# Glassdoor Scraper - Jobs, Companies & Salaries (`makework36/glassdoor-scraper`) Actor Scrape Glassdoor job listings: title, company, location, salary parsed, employment type, description. 25+ structured fields per job via JSON-LD. HTTP-only, low cost. - **URL**: https://apify.com/makework36/glassdoor-scraper.md - **Developed by:** [deusex machine](https://apify.com/makework36) (community) - **Categories:** Jobs, Lead generation - **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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 ## Glassdoor Scraper API — Jobs, Companies, Salaries & Reviews Data A high-performance **Glassdoor scraper** that extracts complete job listings from [Glassdoor.com](https://www.glassdoor.com), one of the most trusted job & employer review platforms with 80M+ reviews and millions of active job postings across the US, UK, Canada, India, Australia, Germany and France. Pull 25+ structured fields per job — title, company name, location parsed to city/state/country, salary range with currency and unit, full description, employment type, posting date, and education/experience requirements — without writing a single line of HTML scraping logic. Built for recruiters tracking US, UK and EMEA labor supply, market analysts comparing pay across [LinkedIn Jobs](https://www.linkedin.com/jobs), [Indeed](https://www.indeed.com), and [BLS](https://www.bls.gov) data, salary benchmarking firms, founders monitoring competitor hiring patterns, and ML teams training resume-to-job matching pipelines against the [schema.org JobPosting](https://schema.org/JobPosting) schema. Output is clean JSON, ready for [Google BigQuery](https://cloud.google.com/bigquery), Snowflake, Postgres, or [Google Sheets](https://workspace.google.com/products/sheets/). ### ✨ Why use this scraper This actor automates browsing **glassdoor.com** the way a real visitor does. It hits the public job search pages, walks through pagination, parses the embedded [schema.org JobPosting](https://schema.org/JobPosting) JSON-LD blocks served alongside each search result, and visits every individual job detail page to extract the full structured posting — title, company, salary, location, employment type, description, education and experience requirements. The pricing logic is automatic: Glassdoor's JSON-LD baseSalary block becomes `salaryMin: 143913`, `salaryMax: 197200`, `salaryCurrency: "USD"`, `salaryUnit: "YEAR"`, plus a human-readable `salaryText: "$143,913 - $197,200 USD/year"`. Locations are split into city, state/region, country, postal code and street address, so downstream filtering by city or state works out of the box. The scraper is HTTP-only — no headless browser, no captcha solver. Memory footprint is 512 MB, dramatically lower than the 4 GB needed by browser-based competitors. It runs on Apify's residential proxy network out of the box. ### 📤 Output fields Every record contains these fields when present in Glassdoor's structured data: #### Identity & links - `title` — Position title - `jobUrl` — Direct link to the Glassdoor listing - `position` — Position in the search results ranking #### Company - `companyName` — Hiring company - `companyUrl` — Company's external URL (sameAs from JSON-LD) - `companyLogoUrl` — Logo image URL - `industry` — Industry classification #### Location - `location` — Concatenated "City, State, Country" string - `addressLocality` — City - `addressRegion` — State or region - `addressCountry` — Country name - `postalCode` — Postal/ZIP code - `streetAddress` — Street address when published - `jobLocationType` — `"TELECOMMUTE"` when remote - `applicantLocationRequirements` — Geographic eligibility #### Salary - `salaryText` — Human-readable formatted string - `salaryMin` — Lower bound number - `salaryMax` — Upper bound number - `salaryValue` — Single value when no range is given - `salaryCurrency` — `"USD"`, `"EUR"`, `"GBP"`, etc. - `salaryUnit` — `"YEAR"`, `"HOUR"`, `"MONTH"`, `"WEEK"` #### Description & requirements - `jobDescription` — Full description text - `jobDescriptionHtml` — Original HTML markup of the description - `qualifications` — Required qualifications when separately published - `responsibilities` — Day-to-day responsibilities - `skills` — Skills list from JSON-LD when provided - `educationRequirements` — Education level required - `experienceRequirements` — Experience required #### Timestamps & employment type - `datePosted` — ISO 8601 posting date - `postedDate` — Alias of datePosted - `validThrough` — Listing expiration date - `employmentType` — Array of types (`"FULL_TIME"`, `"PART_TIME"`, `"CONTRACTOR"`, `"INTERN"`) - `directApply` — Boolean: can apply directly on Glassdoor? ### 🎯 Use cases 1. **Recruitment talent radar** — Track jobs matching your hiring niche, filter by `addressRegion` for US states, by `employmentType` for full-time only, by `salaryMin` for compensation bands. 2. **Salary benchmarking** — Aggregate `salaryMin`/`salaryMax` by job title + location to produce reliable pay bands. The `salaryUnit` field lets you cleanly separate hourly vs annual data. 3. **Hiring intelligence** — Track which companies are scaling specific functions. Combine `companyName` + `industry` for clean B2B segmentation. 4. **ML training corpora** — Pair `title`, full `jobDescription`, `educationRequirements`, and `experienceRequirements` to train resume-to-job matching models. 5. **Lead generation** — Identify companies actively hiring in your niche (e.g. all US companies hiring a "VP of Engineering"). Use `companyName` + `addressLocality` for geographic prospecting. 6. **Compensation transparency reports** — Detect employers consistently posting salary ranges vs those who don't, useful for pay equity research. ### 🚀 How to use #### Mode 1 — Search by keywords (easiest) ```json { "mode": "keywords", "keywords": ["python developer", "data engineer"], "country": "us", "maxJobs": 100, "fetchDetails": true } ```` #### Mode 2 — Multi-country pipeline ```json { "mode": "keywords", "keywords": ["software engineer"], "country": "uk", "maxJobs": 200, "fetchDetails": true } ``` #### Mode 3 — Pre-built search URLs (advanced) ```json { "mode": "urls", "searchUrls": [ { "url": "https://www.glassdoor.com/Job/remote-python-developer-jobs-SRCH_IL.0,6_IS11047_KO7,23.htm" } ], "maxJobs": 50, "fetchDetails": true } ``` ### 📥 Input | Parameter | Type | Default | Description | |---|---|---|---| | `mode` | enum | `"keywords"` | `"keywords"` or `"urls"` | | `keywords` | array | `["python developer"]` | Job titles / keywords | | `country` | enum | `"us"` | Regional Glassdoor domain | | `searchUrls` | array | `[]` | Pre-built URLs (urls mode) | | `maxJobs` | integer | `50` | Cap per keyword/URL | | `fetchDetails` | boolean | `true` | Visit detail pages for full structured data | | `proxyConfiguration` | object | RESIDENTIAL | Apify proxy (residential recommended) | ### 📋 Output example ```json { "position": 1, "title": "Python Developer", "jobUrl": "https://www.glassdoor.com/job-listing/python-developer-social-security-administration-...", "companyName": "US Social Security Administration", "companyLogoUrl": "https://media.glassdoor.com/sql/...png", "companyUrl": "https://www.ssa.gov", "industry": "Government", "location": "Woodlawn, Maryland, United States", "addressLocality": "Woodlawn", "addressRegion": "Maryland", "addressCountry": "United States", "salaryText": "$143,913 - $197,200 USD/year", "salaryMin": 143913, "salaryMax": 197200, "salaryCurrency": "USD", "salaryUnit": "YEAR", "employmentType": ["FULL_TIME"], "datePosted": "2026-05-06T00:00:00", "validThrough": "2026-06-06T00:00:00", "jobDescription": "Summary IT Specialist (APPSW), Python Developer position(s) are being filled through the Office of Personnel Management...", "educationRequirements": "Bachelor's degree", "experienceRequirements": "5 years" } ``` ### 💻 Code examples #### From the Apify API (curl) ```bash curl -X POST "https://api.apify.com/v2/acts/makework36~glassdoor-scraper/run-sync-get-dataset-items?token=$APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "mode": "keywords", "keywords": ["data engineer"], "country": "us", "maxJobs": 100, "fetchDetails": true }' ``` #### From Python (apify-client) ```python from apify_client import ApifyClient client = ApifyClient("YOUR_APIFY_TOKEN") run = client.actor("makework36/glassdoor-scraper").call(run_input={ "mode": "keywords", "keywords": ["python developer", "data scientist"], "country": "us", "maxJobs": 200, "fetchDetails": True, }) for job in client.dataset(run["defaultDatasetId"]).iterate_items(): print(job["title"], job["companyName"], job.get("salaryText")) ``` #### From Node.js (apify-client) ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' }); const run = await client.actor('makework36/glassdoor-scraper').call({ mode: 'keywords', keywords: ['software engineer'], country: 'us', maxJobs: 100, fetchDetails: true, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(`Got ${items.length} jobs`); ``` #### Export to CSV ```bash curl "https://api.apify.com/v2/acts/makework36~glassdoor-scraper/runs/last/dataset/items?format=csv&token=$APIFY_TOKEN" \ -o glassdoor_jobs.csv ``` ### ⚡ Performance | Mode | Time per job | 100 jobs ETA | |---|---:|---:| | Search only (titles + URLs) | ~0.5 s | ~50 s | | With `fetchDetails: true` | ~7–15 s | ~12–25 min | Detailed mode visits each individual job page to extract the full JSON-LD JobPosting. This is necessary for salary, full description, employment type and address. Search-only mode is much faster but returns only title + URL. ### 📊 Comparison | Feature | This actor | Browser-only with proxy | Headless + captcha solver | |---|:---:|:---:|:---:| | Output fields | 25+ structured | 15–20 | 18 | | Salary parsed to Min/Max/Currency/Unit | ✅ | partial | partial | | Location split (city/state/country) | ✅ | ❌ | ❌ | | Pure HTTP (no browser) | ✅ | ❌ | ❌ | | Memory footprint | 512 MB | 4 GB | 4 GB | | Captcha solver required | ❌ | ❌ | ✅ | | Pricing model | PAY\_PER\_EVENT tiered | flat | flat | ### 💵 Pricing This actor uses **PAY\_PER\_EVENT** pricing with tiered volume discounts. | Tier | Standard job (URL+title only) | Detailed job (full JSON-LD) | |:-----|---:|---:| | FREE | $1.50 / 1K | $7.50 / 1K | | BRONZE | $1.10 / 1K | $5.50 / 1K | | SILVER | $0.80 / 1K | $4.00 / 1K | | GOLD | $0.55 / 1K | $2.80 / 1K | | PLATINUM | $0.40 / 1K | $2.20 / 1K | | DIAMOND | $0.28 / 1K | $1.80 / 1K | Plus a one-time **$0.001 per actor run**. Detailed mode is the default because Glassdoor's value lives in the structured JobPosting data on each individual page. ### ❓ FAQ **Why does the scraper need Residential proxies?** Glassdoor blocks datacenter IPs aggressively. Residential proxies route traffic through real households, which Glassdoor accepts. Apify includes residential proxy access in most paid plans. **Is scraping Glassdoor legal?** This actor accesses publicly available job pages — no login, no paywall bypass, no PII extraction beyond what employers post publicly. Always check Glassdoor's terms of service and consult legal counsel for your jurisdiction. **Can I scrape Glassdoor company reviews / salaries?** No — this actor focuses on job listings. Glassdoor's reviews and aggregated salary reports require a different stack and have different terms-of-service implications. **Does this support Glassdoor UK / Canada / Germany / France?** Yes. Set `country` to `uk`, `ca`, `de`, `fr`, `in`, or `au` and the scraper hits the matching regional Glassdoor domain. **How fresh is the data?** The scraper fetches in real time at run start. Glassdoor updates listings continuously. **Can I scrape Glassdoor without writing code?** Yes — use the input form on this page, click Start, then download the dataset as CSV or Excel. **Why are `qualifications` and `responsibilities` fields sometimes empty?** Not all Glassdoor postings split these out as separate JSON-LD properties. When absent, the same information typically lives inside `jobDescription` as a paragraph. **Does the scraper deduplicate jobs?** Yes. Each `jobUrl` is tracked across pages within a run; duplicates are skipped. **Is there a rate limit on my side?** The actor uses jitter between pages and rotates proxy sessions automatically. For very large runs (>5,000 jobs), split across multiple Apify Tasks scheduled minutes apart. ### 📝 Changelog - **0.1** (2026-05) — Initial release. Keywords + URLs modes. JSON-LD parsing for search and detail. 25+ fields. Residential proxy default. ### 🔗 Related actors - [`makework36/indeed-scraper`](https://apify.com/makework36/indeed-scraper) — Indeed.com US jobs - [`makework36/naukri-scraper`](https://apify.com/makework36/naukri-scraper) — Naukri.com India jobs - [`makework36/trustpilot-reviews-scraper`](https://apify.com/makework36/trustpilot-reviews-scraper) — Trustpilot reviews - [`makework36/google-maps-scraper-full`](https://apify.com/makework36/google-maps-scraper-full) — Google Maps places # Actor input Schema ## `mode` (type: `string`): 'keywords' searches Glassdoor by keyword. 'urls' takes pre-built search URLs. ## `keywords` (type: `array`): Job titles or keywords to search (e.g. 'python developer', 'data scientist'). ## `searchUrls` (type: `array`): Pre-built Glassdoor search URLs. ## `country` (type: `string`): Glassdoor regional domain to search on. ## `maxJobs` (type: `integer`): Maximum jobs per keyword/URL. Glassdoor shows ~30 jobs per page. ## `fetchDetails` (type: `boolean`): Visit each job detail page for full description + JSON-LD JobPosting (salary, employment type, address). Slower but ~20 extra fields. ## `proxyConfiguration` (type: `object`): Apify proxy. Residential recommended to avoid Glassdoor rate-limiting. ## Actor input object example ```json { "mode": "keywords", "keywords": [ "python developer" ], "searchUrls": [], "country": "us", "maxJobs": 10, "fetchDetails": true, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # 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 = { "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("makework36/glassdoor-scraper").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 = { "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], } } # Run the Actor and wait for it to finish run = client.actor("makework36/glassdoor-scraper").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 '{ "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call makework36/glassdoor-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=makework36/glassdoor-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Glassdoor Scraper - Jobs, Companies & Salaries", "description": "Scrape Glassdoor job listings: title, company, location, salary parsed, employment type, description. 25+ structured fields per job via JSON-LD. HTTP-only, low cost.", "version": "0.1", "x-build-id": "wznKcPMqNRMCirOyE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/makework36~glassdoor-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-makework36-glassdoor-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/makework36~glassdoor-scraper/runs": { "post": { "operationId": "runs-sync-makework36-glassdoor-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/makework36~glassdoor-scraper/run-sync": { "post": { "operationId": "run-sync-makework36-glassdoor-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "keywords", "urls" ], "type": "string", "description": "'keywords' searches Glassdoor by keyword. 'urls' takes pre-built search URLs.", "default": "keywords" }, "keywords": { "title": "Keywords", "type": "array", "description": "Job titles or keywords to search (e.g. 'python developer', 'data scientist').", "default": [ "python developer" ], "items": { "type": "string" } }, "searchUrls": { "title": "Search URLs", "type": "array", "description": "Pre-built Glassdoor search URLs.", "default": [], "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "country": { "title": "Glassdoor country", "enum": [ "us", "uk", "ca", "in", "au", "de", "fr" ], "type": "string", "description": "Glassdoor regional domain to search on.", "default": "us" }, "maxJobs": { "title": "Max jobs", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum jobs per keyword/URL. Glassdoor shows ~30 jobs per page.", "default": 10 }, "fetchDetails": { "title": "Fetch detailed job info", "type": "boolean", "description": "Visit each job detail page for full description + JSON-LD JobPosting (salary, employment type, address). Slower but ~20 extra fields.", "default": true }, "proxyConfiguration": { "title": "Proxy", "type": "object", "description": "Apify proxy. Residential recommended to avoid Glassdoor rate-limiting.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```