Omkar Kesarkhaneandgithub-actions[bot] ddb67f3efb fix(synthetics): record from a specific step, and stop silently downgrading recorded actions (#13799)
Supersedes #13777, which carried the record-from-step commits alone.
Closing that in favour of this, because the two changes land in the same
three files (`types/synthetics.ts`, `useSyntheticsRecorder.ts`,
`JourneySteps.vue`) and reviewing them apart means resolving the same
conflict twice.

## Problem

**A recorded hover was stored as a click.**

Playwright 1.56 added `hover` to the recorder's action model, reachable
from its "Choose action" picker. The extension's action mapper seeds
every step with `action: 'click'` as a placeholder for its switch to
overwrite, and returned that placeholder from `default:` — so any action
name the switch did not know became a click the author never performed.

On the usual hover target — a nav trigger, a dropdown opener — clicking
it can navigate or submit. The run still reports green.

There are three separate guards meant to stop exactly this, and none of
them fired, because the relabel happens upstream of all of them:

| Guard | Why it missed |
|---|---|
| `UNSUPPORTED_REPLAY_ACTIONS` (extension) | step already said `click` |
| `RETIRED_ACTIONS` → `isStorableAction` | step already said `click` |
| `V2_STEP_ACTIONS` (Rust validation) | `click` is valid |

The same picker offers **Right click** and **Double click** as explicit
choices. Both were flattened too: `click_count` was dropped by the
mapper and never existed downstream, and the probe's executor called
`locator.click({ timeout })` while reading neither `button` nor
`click_count`. A deliberately recorded right click replayed as a left
click; a double click as a single one.

**Recording could only start from scratch.** Fixing step 12 of a 15-step
journey meant re-recording all 15.

## Change

**Record from a specific step.** Each step gets a record action that
replays the prefix before it, then flips the recorder into insert mode
at that point. A restore that cannot reach the requested step reports
where it stopped (`prefixFailed`) rather than silently recording from
the wrong place.

**Every action Playwright can record is now stored and replayed as
itself.**

- `hover` is a first-class v2 action — mapped, stored, validated, and
executed by `Locator.hover` in the probe and `Frame.hover` in the
extension player.
- `button` and `click_count` travel to storage, so right click and
double click replay as recorded.
- An action name the mapper does not know now **throws** instead of
returning the `click` placeholder. This is the part that is not
hover-specific: upstream added one action in nine minors and will add
more, and the next one must be a deliberate decision rather than a
silent downgrade.

**The extension handshake reports capabilities, not just presence.**
`getStatus` now returns `extVersion` and a `capabilities` array; O2
gates affordances on `hasCapability()` with a defined pre-handshake
fallback, and warns when the installed build is older than the minimum.
Previously the protocol carried no version at all — Chrome updates the
extension independently of when O2 deploys, so the two could disagree
about the wire with no way to say so.

**Two dead message declarations, opposite problems.** `setSources` no
longer exists in playwright-core (sources arrive alongside the actions),
so its declared variant could never fire — while its `generatedCode`
field is exactly what an eject-to-code feature would reach for. Deleted.
`elementPicked` is the reverse: it fires on every "Pick locator" and
every click in inspecting mode, and was being discarded, which made
inspect mode a dead end. Now kept.

### Compatibility

`button` and `click_count` are optional with defined absent-behaviour —
absent means a single left click. Every journey stored today stays
valid, means the same thing, and serialises byte-identically. **No
schema version bump and no migration.** A test pins that rather than
leaving it as an intention.

`hover` is a new vocabulary entry with no default, so the probe must be
able to execute one before O2 is allowed to store one — the probe change
ships first.

## Implementation

| File | |
|---|---|
| `src/config/src/meta/synthetics.rs` | `hover` joins
`V2_STEP_ACTIONS`/`V2_ELEMENT_ACTIONS`; `button` and `click_count` added
to `BrowserStepV2` with validation (`left\|middle\|right`, `1..=3`) |
| `web/src/types/synthetics.ts` | `button`/`clickCount` on both step
types; `extVersion` + `capabilities` on `RecorderStatus`; `setSources`
variant deleted and `elementPicked` typed; `prefixFailed` and
insert-mode fields on `recordingStarted` |
| `web/src/utils/synthetics/mapRecordedStep.ts` | promotes
`button`/`clickCount` from the wire, like every other stored field |
| `web/src/utils/synthetics/buildV2Steps.ts` | `hover` in
`ACTION_TO_V2`; crosses camelCase → snake_case for the two click fields
|
| `web/src/constants/synthetics.ts` | `hover` out of `RETIRED_ACTIONS`;
`MIN_EXTENSION_VERSION` |
| `web/src/composables/useSyntheticsRecorder.ts` | `startRecordingFrom`,
`hasCapability`, `pickedSelector`, `extensionOutdated` |
|
`web/src/components/synthetics/journey/{BrowserJourney,JourneySteps}.vue`
| per-step record action and its wiring |

`click_count` is capped at 3: the recorder only ever emits 1 or 2, and
an unbounded count is a way to hold a page's event loop open.

The two click fields cross from camelCase to snake_case in `buildV2Step`
and nowhere else — reading `step.wire` directly inside it would have
worked and invented a second path into storage.

### Depends on a recorder extension build

`hover`, the click fields and the capability handshake all need the
matching extension build. O2 degrades honestly without it:
`hasCapability()` falls back to the pre-handshake set, and an older
build raises the outdated-extension warning instead of failing on a
message shape it does not recognise.

## Tests

- **Rust** — hover accepted as an element action; `button`/`click_count`
validated at both bounds; a step carrying neither still validates (the
compatibility guarantee). Two existing tests encoded "hover is rejected"
and now say the opposite. 101 pass.
- **Probe** — hover hovers rather than clicks; a right click sends the
recorded button; a double click sends two clicks; a journey stored
before these fields replays unchanged. The action union is asserted
against the Rust vocabulary, so the next divergence fails a test instead
of reaching an executor with no case for it. Also pinned: a selector
carrying a frame hop resolves into the iframe, which had no coverage
anywhere.
- **Web** — 1213 across 60 files. Nine existing tests encoded "hover is
retired" across constants, `buildV2Steps`, `buildPayload` and the
save-gate schema; each now states the opposite deliberately.
- **Extension** — the unmapped-action throw, hover round-tripping both
directions, and a double click surviving the round trip as two clicks.

`vue-tsc`, `cargo clippy -D warnings`, and `prettier --check` are clean.
The last commit is formatting only: the three record-from-step files
arrived failing `format:check`, which is a gate of its own and would not
have been caught by lint.

---------

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
2026-08-16 17:50:46 +00:00
2026-08-07 11:45:59 +00:00
2026-06-02 03:58:01 +00:00
2026-08-05 13:44:27 +08:00
2026-03-04 17:55:01 +05:30
2026-03-04 17:55:01 +05:30
2026-01-14 16:54:35 +08:00
2024-09-25 11:09:26 +08:00
2026-04-25 19:18:21 +00:00
2026-08-05 13:28:09 +08:00
2026-08-05 13:28:09 +08:00
2024-06-10 13:10:01 -07:00
2023-11-26 11:04:37 -08:00
2026-06-02 03:58:01 +00:00
2025-08-11 17:06:35 -07:00

OpenObserve

Open source Datadog alternative for logs, metrics, traces, and frontend monitoring. Modern observability platform: 10x easier, 140x lower storage cost, high performance, petabyte scale.

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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?

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

OpenObserve vs Elasticsearch storage cost comparison

Quick Start

OpenObserve Cloud (fastest way)

Get started in minutes without managing infrastructure. The free tier includes up to 50 GB/day of ingestion.

Get Started Free →

🐳 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.

Watch the OpenObserve introduction video

🏠 Unified Overview

A single home for your workspace — active incidents, service health (error rate, latency, requests), anomalies, and recent events at a glance.

OpenObserve home overview

📊 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 →

Logs search with histogram and field explorer

🔍 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 →

Distributed trace waterfall view

🕸️ 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.

Service dependency graph

📈 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 →

Metrics explorer browsing metric time series

📉 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 →

Kubernetes namespace dashboard with template variables

👀 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 →

Session replay with event timeline

🔔 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 →

Alerts list with scheduled, real-time, and anomaly alerts

🚨 Incidents

Correlate related alerts into incidents and track them through their lifecycle — open, acknowledged, and resolved — with severity and dimension context for faster response.

Incident management and tracking

🔀 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 →

Visual pipeline editor

🤖 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.

AI/LLM observability insights

✨ 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.

O2 AI Assistant

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

Read customer stories →

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

Join OpenObserve 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 conversation →

📱 Join the OpenObserve community on WeChat

OpenObserve WeChat QR code

Other ways to connect

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
S
Description
Open source observability platform for logs, metrics, traces, RUM (web, android, ios), Session replay, pipelines, SLO and LLM observability. A sophisticated, simple and highly performant alternative to Datadog, Splunk, and Elasticsearch with 140x lower storage costs and single binary deployment.
Readme AGPL-3.0
1 GiB
Languages
TypeScript 40%
Rust 29.3%
Vue 17%
JavaScript 11%
Python 2.3%
Other 0.3%