drag-and-drop dashboard builder
- No complex tuning — unlike Elasticsearch, there are no shards, replicas, or heap sizes to manage. Just install and go.
Most users are productive within hours, not weeks.
License
Open Source Edition — licensed under AGPL-3.0. We chose AGPL to ensure that improvements to OpenObserve remain open source and benefit the entire community, while still allowing free commercial use. Why AGPL, and why it's good for the community →
Enterprise Edition — licensed under a commercial Enterprise License Agreement (not AGPL), which provides additional flexibility for enterprise deployments.
SBOM
Software Bill of Materials for OpenObserve. You can analyze either SBOM with Dependency-Track.
Rust
The SBOM is available here. To regenerate it:
cargo install cargo-cyclonedx
cargo-cyclonedx cyclonedx
JavaScript
The SBOM is available here. To regenerate it:
npm install --global @cyclonedx/cyclonedx-npm
cd web
cyclonedx-npm > sbom.json