# Company Hiring Trend Monitor (`coregent/company-hiring-trend-monitor`) Actor Monitor public company career pages and ATS boards over repeated runs and detect company-level hiring changes - new roles, removed roles, department growth, location expansion, and remote/hybrid movement. No login or cookies. - **URL**: https://apify.com/coregent/company-hiring-trend-monitor.md - **Developed by:** [Delowar Munna](https://apify.com/coregent) (community) - **Categories:** Jobs, Automation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.40 / 1,000 company-trend-results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Company Hiring Trend Monitor ![Company Hiring Trend Monitor](https://raw.githubusercontent.com/coregentdevspace/company-hiring-trend-monitor-assets/main/thumbnail-company-hiring-trend-monitor.png) Monitor public company **career pages and ATS boards** over repeated runs and detect **company-level hiring changes** — new roles, removed roles, department growth, location expansion, and remote/hybrid movement. The actor turns repeated job-listing snapshots into a clean, flat, CSV-friendly **hiring trend dataset** built for sales triggers, recruiting intelligence, market research, and competitor hiring analysis. Unlike generic job scrapers that only return the _current_ listings, this actor shows **what changed across runs**, which is what matters for sales timing and competitor growth monitoring. - **No login, no cookies, no sessions.** Public sources only. - **One flat trend row per company per run.** - **Pay only for valid unique company trend rows** (`company-trend-result`). --- ### How it works Each run, for every company you supply: 1. **Detect the source** from the URL — Greenhouse, Lever, Ashby, Workable, or a generic careers page. 2. **Extract current open roles** over HTTP (public JSON endpoints where available, otherwise HTML). 3. **Load the previous snapshot** for that company from the Apify Key-Value Store. 4. **Diff** current vs previous: new jobs, removed jobs, open-roles delta, department & location growth, remote/hybrid/on-site movement. 5. **Score** the change with a transparent 0–100 `hiring_trend_score` (no AI). 6. **Save** the new snapshot for next time (unless `saveSnapshot` is off). #### First run is a baseline The **first** time a company is seen there is nothing to compare against, so the row is marked `snapshot_status = baseline_created`, `hiring_trend_label = no_baseline`, `previous_open_roles = null`, and a baseline snapshot is stored. **Run the actor again later** (e.g. on a schedule) to get real change detection. --- ### Supported sources | Source | Example URL | Extraction | | -------------------- | ----------------------------------- | ---------------------------------------------------- | | Greenhouse | `https://boards.greenhouse.io/acme` | Public board JSON API | | Lever | `https://jobs.lever.co/acme` | Public postings JSON API | | Ashby | `https://jobs.ashbyhq.com/acme` | Public job-board JSON API | | Workable | `https://apply.workable.com/acme` | Public widget JSON (best-effort) | | Generic careers page | `https://acme.com/careers` | JSON-LD `JobPosting` + link heuristics (best-effort) | --- ### Input Provide **at least one** of `companyUrls` or `companies`. | Field | Type | Default | Purpose | | ---------------------- | -------- | --------------------------- | -------------------------------------------------------- | | `companyUrls` | string[] | `[]` | Raw career/ATS URLs to monitor | | `companies` | object[] | `[]` | Structured `{ companyName, careersUrl, companyWebsite }` | | `maxCompanies` | integer | `100` | Cap on companies processed (1–1000) | | `maxJobsPerCompany` | integer | `250` | Cap on jobs per company (1–1000) | | `outputMode` | string | `company_trends_only` | `company_trends_only` or `company_and_jobs` | | `onlyChangedCompanies` | boolean | `false` | Keep only companies with detected changes | | `minChangeCount` | integer | `0` | Min `new + removed` jobs to keep a company | | `departmentKeywords` | string[] | `[]` | Keep only companies hiring in these departments | | `locationKeywords` | string[] | `[]` | Keep only companies hiring in these locations | | `remoteFilter` | string | `any` | `any`, `remote_only`, `hybrid_or_remote`, `onsite_only` | | `snapshotKeyPrefix` | string | `hiring-trend` | Namespace for stored snapshots | | `saveSnapshot` | boolean | `true` | Set `false` for dry-run (compare, don't overwrite) | | `deduplicateJobs` | boolean | `true` | Remove duplicate jobs before comparison | | `proxyConfiguration` | object | `{ "useApifyProxy": true }` | See proxy policy below | | `debugMode` | boolean | `false` | Extra logs | > No field accepts login credentials, cookies, session tokens, authorization headers, or private API keys. #### Sample input — structured companies ```json { "companies": [ { "companyName": "Acme SaaS", "companyWebsite": "https://acme.com", "careersUrl": "https://jobs.lever.co/acme" }, { "companyName": "Acme AI", "companyWebsite": "https://acme.ai", "careersUrl": "https://boards.greenhouse.io/acmeai" } ], "outputMode": "company_trends_only", "onlyChangedCompanies": true, "minChangeCount": 1, "saveSnapshot": true } ```` #### Sample input — raw URLs + filters ```json { "companyUrls": [ "https://boards.greenhouse.io/figma", "https://jobs.ashbyhq.com/openai", "https://jobs.lever.co/leverdemo" ], "departmentKeywords": ["engineering", "sales"], "locationKeywords": ["remote", "london"], "remoteFilter": "hybrid_or_remote", "maxJobsPerCompany": 250 } ``` *** ### Output ![Company Hiring Trend Monitor output — all fields, table view](https://raw.githubusercontent.com/coregentdevspace/company-hiring-trend-monitor-assets/main/company-hiring-trend-monitor-output-all-fields-table-view.png) One flat `company_trend` row per company. Key fields: | Field | Description | | ------------------------------------------------------------------------------------ | ------------------------------------------------------- | | `company_name`, `company_website`, `careers_url`, `source_type`, `company_key` | Identity & source | | `snapshot_status` | `baseline_created`, `changed`, `unchanged`, or `failed` | | `current_open_roles`, `previous_open_roles`, `open_roles_delta` | Role counts | | `new_jobs_count`, `removed_jobs_count`, `unchanged_jobs_count`, `changed_job_titles` | Job-level diff | | `top_departments`, `department_growth_signals` | Department mix & growth | | `top_locations`, `location_growth_signals` | Location mix & growth | | `remote_jobs_count`, `hybrid_jobs_count`, `onsite_jobs_count`, `remote_delta` | Workplace mix | | `hiring_trend_score`, `hiring_trend_label`, `reason_tags` | Transparent 0–100 score | | `first_seen_at`, `previous_snapshot_at`, `current_snapshot_at` | Timestamps | | `filtered_match`, `source_error`, `scraped_at` | Status | When `outputMode = company_and_jobs`, additional flat `job_snapshot` rows are pushed for each current job (these are **not** charged). #### Sample `company_trend` row (from a live run) ```json { "record_type": "company_trend", "input_url": "https://boards.greenhouse.io/figma", "company_name": "Figma", "company_website": null, "careers_url": "https://boards.greenhouse.io/figma", "source_type": "greenhouse", "company_key": "figma-5888e4", "snapshot_status": "unchanged", "current_open_roles": 167, "previous_open_roles": 167, "open_roles_delta": 0, "new_jobs_count": 0, "removed_jobs_count": 0, "unchanged_jobs_count": 167, "changed_job_titles": "", "top_departments": "Sales: 64; Engineering: 30; Marketing: 15; Business Operations: 14; Weavy - Figma Weave: 9", "top_locations": "San Francisco, CA, New York, NY, United States: 88; London, England: 14; Tokyo, Japan: 11; Paris, France: 8; San Francisco, CA: 7", "remote_jobs_count": 1, "hybrid_jobs_count": 0, "onsite_jobs_count": 166, "remote_delta": 0, "hiring_trend_score": 50, "hiring_trend_label": "stable", "reason_tags": "large_employer; no_change_detected", "first_seen_at": "2026-06-09T04:19:12.939Z", "previous_snapshot_at": "2026-06-09T04:37:28.443Z", "current_snapshot_at": "2026-06-09T04:39:00.293Z", "filtered_match": true, "source_error": null, "scraped_at": "2026-06-09T04:39:00.293Z" } ``` > The first run for any company is a **baseline** (`snapshot_status: baseline_created`, deltas `null`). The delta fields above populate from the second run onward — for example a growing company returns `snapshot_status: changed`, `new_jobs_count: 11`, `open_roles_delta: 8`, `changed_job_titles: "NEW: Senior Data Engineer; …"`, `department_growth_signals: "Engineering +5; Sales +3"`, and a higher `hiring_trend_score`/`fast_growing` label. #### Sample `job_snapshot` row (`outputMode = company_and_jobs`) ```json { "record_type": "job_snapshot", "company_name": "Figma", "company_key": "figma-5888e4", "source_type": "greenhouse", "job_id": "6789012", "job_title": "Senior Software Engineer, Platform", "department": "Engineering", "location": "San Francisco, CA", "workplace_type": "onsite", "job_url": "https://boards.greenhouse.io/figma/jobs/6789012", "posted_at": "2026-06-02T00:00:00.000Z", "is_new_since_previous": true, "was_removed": false, "current_snapshot_at": "2026-06-09T04:39:00.293Z", "scraped_at": "2026-06-09T04:39:00.293Z" } ``` A `RUN_SUMMARY` object (companies processed, baselines created, changed/unchanged counts, duplicates removed, charged events, per-source counts, runtime) is written to the default Key-Value Store. *** ### Pricing This actor uses **Pay Per Event**. You are charged the `company-trend-result` event **once per valid unique company trend row** that passes your filters and is saved. Failed inputs, duplicates, filtered-out companies, and optional `job_snapshot` rows are **never** charged. The per-run spending limit you set on Apify is respected — the actor stops pushing once the cap is reached. #### 🚦 Proxy policy Use **Apify Datacenter** proxy or **no proxy** for normal runs — both work reliably for public career pages and ATS APIs at this actor's conservative concurrency. **Apify Residential proxy is not supported.** The actor will fail at startup if `apifyProxyGroups` includes `RESIDENTIAL`. Reason: in pay-per-event actors, residential bandwidth (charged per GB) is billed to the developer, not the run user, so a single bandwidth-heavy run could exceed the per-result event revenue. If you genuinely need residential routing, supply your own residential provider via the proxy editor's **Custom proxy URLs** field — that traffic goes through your provider, not Apify, and is unaffected: ``` http://user:pass@proxy.iproyal.com:12321 http://user:pass@proxy.brightdata.com:22225 http://user:pass@proxy.oxylabs.io:7777 ``` *** ### Tips - **Schedule it.** Trend detection needs at least two runs. Use Apify Schedules (e.g. weekly) with the same `snapshotKeyPrefix` to build a hiring-movement history. - **Separate streams** with different `snapshotKeyPrefix` values (e.g. `competitors`, `prospects`). - **Dry-run** with `saveSnapshot: false` to compare without overwriting your stored baseline. # Actor input Schema ## `companyUrls` (type: `array`): Public career-page or ATS board URLs to monitor, e.g. "https://boards.greenhouse.io/acme", "https://jobs.lever.co/acme", "https://jobs.ashbyhq.com/acme". Each URL becomes one company. Provide at least one of Company URLs or Companies. ## `companies` (type: `array`): Structured company inputs as JSON objects: { "companyName": "Acme", "careersUrl": "https://jobs.lever.co/acme", "companyWebsite": "https://acme.com" }. Use this when you want stable company names and websites instead of guessing from the page. ## `maxCompanies` (type: `integer`): Safety cap on how many companies are processed in one run. ## `maxJobsPerCompany` (type: `integer`): Prevents runaway pagination on very large employers. Collection stops for a company after this many unique jobs. ## `outputMode` (type: `string`): Whether the dataset contains only company trend rows, or also the current job rows behind each company. ## `onlyChangedCompanies` (type: `boolean`): Return only companies with detected changes (new jobs, removed jobs, or a non-zero open-roles delta) since the previous run. ## `minChangeCount` (type: `integer`): Keep only companies where (new jobs + removed jobs) is at least this number. ## `departmentKeywords` (type: `array`): Keep only companies hiring in these departments/categories (matched against job departments and titles, case-insensitive). Leave empty to keep all. ## `locationKeywords` (type: `array`): Keep only companies with jobs in these locations (countries, cities, regions, or "remote"), case-insensitive. Leave empty to keep all. ## `remoteFilter` (type: `string`): Filter companies by the work arrangement of their current jobs. ## `snapshotKeyPrefix` (type: `string`): Namespace for the per-company snapshots stored in the Key-Value Store. Use different prefixes to keep separate monitoring streams independent. Letters, numbers, dash, underscore (3-80 chars). ## `saveSnapshot` (type: `boolean`): Save the current snapshot after comparison. Turn off for dry-run/test runs that compare against the previous snapshot without overwriting it. ## `deduplicateJobs` (type: `boolean`): Remove duplicate jobs within each company before comparison (by source job ID, canonical URL, then title/location/department). ## `proxyConfiguration` (type: `object`): Apify Proxy configuration. Defaults to Apify Proxy enabled. Apify Residential is NOT supported and will fail the run at startup; if you need residential routing, supply your own provider via Custom proxy URLs (proxyUrls). ## `debugMode` (type: `boolean`): Extra logs: source detection, extraction counts, and filter/failure reasons. ## Actor input object example ```json { "companyUrls": [ "https://boards.greenhouse.io/figma", "https://jobs.lever.co/voodoo" ], "companies": [], "maxCompanies": 100, "maxJobsPerCompany": 250, "outputMode": "company_trends_only", "onlyChangedCompanies": false, "minChangeCount": 0, "departmentKeywords": [], "locationKeywords": [], "remoteFilter": "any", "snapshotKeyPrefix": "hiring-trend", "saveSnapshot": true, "deduplicateJobs": true, "proxyConfiguration": { "useApifyProxy": true }, "debugMode": false } ``` # Actor output Schema ## `overview` (type: `string`): Flat company-level trend table - one row per company per run, with current/previous open-role counts, deltas, department and location growth signals, remote movement, and a transparent 0-100 hiring-trend score. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "companyUrls": [ "https://boards.greenhouse.io/figma", "https://jobs.lever.co/voodoo" ], "companies": [], "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("coregent/company-hiring-trend-monitor").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "companyUrls": [ "https://boards.greenhouse.io/figma", "https://jobs.lever.co/voodoo", ], "companies": [], "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("coregent/company-hiring-trend-monitor").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "companyUrls": [ "https://boards.greenhouse.io/figma", "https://jobs.lever.co/voodoo" ], "companies": [], "proxyConfiguration": { "useApifyProxy": true } }' | apify call coregent/company-hiring-trend-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=coregent/company-hiring-trend-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Company Hiring Trend Monitor", "description": "Monitor public company career pages and ATS boards over repeated runs and detect company-level hiring changes - new roles, removed roles, department growth, location expansion, and remote/hybrid movement. No login or cookies.", "version": "1.0", "x-build-id": "OaxGUdDyibLP0REyd" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/coregent~company-hiring-trend-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-coregent-company-hiring-trend-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/coregent~company-hiring-trend-monitor/runs": { "post": { "operationId": "runs-sync-coregent-company-hiring-trend-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/coregent~company-hiring-trend-monitor/run-sync": { "post": { "operationId": "run-sync-coregent-company-hiring-trend-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "companyUrls": { "title": "Company career / ATS URLs", "type": "array", "description": "Public career-page or ATS board URLs to monitor, e.g. \"https://boards.greenhouse.io/acme\", \"https://jobs.lever.co/acme\", \"https://jobs.ashbyhq.com/acme\". Each URL becomes one company. Provide at least one of Company URLs or Companies.", "default": [], "items": { "type": "string" } }, "companies": { "title": "Companies (structured)", "type": "array", "description": "Structured company inputs as JSON objects: { \"companyName\": \"Acme\", \"careersUrl\": \"https://jobs.lever.co/acme\", \"companyWebsite\": \"https://acme.com\" }. Use this when you want stable company names and websites instead of guessing from the page.", "default": [] }, "maxCompanies": { "title": "Max companies", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Safety cap on how many companies are processed in one run.", "default": 100 }, "maxJobsPerCompany": { "title": "Max jobs per company", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Prevents runaway pagination on very large employers. Collection stops for a company after this many unique jobs.", "default": 250 }, "outputMode": { "title": "Output mode", "enum": [ "company_trends_only", "company_and_jobs" ], "type": "string", "description": "Whether the dataset contains only company trend rows, or also the current job rows behind each company.", "default": "company_trends_only" }, "onlyChangedCompanies": { "title": "Only changed companies", "type": "boolean", "description": "Return only companies with detected changes (new jobs, removed jobs, or a non-zero open-roles delta) since the previous run.", "default": false }, "minChangeCount": { "title": "Minimum change count", "minimum": 0, "maximum": 1000, "type": "integer", "description": "Keep only companies where (new jobs + removed jobs) is at least this number.", "default": 0 }, "departmentKeywords": { "title": "Department keywords", "type": "array", "description": "Keep only companies hiring in these departments/categories (matched against job departments and titles, case-insensitive). Leave empty to keep all.", "default": [], "items": { "type": "string" } }, "locationKeywords": { "title": "Location keywords", "type": "array", "description": "Keep only companies with jobs in these locations (countries, cities, regions, or \"remote\"), case-insensitive. Leave empty to keep all.", "default": [], "items": { "type": "string" } }, "remoteFilter": { "title": "Remote filter", "enum": [ "any", "remote_only", "hybrid_or_remote", "onsite_only" ], "type": "string", "description": "Filter companies by the work arrangement of their current jobs.", "default": "any" }, "snapshotKeyPrefix": { "title": "Snapshot key prefix", "type": "string", "description": "Namespace for the per-company snapshots stored in the Key-Value Store. Use different prefixes to keep separate monitoring streams independent. Letters, numbers, dash, underscore (3-80 chars).", "default": "hiring-trend" }, "saveSnapshot": { "title": "Save snapshot", "type": "boolean", "description": "Save the current snapshot after comparison. Turn off for dry-run/test runs that compare against the previous snapshot without overwriting it.", "default": true }, "deduplicateJobs": { "title": "Deduplicate jobs", "type": "boolean", "description": "Remove duplicate jobs within each company before comparison (by source job ID, canonical URL, then title/location/department).", "default": true }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Apify Proxy configuration. Defaults to Apify Proxy enabled. Apify Residential is NOT supported and will fail the run at startup; if you need residential routing, supply your own provider via Custom proxy URLs (proxyUrls).", "default": { "useApifyProxy": true } }, "debugMode": { "title": "Debug mode", "type": "boolean", "description": "Extra logs: source detection, extraction counts, and filter/failure reasons.", "default": false } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```