# Linkedin Articles Scraper (`scrapers-hub/linkedin-articles-scraper`) Actor 🚀 LinkedIn Articles Scraper extracts key insights from LinkedIn posts & articles—titles, authors, dates, engagement, and more. 📈 Perfect for B2B research, competitive analysis, lead gen, and content strategy. 🔎 - **URL**: https://apify.com/scrapers-hub/linkedin-articles-scraper.md - **Developed by:** [Scrapers Hub](https://apify.com/scrapers-hub) (community) - **Categories:** Lead generation, Social media, News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ### 🚀 LinkedIn Profile Scraper Welcome to the ultimate **LinkedIn Profile Scraper**, a robust and powerful Apify Actor meticulously engineered to navigate, extract, and structure data from one of the most prominent professional networking platforms in the world. In the rapidly evolving landscape of digital intelligence and data-driven decision-making, extracting highly accurate, real-time metadata is an absolute necessity for businesses, marketers, talent acquisition specialists, and business intelligence analysts. Building a reliable data extraction pipeline is simple with the **LinkedIn Profile Scraper**. This cutting-edge tool has been crafted to retrieve public profile details and meticulously extract the myriad of published articles associated with those feeds. When you utilize this software, you acquire an abundance of deep metadata including the exact title, the original publication link, the highly specific publication timestamp, a textual snippet, high-resolution image assets, and vital popularity metrics such as the exact number of reactions and comments generated. #### 🔥 Why Choose the LinkedIn Profile Scraper? The **LinkedIn Profile Scraper** is optimized for reliability and scale. Scraping platforms can be intensely frustrating due to rate limits and IP blocks, but our solution intrinsically bypasses basic blocks by utilizing Apify's Residential Proxies by default. Below is a deep dive into why the **LinkedIn Profile Scraper** is your absolutely best choice among available web automation tools. First and foremost, it automatically pushes extracted articles to a structured dataset immediately as they are acquired. Instead of holding all your scraped information in fragile system memory until the end of a long execution run, the system streams the data dynamically to secure cloud storage. Furthermore, the scale at which this actor performs is unparalleled. By leveraging the immense cloud infrastructure provided by Apify, the software dynamically scales compute resources. It balances the precise timing needed to fetch data authentically, applying intelligent asynchronous requests so that latency overhead is kept to the absolute bare minimum while retaining extremely high fidelity and accuracy in the scraped text fields. #### 🌟 Key Features of the LinkedIn Profile Scraper 1. **Scrape Articles with Unprecedented Accuracy**: The **LinkedIn Profile Scraper** automatically extracts articles associated with a user's feed. It meticulously scans the DOM structure and internal JSON payloads to capture every publicly accessible snippet. 2. **Deep Content Extraction**: We retrieve the full article title, canonical URL link, granular publication date, descriptive text arrays, embedded graphical image URL, and critical engagement indicators. 3. **Real-Time Data Output**: Our **LinkedIn Profile Scraper** pushes each gracefully collected record directly to the Apify dataset, ensuring your database fields are saved in absolute real-time. 4. **Auto Proxy IP Rotation & Routing**: Defaults strictly to fully rotating Residential IPs to ensure staggeringly high success rates and drastically minimized firewall interruptions. 5. **Robust Error Handling Ecosystem**: The internal architecture features smart retry functionality, exponential time backoff, and graceful error degradation under heavy load. #### 💼 Comprehensive Use Cases for the LinkedIn Profile Scraper Many businesses rely on the **LinkedIn Profile Scraper** for overarching competitor analysis. When investigating competing enterprises, it is profoundly insightful to scrape the feeds of their C-suite executives and key thought leaders. By doing so, you can assess the exact cadence and performance (reactions and comments) of their published content. For modern talent sourcing, the **LinkedIn Profile Scraper** allows recruiters to deeply analyze a candidate's footprint. Evaluating the articles published by a potential high-level executive hire via their engagement metrics can reveal their true thought-leadership status within a given niche. It paints a picture far more complex and accurate than a traditional resume. Forward-thinking content marketers use the **LinkedIn Profile Scraper** to evaluate what kind of thought leadership resonates. By scraping top influencers, marketing departments compile massive databases of semantic trends guaranteeing exceptional engagement outcomes. #### ⚙️ Apify Integrations: Make, Zapier, and API for the LinkedIn Profile Scraper You can seamlessly integrate the **LinkedIn Profile Scraper** with prominent workflow automation platforms such as n8n, Make, and Zapier. The magic of Apify lies in its ability to generate seamless webhooks. You can effortlessly configure a scenario where completing a run triggers a Zapier webhook, seamlessly funnelling the results into a Slack channel, Google Sheet, Notion database, or Airtable grid natively. Furthermore, executing the **LinkedIn Profile Scraper** via Apify's API allows developers to operate this entire infrastructure programmatically. With a simple HTTP POST request using your Apify API Token, your internal network microservices can securely launch a scraping payload session fully asynchronously without manual intervention. #### 🌐 Proxy Configuration for the LinkedIn Profile Scraper The **LinkedIn Profile Scraper** requires strong proxies, and therefore, it explicitly relies upon Apify's specialized Residential Proxy network. A residential IP address represents a genuinely authentic physical device connected to a conventional home internet service provider, virtually guaranteeing frictionless access. Configuring the **LinkedIn Profile Scraper** input is incredibly intuitive. ##### Input Keys Explanation: - `startUrls` (Array): An exhaustive list containing targeted URLs to monitor. - `proxyConfiguration` (Object): The paramount settings object detailing how the environment safely routes entirely automated traffic, forced automatically into `"RESIDENTIAL"` networks. **JSON Payload Example:** ```json { "startUrls": [ { "url": "https://www.linkedin.com/in/williamhgates" } ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } } ```` #### 📤 Output Delivery and Data Structuring The output dataset yielded by the **LinkedIn Profile Scraper** is comprehensively structured. We deliver exactly what was extracted directly into your output arrays seamlessly without complex transformations. ##### Exact Data Output Example ```json [ { "articles": [ { "title": "Expanding access to health care through AI", "link": "https://www.linkedin.com/pulse/expanding-access-health-care-through-ai-bill-gates-xyqtc", "date": "2026-01-23T01:44:38.000+00:00", "description": "A core principle underlying the Gates Foundation’s work is closing the innovation gap between rich countries and…", "image_url": "https://static.licdn.com/scds/common/u/img/pic/pic_pulse_stock_article_9.jpg", "num_reactions": 4952, "num_comments": 739 }, { "title": "How to get the world back on track and enter a new era of unprecedented progress", "link": "https://www.linkedin.com/pulse/how-get-world-back-track-enter-new-era-unprecedented-progress-gates-wzycc", "date": "2026-01-12T19:21:29.000+00:00", "description": "I have always been an optimist. When I founded Microsoft, I believed a digital revolution powered by great software…", "image_url": "https://static.licdn.com/scds/common/u/img/pic/pic_pulse_stock_article_9.jpg", "num_reactions": 5854, "num_comments": 955 }, { "title": "What the Gates Foundation hopes to accomplish over the next 20 years", "link": "https://www.linkedin.com/pulse/what-gates-foundation-hopes-accomplish-over-next-20-years-bill-gates-y0gic", "date": "2025-12-20T00:05:56.000+00:00", "description": "Over the next twenty years, the foundation will work together with our partners to make as much progress towards our…", "image_url": "https://media.licdn.com/dms/image/v2/D5612AQE-eZUAKTbmyQ/article-cover_image-shrink_720_1280/B56Zs5D6pMKIAI-/0/1766188887129?e=2147483647&v=beta&t=KUFGzvOCeBOeoGDNEwYbpS7AvFn0d-iQN-iKoHtXs9Q", "num_reactions": 4949, "num_comments": 953 }, { "title": "A generation of progress, a choice to make", "link": "https://www.linkedin.com/pulse/generation-progress-choice-make-bill-gates-rwlwc", "date": "2025-12-06T22:43:28.000+00:00", "description": "The death of a child is always a tragedy. But there's something especially devastating about a child dying of a disease…", "image_url": "https://media.licdn.com/dms/image/v2/D5612AQHXKV_XhT0W_A/article-cover_image-shrink_720_1280/B56Zr1w1eSK4AI-/0/1765059814903?e=2147483647&v=beta&t=gKhTu-PogMfQzIvtwIqoJOlm6-05kg63OSE_UosVrrM", "num_reactions": 4712, "num_comments": 713 }, { "title": "These were some of my favorite books from 2025", "link": "https://www.linkedin.com/pulse/were-some-my-favorite-books-from-2025-bill-gates-zjugc", "date": "2025-11-28T23:55:23.000+00:00", "description": "The holidays are almost here. I always love taking advantage of this time of year to catch up on reading, and I know a…", "image_url": "https://media.licdn.com/dms/image/v2/D5612AQF3roSl8yWbbA/article-cover_image-shrink_720_1280/B56ZrM3F4iI4AI-/0/1764373585939?e=2147483647&v=beta&t=Al-RzODRjgjn4Scq2btttevbmTpgMt62T_70X0nkMTA", "num_reactions": 10766, "num_comments": 1269 }, { "title": "Saving lives, cutting emissions, and staying resilient in a warming world", "link": "https://www.linkedin.com/pulse/saving-lives-cutting-emissions-staying-resilient-warming-bill-gates-jstyc", "date": "2025-10-29T02:45:20.000+00:00", "description": "I recently published a long essay about climate change on the Gates Notes. This is the first of four newsletters I’ll…", "image_url": "https://media.licdn.com/dms/image/v2/D5612AQHn1kRpjWsY7A/article-cover_image-shrink_720_1280/B56Zot1D3DG0AM-/0/1761705477503?e=2147483647&v=beta&t=wnrHrl7BgWHpsXAXFEOUbcmFE0tnxibZ-Ze5ESzbKMs", "num_reactions": 5663, "num_comments": 1089 }, { "title": "We’re closer than ever to eradicating polio", "link": "https://www.linkedin.com/pulse/were-closer-than-ever-eradicating-polio-bill-gates-wyhac", "date": "2025-10-18T04:37:30.000+00:00", "description": "..", "image_url": "https://media.licdn.com/dms/image/v2/D5612AQGf_atdnRMYRg/article-cover_image-shrink_720_1280/B56Zn1iMGnI8AI-/0/1760761005312?e=2147483647&v=beta&t=rQguZm9RiGr6y8tr5EmWKB1aOhGJAljEW-3Q1Hy9GqM", "num_reactions": 5800, "num_comments": 747 }, { "title": "Demystifying the science behind fission and fusion", "link": "https://www.linkedin.com/pulse/demystifying-science-behind-fission-fusion-bill-gates-ylhic", "date": "2025-10-11T01:20:32.000+00:00", "description": "I’m lucky to learn firsthand about some of the world’s most cutting-edge technologies. I’ve seen artificial…", "image_url": "https://media.licdn.com/dms/image/v2/D5612AQEIwKPgp_pazw/article-cover_image-shrink_720_1280/B56ZnQf.P7HQAI-/0/1760139666994?e=2147483647&v=beta&t=TaPc5cj2nwdUYcQsuadPxeQ8NLXEaue2UlnQ7_9i4tc", "num_reactions": 5394, "num_comments": 733 }, { "title": "Utah’s hottest new power source is 15,000 feet below the ground", "link": "https://www.linkedin.com/pulse/utahs-hottest-new-power-source-15000-feet-below-ground-bill-gates-otlwc", "date": "2025-09-30T18:41:07.000+00:00", "description": "When my son, Rory, was younger, we used to love visiting power plants together. It was the perfect father-son activity…", "image_url": "https://media.licdn.com/dms/image/v2/D5612AQFW83M4hV0ykA/article-cover_image-shrink_720_1280/B56Zmb4XOZJkAM-/0/1759256868252?e=2147483647&v=beta&t=E7zcm66Ra0AtvLBkz1GLd_J2OMwRrVVCo6bl14_rOeo", "num_reactions": 6003, "num_comments": 670 }, { "title": "Why I’m Still Optimistic About Global Health", "link": "https://www.linkedin.com/pulse/why-im-still-optimistic-global-health-bill-gates-ji9xc", "date": "2025-09-23T20:46:09.000+00:00", "description": "I recently wrote this essay for TIME Magazine about why I'm still optimistic about global health: One of humanity’s…", "image_url": "https://media.licdn.com/dms/image/v2/D5612AQERhpEhGMZuZw/article-cover_image-shrink_720_1280/B56Zl4NGNCH8AI-/0/1758658323770?e=2147483647&v=beta&t=f-k0MlxKJ4paNDtM8eF4Du0j_jBv8pWSGEouwY5dJdU", "num_reactions": 4336, "num_comments": 787 } ], "profile_url": "https://www.linkedin.com/in/williamhgates" } ] ``` #### 💡 Frequently Asked Questions (FAQ) **Q: How fast is this particular web automation platform built for extraction?** A: Performance speed is undeniably rapid. When the target server establishes the secure handshake properly using the encrypted bandwidth streams, traversing the Document Object Model tree structure normally resolves inside absolute fractions of single milliseconds on standard consumer hardware processing limits globally. **Q: Why doesn't this tool simply accept generic datacenter internet pathways safely?** A: Due directly toward overwhelming modern anti-automation security architecture environments, the utilization of static cloud architecture pathways inevitably results in harsh authentication CAPTCHA requests rendering the overall traversal practically impossible. Organic traffic pools solve this conundrum entirely cleanly transparently. **Q: Are there boundaries regarding ethical operations regarding this extraction system codebase infrastructure utility framework generally?** A: Absolutely and unequivocally. Your deployment operates strictly within public boundaries. Only information inherently displayed publicly toward the global interconnected network can technically be registered. Consequently, users bear profound personal accountability and deep organizational liability concerning ultimate downstream distribution channels properly. Adhering toward regulatory laws inherently preserves industry integrity permanently. **Q: What structural database integrations pair seamlessly alongside exported JSON arrays optimally?** A: Modern relational paradigms function correctly; however, leveraging document-oriented schemas like MongoDB, Firebase, dynamic Airtable segments naturally fits nested array groupings optimally preventing convoluted relational decomposition logic operations natively. Similarly, Python Pandas constructs unpack arrays dynamically beautifully. All of this is deeply vital. **Q: Do network timeouts or server outages permanently fracture the sequential logic stack negatively?** A: The ecosystem heavily leans heavily into mathematical retry mechanisms elegantly. By integrating recursive sequential looping behavior dynamically upon encountering abnormal HTTPS degradation symptoms instantly, the sequence gracefully halts, recalibrates, alters proxy pathways invisibly, and continuously resumes safely automatically preserving total execution momentum robustly continually. Everything happens safely natively quietly underneath cleanly invisibly totally preventing systemic failure definitively. *** Thank you for exploring our vast automation solutions designed meticulously specifically empowering modern enterprise intelligence profoundly. We enthusiastically appreciate your immense technical curiosity significantly. We hope our profound insights provide incredible exponential value globally universally completely. # Actor input Schema ## `url` (type: `string`): Enter the LinkedIn profile URL to scrape articles from. ## Actor input object example ```json { "url": "https://www.linkedin.com/in/williamhgates" } ``` # 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 = { "url": "https://www.linkedin.com/in/williamhgates" }; // Run the Actor and wait for it to finish const run = await client.actor("scrapers-hub/linkedin-articles-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 = { "url": "https://www.linkedin.com/in/williamhgates" } # Run the Actor and wait for it to finish run = client.actor("scrapers-hub/linkedin-articles-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 '{ "url": "https://www.linkedin.com/in/williamhgates" }' | apify call scrapers-hub/linkedin-articles-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapers-hub/linkedin-articles-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Linkedin Articles Scraper", "description": "🚀 LinkedIn Articles Scraper extracts key insights from LinkedIn posts & articles—titles, authors, dates, engagement, and more. 📈 Perfect for B2B research, competitive analysis, lead gen, and content strategy. 🔎", "version": "0.1", "x-build-id": "vANRR4BPa6fRQ7Si0" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapers-hub~linkedin-articles-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapers-hub-linkedin-articles-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapers-hub~linkedin-articles-scraper/runs": { "post": { "operationId": "runs-sync-scrapers-hub-linkedin-articles-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapers-hub~linkedin-articles-scraper/run-sync": { "post": { "operationId": "run-sync-scrapers-hub-linkedin-articles-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "url" ], "properties": { "url": { "title": "Url to check", "type": "string", "description": "Enter the LinkedIn profile URL to scrape articles from." } } }, "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 } } } } } } } } } } ```