How to Mount an SMB Share in Linux

Symlinks, also known as symbolic links, are like shortcuts in the Linux world. They allow you to create a new name (or link) that points to another file, directory, or any object within the file system. Their primary advantage lies in reducing redundancy by avoiding the need for multiple copies of the same file. When you have a symlink, changes made to the original file reflect across all its symbolic links. This eliminates the hassle of updating numerous copies individually. Additionally, symlinks offer a flexible way to manage access permissions. For instance, different users with directories pointing to subsets of files can limit visibility beyond what standard file system permissions allow. In essence, symlinks are indispensable for efficient file management and organization, streamlining updates and access control in complex systems. Prerequisites To follow this tutorial, you will need: A cloud server, virtual machine or computer running a Linux operating system. On Hostman, you can deploy a server with Ubuntu, CentOS or Debian in under a minute. Creating Symbolic Links with the ln Command The ln command is used to create symbolic links in Linux. Follow these steps: Open a terminal window. Navigate to the directory where you want to create the symbolic link. Use the following command syntax to create a symlink: ln -s /path/to/source /path/to/symlink Replace /path/to/source with the actual path of the file or directory you want to link, and /path/to/symlink with the desired name/location of the symlink. Understanding the ln Command Options The ln command offers various options to customize symlink creation:  -s: Creates a symbolic link.  -f: Overwrites an existing symlink.  -n: Treats symlink targets as normal files. Explore these options based on your linking needs. Creating Symbolic Links to Files To create a symlink to a file, use the ln command with the -s option. Here's an example of how you can create a symbolic link to a file using the ln command. The command below creates a symbolic link named symlink_file in the current directory, pointing to the file /path/to/file: ln -s /path/to/file /path/to/symlink_file Replace /path/to/file with the actual file path and /path/to/symlink_file with the desired symlink name. In this example, the file path is absolute. You can also create a symbolic link with a relative path. However, keep in mind that for the symlink to work correctly, anything accessing it must first set the correct working directory, or the link may appear broken. Creating Symbolic Links to Directories You can use the ln command to create a symbolic link that points to a directory. For instance, the command below creates a symbolic link called symlink_directory in the current directory, which points to the directory /path/to/directory: ln -s /path/to/directory /path/to/symlink_directory This command creates a symbolic link named symlink_directory in your current location, linking it to the /path/to/directory directory. Forcefully overwrite a symbolic link You can use the -f flag with the ln command. For example, if the path in a symlink is incorrect due to a typo or if the target has moved, you can update the link like this: ln -sf /path/to/new-reference-dir symlink_directory Using the -f flag ensures that the old symlink's contents are replaced with the new target. It also automatically removes any conflicting files or symlinks if there's a conflict. If you attempt to create a symlink without the -f flag and the symlink name is already in use, the command will fail. Verifying Symbolic Links You can display the contents of a symlink using the ls -l command in Linux: ls -l symlink_directory The output will show the symlink and its target: symlink_file -> /path/to/reference_file Here, symlink_file is the name of the symlink, and it points to the file /path/to/reference_file. ls -l /path/to/symlink The output will show the symlink and its target. Symbolic Link Best Practices Use descriptive names for symbolic links. Avoid circular links to prevent system confusion. Update symlinks if the target's location changes. Use Cases for Symbolic Links Managing Configuration Files: Linking configuration files across systems. Version Control: Symbolic linking common libraries for development projects. Data Backup: Creating symbolic links to backup directories. Potential Pitfalls and Troubleshooting Permission Issues: Ensure proper permissions for source and symlink. Broken Links: Update symlinks if target files are moved or deleted. Cross-Filesystem Links: Symlinks may not work across different filesystems. Conclusion Symlinks are valuable for streamlining file management and system upkeep. They simplify updates across multiple applications sharing a common file, reducing maintenance complexity. They also offer an alternative to directories like /etc, often requiring root access for file modifications. Developers find symlinks useful for transitioning between local testing files and production versions seamlessly. By following this tutorial, you've mastered the art of creating symbolic links in Linux. Leverage symlinks for efficient file management and customization. By the way, with Hostman, you can run your workloads on efficient NL VPS that support low latency for EU-based users. Check this out, we have plenty of budget VPS hosting options for your projects. Frequently Asked Questions (FAQ) How do you create a symbolic link in Linux?  Use the ln command with the -s flag. The syntax is ln -s [path_to_target] [path_to_link]. For example: ln -s /var/www/html/mysite ~/mysite-shortcut. What is an example of a symlink?  A desktop shortcut is the most common example. It is a small file that points to a program or document stored elsewhere on your drive, allowing you to open it without moving the original file. How do I find symbolic links in Ubuntu?  To see links in your current directory, run ls -la and look for files marked with an l permission (e.g., lrwxrwxrwx). To search for all symlinks in a directory and its subfolders, use find . -type l. How do I remove a symbolic link?  You can remove a symlink just like a regular file using rm [link_name] or unlink [link_name]. This deletes the link but leaves the original file untouched. What is the difference between a hard link and a symbolic (soft) link?  A symbolic link points to the location of a file (like a shortcut). If the original file is deleted, the link breaks. A hard link points to the actual data on the disk; even if you delete the original file name, the data remains accessible through the hard link.

Keyboard shortcuts in Linux are a great tool that can help you work more efficiently. Instead of using the mouse and navigating the menus, you can often press a couple of buttons to get you to the same result much quicker. Linux operating systems support a wide range of these shortcuts, or hotkeys. It’s important to note that each OS can have specific hotkeys that might not work in other distributions. However, you can fix that as users can add new or modify existing combinations in their system settings. Choose your server now! In this article, we will cover universal key combinations that are universal across different desktop environments. Most of the Linux hotkeys we examine are focused on working with the terminal. The commands in this article sometimes use the Super key, which corresponds to the Windows key in Windows OS or the Cmd key in macOS. For example, the shortcut to switch keyboard layouts Super + Space in Linux is similar to Windows + Space or Cmd + Space. Basic Linux Shortcuts Let’s start with basic general-purpose shortcuts. They help perform repetitive tasks more quickly. Alt + Tab or Super + Tab: Switches between windows. Similar to the function in Windows and other OSes. Super + Space: Switches between multiple keyboard layouts. Super + A: Opens the applications menu (usually located in the bottom left corner). F2: Used to rename files. Navigate to the file, click it once, then press F2 to rename. Ctrl + Alt + T: One of the most important and popular Linux shortcuts that opens the terminal window. Alt + F2: Opens a command prompt window in the center of the screen, where you can run a command or open a program. Super + D: Minimizes all windows to show the desktop. Ctrl + Alt + Del: Brings up a prompt with “Cancel” and “Log Out” options. The system logs out automatically if no selection is made within 60 seconds. These combinations help any specialist work more efficiently in Linux. But let’s move on to the more useful terminal-related hotkeys. Linux Terminal Shortcuts The terminal in Linux is the primary tool for interacting with the command shell. Below are terminal hotkeys that will help you work more efficiently. Terminal Window Management These shortcuts help open, switch, and close terminal tabs and windows quickly: Ctrl + Shift + Q: Completely closes the terminal window. Ctrl + Shift + T: Opens a new terminal tab. Ctrl + Shift + W: Closes the current terminal tab (or window if only one tab is open). Ctrl + Shift + D: Detaches the terminal tab into a separate window. Ctrl + PgUp / PgDown: Switches between terminal tabs (previous/next). Cursor Movement in a Line Linux users primarily use the keyboard in the terminal. To avoid switching to the mouse, here are some shortcuts for faster cursor navigation: Ctrl + A (or Home): Moves the cursor to the beginning of the line. Ctrl + E (or End): Moves the cursor to the end of the line. Ctrl + XX: Quickly moves the cursor to the beginning of the line; using it again returns it to the original position. Ctrl + → / ← or Alt + F / B: The first pair moves the cursor one word forward or backward. The second pair does the same using the Alt key. Input and Editing In addition to quickly moving the cursor along the line, you can also simplify input and editing of commands.  TAB: One of the main hotkeys in the Linux terminal, used for auto-completing commands or file paths. Pressing once completes the command; pressing twice suggests multiple completion options if available. Ctrl + T: Swaps the last two characters before the cursor. Alt + T: Similar to the previous shortcut but swaps the last two words before the cursor. Alt + Backspace: Deletes the word before the cursor. Alt + D: Deletes all characters after the cursor up to the next space. Alt + U / Alt + L: The first changes all characters to the right of the cursor to uppercase; the second to lowercase. Clipboard Operations These shortcuts allow interaction with the clipboard in the terminal: copying, cutting, or pasting parts of a line or the entire line. Ctrl + W: Deletes the word before the cursor. Ctrl + U: Deletes everything from the cursor to the beginning of the line. Ctrl + K: Deletes everything from the cursor to the end of the line. Ctrl + Y: Pastes the last deleted text from the clipboard using one of the three commands above. Command History Navigation Hotkeys also help interact with the command history in the terminal. This is useful when searching for previously used commands. To view the list of executed commands, use: history To quickly find and execute a previously used command, use the shortcuts below: Ctrl + R: Opens a search prompt to find a previously used command. Press Enter to run it, or Esc to edit or exit. Ctrl + O: Executes the command found using the shortcut above. Alt + <: Loads the first command from the command history. Screen Output Management The following shortcuts control the amount of information displayed in the terminal window and help focus on specific data even during a running process. Ctrl + C: Sends the SIGINT signal to the active process, immediately interrupting it. Ctrl + D: An alternative to exit, used to close the terminal. Often used in SSH sessions to disconnect from a remote host. Ctrl + Z: Suspends the active process and sends it to the background. Use the fg command to bring it back. Use jobs to list background processes. Ctrl + L: An alternative to the clear command, clears the terminal screen. Ctrl + S / Ctrl + Q: Ctrl + S pauses the terminal output; Ctrl + Q resumes it. Useful for stopping the screen output temporarily to examine or copy information. Adding and Modifying Hotkeys A Linux user may find that some combinations do not work or are missing entirely. Hotkeys may differ depending on the distribution as each system includes a default list of predefined shortcuts. However, in most Linux environments, users can create new shortcuts or modify existing ones.  Use Super + A to open the application menu. Use the search bar to find and open Settings. In the opened window, find and go to the Devices tab. Go to the Keyboard section. On the right side, a list of default hotkeys will appear. Click on any command to open the editing window and assign a new shortcut. If the desired command is not listed, you can add a custom one by clicking the + at the bottom. Enter its name, the command to execute, and the key combination. Choose your server now! Conclusion This article reviewed the main Linux hotkeys that simplify and speed up user workflow. It’s important to note that this is not a complete list. In addition to those listed, there are other combinations that cover different functionalities in Linux distributions. And if you’re looking for a reliable, high-performance, and budget-friendly solution for your workflows, Hostman has you covered with Linux VPS Hosting options, including Debian VPS, Ubuntu VPS, and VPS CentOS. Frequently Asked Questions (FAQ) What are the common shortcut keys for Linux?  While they vary by desktop environment (GNOME, KDE, etc.), standard global shortcuts include: Ctrl+Alt+T: Open a new Terminal window. Alt+Tab: Switch between open applications. Super Key (Windows Key): Open the Activities overview or Application menu. Alt+F4: Close the current window. What are the Linux shortcut keys for the terminal?  Terminal shortcuts differ from standard text editors. Key commands include: Ctrl+Shift+C / V: Copy and Paste text (standard Ctrl+C/V won't work). Ctrl+C: Interrupt (kill) the currently running process. Ctrl+L: Clear the terminal screen. Ctrl+A / Ctrl+E: Jump the cursor to the start or end of the line. How to set keyboard shortcuts in Linux?  Open your system Settings and select Keyboard. Scroll to the "Keyboard Shortcuts" section (sometimes under "View and Customize Shortcuts"). Here you can modify existing keys or add a custom shortcut by defining a command and pressing the desired key combination. How to use shortcuts on Linux?  Simply press the modifier keys (like Ctrl, Alt, or Super) and the action key simultaneously. Note that Linux shortcuts are case-sensitive regarding the Shift key; for example, Ctrl+c is different from Ctrl+Shift+C.

If you’ve ever exported data from websites manually, you know how tedious it can be: you have to open the site and many links, then go through each one, copy the data, and paste it into a spreadsheet. And if there’s a lot of data, the process turns into endless routine work. The good news is that this can be automated, and you don’t need programming skills to do it. Once you set up the scenario, everything will run automatically: the n8n platform will collect the data, save it to a database, and send it further if necessary. In this article, we’ll look at how to set up such a process with minimal effort. We’ll create a chain that: retrieves a list of articles, saves the data to PostgreSQL, collects the full text of each publication, stores everything in the database. All this doesn’t require any special skills, just a basic understanding of how the terminal and web panel work. You can figure it out even if you’ve never heard of n8n before. Next, we’ll break down the process step by step, from starting the server to building the working process. By the end, you’ll have a workflow that saves you hours and handles routine tasks automatically. Overview Let’s say you need to collect the texts of all articles in the “Tutorials” section. To complete the task, we’ll break it down into a sequence of steps, also known as a pipeline. What needs to be done? Collect the titles of all articles in the catalog along with their links. The site provides the data page by page; you can’t get all the links at once, so you need to collect them in a loop. Within the loop, save the collected links to the database. If there are many links, it’s most reliable to store intermediate data in a database. After the loop, extract the links from the database and start a new loop. By this stage, we’ll have a table with links to articles. Now we need to process each link and extract the text. Save the article texts. In the new loop, we’ll store the data in a new table in the database. What will we use? To implement the project, we’ll use ready-made cloud services. With Hostman, you can quickly deploy: a cloud server on Linux, a cloud PostgreSQL database. Step 1. Create a Server and Install n8n Go to the control panel and open the Cloud servers section in the left panel. Click Create server. Choose the appropriate location and configuration. When selecting a configuration, keep in mind that n8n itself is very lightweight. The main load falls on memory (RAM). It’s used to handle multiple simultaneous tasks and store large logs/history. Additional CPU cores help with complex chains with many transformations or a large number of concurrent executions. Below is a comparative table to help you choose the right configuration: Configuration Characteristics Best For 1 × 3.3 GHz, 2 GB, 40 GB Low Test scenarios, 1–2 simple workflows without large loops or attachment handling. 2 × 3.3 GHz, 2 GB, 60 GB Optimal for most tasks Small automations: data exports, API operations, database saves, periodic jobs. Good starting tier. 2 × 3.3 GHz, 4 GB, 80 GB Universal option Moderate load: dozens of active workflows, loops over hundreds of items, JSON handling and parsing. Good memory margin. 4 × 3.3 GHz, 8 GB, 160 GB For production and large scenarios High load: constant cron triggers, processing large data sets, integrations with multiple services. 8 × 3.3 GHz, 16 GB, 320 GB Overkill for n8n Suitable if you plan to run additional containers (e.g., message queue, custom API). Usually excessive for n8n alone. In section Network keep the public IPv4 address enabled; this ensures the server is accessible from any network. Add a private network for connecting to the database; you can use the default settings. Adjust other parameters as needed. Click Order. Server creation and setup take about 10 minutes. After that, install n8n on it following the official documentation. Step 2. Create a PostgreSQL Database Once the n8n server is up and running, you need to prepare a place to store your data. For this, we’ll use a cloud PostgreSQL database (DBaaS). This is more convenient and practical than deploying it yourself: you don’t have to install and maintain hardware, configure software, or manage complex storage systems.  Go to the control panel, click on the Databases tab in the left panel, then click Create Database. In section Database Type, choose PostgreSQL. In section 4. Network, you can disable the public IPv4 address; the connection to the database will occur through the private network. This is not only safer but also more cost-effective. Click Order. The database will be ready in about 5 minutes. Step 3. Learn the Basics of n8n It’s easy to get familiar with n8n, and you’ll quickly see that for yourself. In this step, we’ll look at n8n’s main elements, what they do, and when to use them. What Nodes Are and Why They’re Needed In n8n, every automation is built from nodes—blocks that perform one specific task. Node Type Function Trigger Starts a workflow based on an event: by time (Schedule), webhook, or service change. Action Sends a request or performs an operation: HTTP Request, email sending, database write. Logic Controls flow: If, Switch, Merge, Split In Batches. Function / Code Allows you to insert JS code (Function, Code) or quick expressions. Any scenario can be built using these node types. How to Create Nodes Click “+” in the top-right corner of the workspace or on the output arrow of another node. Type the node name in the search, for example: http or postgresql. Click it. The node will appear and open its settings panel. Fill in the required fields: URL, method, and credentials. Fields with a red border are mandatory. Click Execute Node. You’ll see a green checkmark and an OUTPUT section with data. This is a quick way to verify the node works correctly. Other Useful Features in n8n Feature Where to Find Purpose Credentials Main page (Overview) → Credentials tab Stores logins/tokens; set once, use in any node. Variables Any input field supports expressions {{ ... }} Use for dynamic dates, counters, or referencing data from previous nodes. Executions Main page (Overview) → Executions tab Logs of all runs: see input/output data, errors, execution time. Workflow History Enabled via advanced features; button in top panel on Workflow page Similar to Git: revert to any previous scenario version. Folders Main screen; click the folder-with-plus icon near sorting and search Keeps workflows organized if you have many. Templates Templates tab on the left of the Workflow screen, or via link Ready-made recipes: connect Airtable, Slack bot, RSS parsing, etc. Step 4. Build a Workflow in n8n Now we have everything we need: a server with n8n and a PostgreSQL database. We can start building the pipeline. On the main screen, click Create workflow. This will open the workspace. To start the pipeline, you need a trigger. For testing, use Trigger manually: it allows you to launch the process with a single button click. After testing, you can switch to another trigger, such as scheduling data export once a day. n8n window after creating a workflow: choosing a trigger for manual or scheduled start. Screenshot by the author  / n8n.io We’ll create a universal pipeline. It will go through websites, extract links page by page, then go through all of them and extract data. However, since every website is structured differently and uses different technologies, there’s no guarantee that this setup will work everywhere without adjustments. Get the Request from the Browser Click “+” next to the trigger. The action selection panel will open. In the search field, type http and select HTTP Request. Selecting the next step in n8n: adding the “HTTP Request” node for sending requests to a website. Screenshot by the author / n8n.io A panel will open to configure the parameters. But you can simply import the required data from your browser; that way, you don’t have to dive into the details of HTTP requests. Now you need to understand how exactly the browser gets the data that it displays on the page. Usually, this happens in one of two ways: The server responds with a ready-made HTML page containing the data. The server responds with a JSON dictionary. Open in your browser the page you want to get data from. For example, we’ll use the Tutorials page. Then open the Developer Tools (DevTools) by pressing F12 and go to the Network tab. On our example site, there’s a See more button. When clicked, the browser sends a request to the server and receives a response. When a user clicks a button to view details, usually a single request is sent, which immediately returns the necessary information. Let’s study the response. Click the newly appeared request and go to the Response tab. Indeed, there you’ll find all the article information, including the link. If you’re following this example, look for a GET request starting with: https://content.hostman.com/items/tutorials?... That’s the one returning the list of publications. Yours might differ if you’re analyzing another site. On the Headers tab, you can study the structure of the response to understand how it’s built. You’ll see that parameters are passed to the server: limit and offset. limit restricts the number of articles returned per request (6 in our case). offset shifts the starting point. offset = 6 makes sense because the first 6 articles are already displayed initially, so the browser doesn’t need to fetch them again. To fetch articles from other pages, we’ll shift the offset parameter with each request and accumulate the data. Copy the command in cURL format: it contains all the request details. Right-click the request in the web inspector → Copy value → Copy as cURL. An example command might look like this: curl 'https://content.hostman.com/items/tutorials?limit=6&offset=6&fields[]=path&fields[]=title&fields[]=image&fields[]=date_created&fields[]=topics&fields[]=text&fields[]=locale&fields[]=author.name&fields[]=author.path&fields[]=author.avatar&fields[]=author.details&fields[]=author.bio&fields[]=author.email&fields[]=author.link_twitch&fields[]=author.link_facebook&fields[]=author.link_linkedin&fields[]=author.link_github&fields[]=author.link_twitter&fields[]=author.link_youtube&fields[]=author.link_reddit&fields[]=author.tags&fields[]=topics.tutorials_topics_id.name&fields[]=topics.tutorials_topics_id.path&meta=filter_count&filter=%7B%22_and%22%3A%5B%7B%22status%22%3A%7B%22_eq%22%3A%22published%22%7D%7D%2C%7B%22_or%22%3A%5B%7B%22publish_after%22%3A%7B%22_null%22%3A%22true%22%7D%7D%2C%7B%22publish_after%22%3A%7B%22_lte%22%3A%22$NOW(%2B3+hours)%22%7D%7D%5D%7D%2C%7B%22locale%22%3A%7B%22_eq%22%3A%22en%22%7D%7D%5D%7D&sort=-date_created' \ -H 'sec-ch-ua-platform: "Windows"' \ -H 'Referer: https://hostman.com/' \ -H 'User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/141.0.0.0 Safari/537.36' \ -H 'Accept: application/json, text/plain, */*' \ -H 'sec-ch-ua: "Google Chrome";v="141", "Not?A_Brand";v="8", "Chromium";v="141"' \ -H 'sec-ch-ua-mobile: ?0' Now go back to n8n. Click Import cURL and paste the copied value. Important: if you copy the command from Firefox, the URL might contain extra ^ symbols that can break the request. To remove them: Method 1. In n8n: After import, click the gear icon next to the URL field. Choose Add Expression. The URL becomes editable. Press Ctrl + F (Cmd + F on macOS), enable Replace mode, type ^ in the search field, leave the replacement field empty, and click Replace All. Method 2. In VSCode: Paste the cURL command into a new .txt or .sh file. Press Ctrl + H (Cmd + H on macOS). In Find, enter ^, leave Replace with empty, and click Replace All. Copy the cleaned command back into n8n. Click Import, then Execute step. After a short delay, you should see the data fetched from the site in the right-hand window. Now you know how to retrieve data from a website via n8n. Add a Cyclical Algorithm Let’s recall the goal: we need to loop through all pages and store the data in a database. To do that, we’ll build the following pipeline: Add a manual trigger: Trigger manually. It starts the workflow when you click the start button. Connect all nodes sequentially to it. In the first node, set values for limit and offset. If they exist in the input, leave them as is. Otherwise, default limit = 100 and offset = 0 (for pagination).Add a Edit Fields node → click Add Field. In the “name” field: limit In the “value” field:{{ $json.limit !== undefined ? $json.limit : 100 }} Add another field: “name”: offset “value”:{{ $json.offset !== undefined ? $json.offset : 0 }} Both expressions dynamically assign values. If this is the first loop run, it sets the default value; otherwise, it receives the updated variable.Set both to Number type and enable Include Other Input Fields so the loop can pass values forward. In the HTTP Request node, the API call uses the limit and offset values. The server returns an array under the key data. Set the URL field to Expression, inserting the previous node’s variables: {{ $json.limit }} and {{ $json.offset }}. Next, an If node checks if the returned data array is empty. If empty → stop the loop. If not → continue.Condition: {{ $json.data }} (1); Array (2) → is empty (3). Under the false branch, add a Split Out node. It splits the data array into separate items for individual database writes. Add an Insert or update rows in a table (PostgreSQL) node. Create credentials by clicking + Create new credential.Use Hostman’s database details: Host: “Private IP” field Database: default_db User / Password: “User login” and “Password” fields Example SQL for creating the table (run once via n8n’s “Execute a SQL query” node): CREATE TABLE tutorials ( id SERIAL PRIMARY KEY, author_name TEXT, topic_name TEXT UNIQUE, topic_path TEXT, text TEXT );  This prepares the table to store article data. Each item writes to tutorials with fields topic_name, author_name, and topic_path. The Merge node combines: Database write results Old limit and offset values Since the PostgreSQL node doesn’t return output, include it in Merge just to synchronize: the next node starts only after writing completes. The next Edit Fields node increases offset by limit (offset = offset + limit).This prepares for the next API call—fetching the next page. Connect this last Edit Fields node back to the initial Edit Fields node, forming a loop. The workflow repeats until the server returns an empty data array, which the If node detects to stop the cycle. Add a Second Loop to Extract Article Texts In our setup, when the If node’s true branch triggers (data is fully collected), we need to fetch all article links from the database and process each one. Second loop in n8n: fetching links from DB and saving article text to a table. Screenshot by the author / n8n.io Here, each iteration requests one article and saves its text to the database. Add Select rows from a table (PostgreSQL): it retrieves the rows added earlier. Since n8n doesn’t have intermediate data storage, the database serves this role. Use SELECT operation and enable Return All to fetch all rows without limits. This node returns all articles at once, but we need to handle each separately. Add a Loop over items node. It has two outputs: loop: connects nodes that should repeat per item, done: connects what should run after the loop ends. Inside the loop, add a request node to fetch each article’s content. Use DevTools again to find the correct JSON or HTML request. In this case, the needed request corresponds to the article’s page URL.Note: this request appears only when you navigate to an article from the Tutorials section. Refreshing inside the article gives HTML instead.To learn how to extract data from HTML, check n8n’s documentation. In the request node, insert the article path from the database (convert URL field to Expression). Finally, add an Update rows in a table node to store the article text from the previous node’s output. At this point, the loop is complete. You can test your setup. Step 5. Schedule Workflow Execution To avoid running the workflow manually every time, you can set up automatic execution on a schedule. This is useful when you need to refresh your database regularly, for example, once a day or once an hour. n8n handles this through a special node called Schedule Trigger. Add it to your pipeline instead of Trigger manually. In its settings, you can specify the time interval for triggering, starting from one second. Configuring the Schedule Trigger node in n8n for automatic workflow execution. Screenshot by the author / n8n.io That’s it. The entire pipeline is now complete. To make the Schedule Trigger work, activate your workflow: toggle the Inactive switch at the top-right of the screen. Screenshot by the author / n8n.io With the collected data, you can, for example, automate customer support so a bot can automatically search for answers in your knowledge base. Common Errors Overview The table below lists common issues, their symptoms, and solutions. Symptom Cause (Error) Working Solution When switching the webhook from “Test” to “Prod,” the workflow fails with “The workflow has issues and cannot be executed.” Validation failed in one of the nodes (a required field is empty, outdated credentials, etc.) Open the workflow, fix nodes marked with a red triangle (fill in missing fields, update credentials), then reactivate. PostgreSQL node returns “Connection refused.” The database service is unreachable: firewall closed, wrong port/host, or no Docker network permission. If DB runs in Docker: check that it listens on port 5432, its IP is whitelisted, and n8n runs in the same network; add network_mode: bridge or a private network. If using Hostman DBaaS, check that the database and n8n host are on the same private network and ensure the DB is active. Node fails with “Cannot read properties of undefined.” A script/node tries to access a field that doesn’t exist in the incoming JSON. Before accessing the field, use an IF node or {{ $json?.field ?? '' }}; make sure the previous node actually outputs the expected field. Execution stops with a log message: “n8n may have run out of memory.” The workflow processes too many elements at once; Split In Batches keeps a large array in RAM. Reduce batch size, add a Wait node, split the workflow, or upgrade your plan for more RAM. Split In Batches crashes or hangs on the last iteration (OOM). Memory leak due to repeated loop cycles. Set the smallest reasonable batch size, add a 200–500 ms Wait, or switch to Queue Mode for large data volumes. Database connection error: pq: SSL is not enabled on the server. The client attempts SSL while the server doesn’t support it. Add sslmode=disable to the connection string. Conclusion Automating data export through n8n isn’t about complex code or endless scripting; it’s about setting up a workflow once and letting it collect and store data automatically. We’ve gone through the full process: Created a server with n8n without manual terminal setup, Deployed a cloud PostgreSQL database, Built a loop that collects links and article texts, Set up scheduled execution so everything runs automatically. All of this runs on ready-made cloud infrastructure. You can easily scale up upgrading plans as your workload grows, connect new services, and enhance your workflow. This example demonstrates one of the most common n8n patterns: Iterate through a website’s pages and gather all links, Fetch data for each link, Write everything to a database. This same approach works perfectly for: Collecting price lists and monitoring competitors, Content archiving, CRM integrations. It’s all up to your imagination. The beauty of n8n is that you can adapt it to any task without writing complex code.We also prepared special VPS with NVMe storage so you can do everything you want with your projects!