osmoda-routines triggers extract-transform-load jobs on your schedule.
Process extracted data and load into your target database or warehouse.
Sends notification on pipeline success, failure, or data anomalies.
Data Pipeline Agent Template
This template describes the architecture for a scheduled ETL/data pipeline agent on osModa. The agent extracts data from configured sources on a cron schedule via osmoda-routines, transforms it through your processing logic, loads results into a target store, and sends alerts on completion or failure. osmoda-egress allowlists data sources, osmoda-watch ensures crash recovery, and every run is logged to the SHA-256 audit ledger.
This is an architecture pattern, not a downloadable ETL tool. It describes which osModa daemons your pipeline would use, how data flows from source through extraction, transformation, and loading to alerting, and how to handle failures gracefully. You bring your own ETL logic (Python, Node.js, Rust, SQL scripts, or any tool) and build the pipeline following this pattern on your osModa server.
TL;DR
- • Scheduled ETL runs via osmoda-routines -- any cron expression (hourly, nightly, weekly)
- • Data source allowlisting via osmoda-egress -- pipeline can only reach approved endpoints
- • Crash recovery via osmoda-watch -- pipeline restarts and resumes from checkpoint
- • SHA-256 audit ledger logs every pipeline run, record counts, and errors
- • Alerts via Telegram, Slack, or Discord on success, failure, or anomalies
- • Solo ($14.99/mo) for simple pipelines, Pro ($34.99/mo) for compute-heavy transforms
Architecture Diagram
The data flow for a scheduled ETL pipeline agent on osModa.
┌──────────────────────────────────────────┐
│ osmoda-routines (CRON) │
│ triggers pipeline on defined schedule │
└──────────────────┬───────────────────────┘
▼
┌──────────────────────────────────────────┐
│ DATA SOURCES │
│ databases, APIs, S3, file servers │
│ outbound via osmoda-egress allowlist │
└──────────────────┬───────────────────────┘
│
▼
┌──────────────────────────────────────────┐
│ EXTRACT │
│ (your agent code) │
│ pull raw data from allowed sources │
│ supervised by osmoda-watch │
└──────────────────┬───────────────────────┘
│
▼
┌──────────────────────────────────────────┐
│ TRANSFORM │
│ clean, validate, reshape, enrich │
│ apply business logic to raw data │
│ checkpoint progress to disk │
└──────────────────┬───────────────────────┘
│
▼
┌──────────────────────────────────────────┐
│ LOAD │
│ write to target database / warehouse │
│ upsert, append, or replace strategies │
└──────────────────┬───────────────────────┘
│
▼
┌──────────────────────────────────────────┐
│ ALERT │
│ notify on success, failure, anomalies │
│ Telegram / Slack / Discord │
└──────────────────────────────────────────┘
┌──────────────────────────────────────────┐
│ AUDIT LEDGER (SHA-256) │
│ logs every run: records in/out, errors │
│ tamper-evident pipeline history │
└──────────────────────────────────────────┘Components
The building blocks of this data pipeline architecture.
Cron Scheduler
osmoda-routines triggers the pipeline on a cron schedule you define. Supports standard cron expressions. Failed runs are logged to the audit ledger and the next scheduled run proceeds normally.
Extractor
Your code that connects to data sources and pulls raw data. Fetches from databases, REST APIs, S3 buckets, or file servers. All outbound connections pass through osmoda-egress for allowlisting.
Transformer
Your processing logic that cleans, validates, reshapes, and enriches the raw data. This is where compute requirements vary -- simple CSV reshaping needs minimal resources, while large joins or ML feature engineering need more.
Loader
Writes transformed data to the target store. Supports upsert, append, or full-replace strategies depending on your use case. Target can be a local database, remote warehouse, or filesystem on the same server.
Alert System
Sends notifications on pipeline completion, failure, or data anomalies (e.g., record count dropped unexpectedly). Supports Telegram, Slack, Discord, and WhatsApp via osModa multi-channel messaging.
Crash Recovery
osmoda-watch supervises the pipeline process. If it crashes mid-run, the watchdog restarts it. Checkpoint-based recovery lets the pipeline resume from the last processed batch instead of reprocessing everything.
osModa Features Used
The specific daemons and platform capabilities this template relies on.
osmoda-routines
Cron scheduler for ETL runs. Triggers your pipeline on any schedule you define. Handles job lifecycle, failure logging, and prevents overlapping runs.
osmoda-egress
Data source allowlisting proxy. Only allows outbound connections to endpoints you have explicitly approved. Prevents the pipeline from reaching unauthorized databases, APIs, or services.
osmoda-watch
Process supervision with auto-restart. If the pipeline crashes due to out-of-memory errors, network timeouts, or malformed data, osmoda-watch restarts it.
SHA-256 Audit Ledger
Tamper-evident log of every pipeline run. Records start time, end time, records extracted, records loaded, errors, and a SHA-256 hash per entry. Useful for debugging, compliance, and data lineage verification.
Step-by-Step Setup
How to implement this architecture pattern on your osModa server.
- 1
Spawn a server and SSH in
Go to spawn.os.moda and create a Solo ($14.99/mo) or Pro ($34.99/mo) server depending on your transform complexity. SSH in with your key. All 9 Rust daemons are already running.
- 2
Configure the data source allowlist
Add the hostnames of your data sources (database servers, API endpoints, S3 buckets) to the osmoda-egress allowlist. Only approved sources will be reachable.
- 3
Build the extract, transform, and load stages
Write your extraction code to pull data from sources. Build the transform logic to clean and reshape it. Implement the loader to write results to your target store. Use any language -- Python, Node.js, Rust, SQL scripts.
- 4
Register the pipeline with osmoda-watch
Register the pipeline process with osmoda-watch for crash recovery. Configure restart policies and implement checkpointing so the pipeline can resume from the last processed batch after a crash.
- 5
Schedule the pipeline via osmoda-routines
Define your ETL schedule using a cron expression. osmoda-routines will trigger the pipeline at the specified times and log each run to the SHA-256 audit ledger.
- 6
Connect alerting channels
Configure Telegram, Slack, or Discord notifications. The pipeline sends alerts on successful completion (with record counts), failures (with error details), or data anomalies (e.g., unexpected drops in record volume).
Recommended Plan
Plan choice depends on your transform complexity. Simple pipelines are I/O-bound (waiting for data sources to respond), while compute-heavy transforms need more CPU and RAM.
Solo — $14.99/mo
2 CPU · 4 GB RAM · 40 GB disk
Sufficient for simple pipelines: CSV parsing, JSON restructuring, basic aggregations, and loading into a local SQLite or remote PostgreSQL database. Handles most daily or hourly ETL schedules without issue.
Pro — $34.99/mo
4 CPU · 8 GB RAM · 80 GB disk
Recommended for compute-heavy transforms: large dataset joins, ML feature engineering, processing millions of records per run, or running multiple concurrent pipelines. The additional CPU and memory prevent OOM crashes.
Frequently Asked Questions
Is this a downloadable ETL tool?
No. This is an architecture pattern describing how to design a data pipeline agent on osModa. It outlines the data flow (Source, Extract, Transform, Load, Alert), the daemons involved (osmoda-routines for scheduling, osmoda-egress for source allowlisting, osmoda-watch for crash recovery), and the recommended plan. You write the ETL code yourself using any language or framework and deploy it on your osModa server following this pattern.
How does osmoda-routines handle ETL scheduling?
osmoda-routines supports standard cron expressions and event-driven triggers. You define a schedule (e.g., every hour, every night at 2 AM, every Monday morning) and osmoda-routines executes your pipeline at the specified times. If a run fails, the failure is logged to the SHA-256 audit ledger and the next scheduled run proceeds normally. You can also trigger runs manually.
What happens if the pipeline crashes mid-run?
osmoda-watch detects the crash and restarts the pipeline process. For long-running ETL jobs, you can implement checkpoint-based recovery: the pipeline saves its progress (last record processed, current batch offset) to disk, and on restart, resumes from the last checkpoint instead of reprocessing everything. The crash and restart are logged to the audit ledger.
How does the SHA-256 audit ledger work for pipeline runs?
Every pipeline run is logged to the SHA-256 audit ledger. Each entry records the run start time, end time, records extracted, records transformed, records loaded, any errors encountered, and a SHA-256 hash of the entry. This creates a tamper-evident log of all pipeline activity. You can query the ledger to audit pipeline history, debug failures, or verify data lineage.
What plan is recommended for a data pipeline agent?
Solo ($14.99/mo, 2 CPU, 4 GB RAM, 40 GB disk) is sufficient for simple pipelines with lightweight transforms -- CSV parsing, JSON restructuring, basic aggregations. For compute-heavy transforms like large dataset joins, ML feature engineering, or processing millions of records per run, Pro ($34.99/mo, 4 CPU, 8 GB RAM, 80 GB disk) provides the additional CPU and memory.
Can I connect to external databases and APIs as data sources?
Yes. You add the hostnames of your data sources (database servers, REST APIs, S3 endpoints, etc.) to the osmoda-egress allowlist. The pipeline can only reach approved sources -- any request to a non-allowlisted host is blocked. This prevents the pipeline from being exploited to access unauthorized resources, which matters when your transform logic processes untrusted data.
Build Your Data Pipeline on osModa
Spawn a dedicated server with osmoda-routines for scheduling, osmoda-egress for data source control, and osmoda-watch for crash recovery. From $14.99/month.
Last updated: March 2026