Pricing

Pay per usage

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Monitoring

Try for free

Developed by

Apify

This actor monitors your actors' statuses, validates their datasets' data, and displays useful information in an interactive dashboard. And if something happens, you'll get notified via email or Slack.

4.4 (5)

Pricing

Pay per usage

Monthly users

Runs succeeded

75%

Last modified

10 months ago

Automation

You can access the Monitoring programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1echo '{
2  "dashboardStatisticsFrequency": "Every day at noon",
3  "validationCheckOptions": "/* global ow */\\n// The `ow` variable represents the ow validation variable. More at https://sindresorhus.com/ow/index.html\\n [\\n    {\\n        filter: \\"us\\", // matches all targets with \\"us\\" pattern\\n        minItemCount: 5000,\\n        schema: {\\n            url: ow.string.url,\\n            description: ow.string,\\n        },\\n    },\\n    {\\n        Ids: [\\"A1b2C3d4\\", \\"B1A2d45\\"], // matches 2 targets with specific IDs\\n        schema: {\\n            itemId: ow.number,\\n            region: ow.string,\\n        },\\n    },\\n]",
4  "validationCheckFrequency": "Per run",
5  "duplicationCheckFrequency": "Per run"
6}' |
7apify call apify/monitoring --silent --output-dataset

Monitoring API through CLI

The Apify CLI is the official tool that allows you to use Monitoring locally, providing convenience functions and automatic retries on errors.

Install the Apify CLI

1npm i -g apify-cli
2apify login

Other API clients include:

Monitoring API in Python

Monitoring API in JavaScript

Monitoring OpenAPI definition

Monitoring API

Pricing

Pricing model

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage.

Send Email

apify/send-mail

The actor automatically sends an email to a specific address. This actor is useful for notifications and reporting. With only 3 lines of JavaScript code, you'll be on top of your scraping actors and never miss important results or issues.

Apify

2.8k

Monitoring Reporter Dashboard

apify/monitoring-reporter-dashboard

The monitoring reporter dashboard is a part of the Apify Monitoring Suite (apify/monitoring). See its readme for more information and how to use this.

Apify

Slack Message Generator

katerinahronik/slack-message

This actor sends messages to Slack automatically. It can be used instead of email notifications and is ideal to combine with other actors monitoring successful runs, errors, etc.

Kateřina Hroníková

112

Monitoring Reporter Slack

apify/monitoring-reporter-slack

The Monitoring reporter slack is a part of the Apify Monitoring Suite (apify/monitoring). See its readme for more information and how to use this.

Apify

Validate Dataset(s) with JSON Schema

jaroslavhejlek/validate-dataset-with-json-schema

This Actor validates items in one or more datasets against a provided JSON Schema. Use it if you planning to add a dataset validation schema to your actor and you want test it.

Jaroslav Hejlek

vncz-test-actor

vnczes/vncz-test-actor

Something

Vincenzo Chianese

Status Page

jannovotny/status-page

Show charts with daily counts of your datasets. Useful for monitoring periodical scrapes.

Jan Novotný

Apify Actors

prog-party/apify-actors

This Apify Actors Actor retrieves data from Apify, allowing to filter, and returns a list of actors as a Dataset.

Prog Party

Slack Messages Downloader

zuzka/slack-messages-downloader

Download up to 1,000 Slack messages from a public channel of your choice. Extract message text, image URL, timestamp, reply count, user ID, reply user IDs, and more. Export Slack data in JSON, CSV, and Excel and use it for archives, backups, and automated reports.

Zuzka Pelechová

LLM Dataset Processor

dusan.vystrcil/llm-dataset-processor

Allows you to process output of other actors or stored dataset with single LLM prompt. It's useful if you need to enrich data, summarize content, extract specific information, or manipulate data in a structured way using AI.