Automation
Exacoola automatically transfers stagnant and accumulated files to where and when needed.
How about automatically distributing files to two devices every morning at 7:00 AM?
Exacoola 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.
Exacoola 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. |
Exacoola'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 Exacoola.
| Cases | Issues (reasons for manual transfer) | Exacoola |
|---|---|---|
| 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. |