How about automatically distributing files to two devices every morning at 7:00 AM?#
INNORIX Platform can automatically initiate file transfers based on various conditions.#
| Schedule conditions | Example |
|---|---|
| Once on a specific date, time | 2026-01-10 03:00, Windows 100 → Debian server emergency patch |
| Once on a specific date, time | 2026-01-15 21:00, Ubuntu 500 → AWS S3 Glacier monthly backup |
| Once on a specific date, time | 2026-02-01 00:30, CentOS 800 → RHEL key log collection |
| Once on a specific date, time | 2026-03-05 18:00, macOS 60 → Windows central server data snapshot |
| Once on a specific date, time | 2026-04-22 05:00, Rocky 120 → Ubuntu 40 image model synchronization |
| Once on a specific date, time | 2026-04-01 11:00, Debian 200 → AWS S3 disaster recovery image upload |
| Repeat every hour | macOS 80 → RHEL server log collection every hour |
| Repeat every hour | Windows 600 → AWS S3 monitoring data upload every hour |
| Repeat every hour | Ubuntu every hour 1,000 units → Debian analysis server operation logs forwarded |
| Repeat every hour | 150 Fedora units → CentOS central server telemetry collected every hour |
| Repeat every hour | 300 Rocky units → RHEL operating parameters transferred every hour |
| Repeat every hour | 200 CentOS units → 30 Ubuntu units configuration file updates every hour |
| Specific time every day | Daily at 02:00, Debian 250 units → CentOS 3,000 units package synchronization |
| Specific time every day | Daily at 23:30, Fedora 300 units → RHEL server daily report |
| Specific time every day | Daily at 05:00, Windows 700 units → AWS S3 fault report upload |
| Specific time every day | Daily at 04:00, macOS 50 units → Ubuntu 200 units security patch distribution |
| Specific time every day | Daily at 01:15, Ubuntu 2,000 units → Debian server inventory automatic collection |
| Specific time every day | Daily at 06:00, Rocky 100 units → Windows central server diagnostic files transfer |
| Day of the week, time | Every Monday at 09:00, Windows 500 units → 100 Ubuntu units Production files |
| Day of the week, time | Every Friday at 10:00 PM, 1,200 CentOS units → AWS S3 weekly maintenance backup |
| Day of the week, time | Every Wednesday at 3:00 PM, 300 Fedora units → Debian analytics server model training files |
| Specific day of the month, time | Every month at 00:10 AM, 200 macOS units → AWS S3 monthly backup |
| Specific day of the month, time | Every month at 03:00 AM, 80 Rocky units → RHEL report submission |
| Specific day of the month, time | Every month at 02:00 AM, 300 Debian units → Windows server accounting file transfer |
If you need to transfer only files that meet certain criteria, you can easily filter them on the source device.#
Precisely filter source files based on multiple criteria to meet your specific needs.#
| Filter conditions | Example scenario |
|---|---|
| Specific extensions (jpg, png, etc.) | 200 macOS systems → When transferring to AWS S3, only "jpg/png" image files are collected and used for quality inspection. |
| Specific extensions (txt, log only) | 800 Ubuntu systems → Automatically collect only system logs (log/txt) to the Debian analysis server. |
| File names containing specific characters ("daily") | 500 CentOS systems → Back up only "daily" files from the RHEL server. |
| File names containing specific numbers ("2026") | 300 Windows systems → Upload only annual reports containing "2026" to S3. |
| Files without specific characters in their file names | 150 Rocky systems → Transfer only files without "temp" from the Ubuntu central server, excluding temporary files. |
| Files larger than a specific size (> 500MB) | 100 macOS systems → Transfer only large videos over 500MB to S3. |
| Files smaller than a specific size (< 5MB) | 400 Windows systems → Automatically reflect only small configuration files under 5MB to the Debian server. |
| Matches a regular expression condition ("^log_[0-9]{8}") | 1,000 Ubuntu systems → Transfer only files matching the date pattern (e.g., log_20260101) from the RHEL server. |
| Regular expression condition ("report_[A-Z]{3}.csv") | 250 Fedora systems → Transfer only report files containing region codes from 50 CentOS systems. |
| Synchronization: Transfer only new files | Debian After comparing 600 Ubuntu systems to 80 Ubuntu systems, only new files not present in Ubuntu were synchronized. |
| Synchronization: Resend only changed files | 500 Windows systems → Overwrite only files with new timestamps on the RHEL server. |
| Extension exclusion filter (e.g., exclude *.tmp) | 1000 CentOS systems → Upload only the remaining files, excluding *.tmp temporary files from S3. |
| Transfer only files within a specific folder | 300 macOS systems → Transfer only the /data/images/ folder from the Debian central server. |
| Composite filter with a specific file name pattern and size condition | 400 Ubuntu systems → Backup and transfer only "backup_*.tar" files larger than 1GB from the Windows server. |
You can freely configure the storage method or conditions on the target device side, if necessary.#
INNORIX Platform supports a variety of target conditions to optimize file storage.#
| Source → Target | Saving conditions | Description |
|---|---|---|
| Windows01 → Linux01 | Auto numbering | If a file with the same name exists, it is saved as file(1).txt. |
| Windows02 → Linux02 | Auto numbering | Duplicates are handled as image_001(2).jpg. |
| Ubuntu01 → Windows03 | Overwrite | Existing files are immediately replaced with new files. |
| Ubuntu02 → Windows04 | Overwrite | Updates to the latest file as soon as a file with the same name is found. |
| macOS01 → macOS02 | Create date folder | /2026-01-15/ Automatically creates and saves a folder with the same date. |
| macOS02 → macOS03 | Create date folder | Organizes daily by date in the /YYYY-MM-DD/ format. |
| Rocky01 → Debian01 | Source device folder | Saves in the /Rocky01/ folder. |
| Rocky02 → Debian02 | Source device folder | Automatically sorts and saves by device name. |
| Debian03 → Windows05 | Direct input folder | Saves in the user-specified /projects/alpha/ folder. |
| Debian04 → Windows06 | Direct input folder | Saves in the /custom/path/reports/ folder. |
| Fedora01 → Ubuntu03 | Auto numbering | Prevents duplication using the same method as video_1(3).mp4. |
| Fedora02 → Ubuntu04 | Overwrite | Replaces with the latest CSV file every hour. |
| Windows07 → macOS04 | Create date folder | Saves all files under /2026-02-01/. |
| Windows08 → macOS05 | Create date folder | Archives by newly created date. |
| Ubuntu05 → Rocky03 | Source device folder | /Ubuntu05/ Maintains the internal tree and saves. |
| Ubuntu06 → Rocky04 | Source device folder | Automatically organizes the collection structure by device. |
| macOS06 → Windows09 | Direct input folder | Saves in the /CustomerA/data/ folder. |
| macOS07 → Windows10 | Direct input folder | /Backup/Monthly/ User-specified folder. Maintain |
| RedHat01 → Fedora05 | Auto numbering | log.txt → log(1).txt → log(2).txt |
| RedHat02 → Fedora06 | Overwrite | Replace the existing log file with the latest log file and save it |
Sequentially connecting devices in multiple is also very simple.#
You can create as many sequential transfer flows as you want, without any device limitations.#
| Purpose | Sequential transfers example |
|---|---|
| AI model training data collection and refinement | 5 Debian machines → RHEL → Windows → 100 Ubuntu machines |
| Large-scale image data labeling pipeline | macOS workstations → Ubuntu labeling servers → AWS S3 → RHEL analytics servers |
| Automated collection and backup of scientific experiment results | 20 Fedora sensor machines → Debian centralized servers → Azure Blob Storage → CentOS analytics cluster |
| Financial log security analysis pipeline | RHEL security machines → CentOS SIEM servers → Ubuntu ML servers → AWS S3 storage |
| Mobile app build artifact distribution | macOS build machines → Debian packaging → Azure Blob → 10 Fedora test machines |
| Large-scale medical data refinement and diagnostic model distribution | 30 Ubuntu imaging machines → RHEL analytics servers → AWS S3 → 50 Debian diagnostic machines |
| IoT device log collection and summary model transfer | 100 Fedora IoT machines → CentOS gateway → Debian analytics servers → Azure Blob storage |
| Compression, refinement, and backup of lab experiment results | RHEL sensors → Fedora refinement servers → macOS verification → AWS S3 final backup |
| Automated enterprise code deployment | Windows development servers → Debian CI servers → RHEL deployment servers → 40 CentOS nodes |
| Global deployment of AI inference models | Ubuntu main servers → AWS S3 → Azure Blob → macOS/RHEL/Ubuntu mix 200 units |
You can also link them so that once A transfer is complete, B transfer automatically resumes.#
Different transfers are connected in real time and automatically executed sequentially as a single flow.#
| Schedule conditions | Example |
|---|---|
| Starts when a specific transfer is completed | 500 Ubuntu servers → AWS S3 complete, then 200 RHEL servers → Windows servers automatically start. |
| Starts when a specific transfer is completed | 300 CentOS servers → Fedora Hub completes 20 servers, then Hub → macOS 150 servers begin deployment. |
| Starts when a specific transfer is completed | 400 Windows servers → Debian servers complete, then Debian → AWS S3 backups automatically start. |
| Starts when a specific transfer is completed | 80 Rocky servers → RHEL central server completes, then RHEL → Ubuntu 1,000 servers are deployed. |
| Starts when a specific transfer is completed | 200 macOS servers → AWS S3 upload completes, then S3 → Windows 500 servers are redistributed. |
| Starts when a specific transfer is completed | 250 Fedora servers → CentOS Hub completes, then Hub → Debian 200 servers are deployed normally. |
INNORIX Platform's automation is broadly categorized into four types, allowing even complex tasks to be easily configured.#
| Start conditions | Filters for source files | Saving conditions in target path | Event after complete |
|---|---|---|---|
| Starts upon completion of a specific transfer | Specific extensions (e.g., jpg, png, etc.) | Duplicate files are automatically numbered. | Call a specific CallBackURL after the transfer is complete |
| Sends once at a specified date and time | Files with specific characters or numbers in their file names | Duplicate files are overwritten. | |
| Repeatedly every hour | Files without specific characters or numbers in their file names | Create and save a folder with the date each time. | |
| Repeatedly at a specified time every day | Files larger than a specific capacity | Create and save a folder with the source device name. | |
| Repeatedly on a specific day and time every week | Files smaller than a specific capacity | Create and save a folder with the manually entered name. | |
| Repeatedly on a specific day and time every month | Files with file names that match specific regular expression conditions | ||
| Synchronization - Compare two devices and transfer only new files |
Plan and execute file transfer tasks that were previously difficult to automate with INNORIX Platform.#
| Cases | Issues (reasons for manual transfer) | INNORIX Platform |
|---|---|---|
| Randomly generated log collection | Unpredictable log generation timing → Engineers manually connect. | Automatically collects new files immediately through folder monitoring. |
| Inspection image and data generation for manufacturing device | Data generation cycles vary by device, making scheduling impossible. | Transfers files immediately upon creation, automatically resumes transfers upon interruption. |
| Intermittent network device (local and remote areas) | Repeated transfer interruptions → Engineers repeatedly retransfer. | Automatically retries/resumes upon connection. |
| Remote CCTV and recording file collection | Irregular recording end times → Manual collection and USB transfer. | Automatically detects and collects only completed files. |
| Large-scale device patching (hundreds or more) | Manual connection and upload for each device takes several days. | Simultaneous connection and patch distribution to multiple devices. |
| Amorphous data explosion (images, sensors, video) | Manual collection tasks surge when data generation volume increases. | Condition-based automatic collection + resume transfer. |