Pipeline Management

Pipeline management is reliable, easy, and flexible with Etleap ETL.

Data Ops: The Etleap Way

shield icon


Etleap is built to handle the expected and the unexpected, preempting known issues and minimizing impact when new problems arise.

hand icon


At each stage of the data ops workflow, Etleap ETL provides easy setup and guides users to clear issue resolution.

hub icon


Etleap ETL has the flexibility to meet every customer’s dynamic data environment and unique needs.

shield icon Reliable

Ready for the expected and the unexpected

Etleap ensures reliable data ops in two key ways:

Incorporating a wealth of ETL troubleshooting experience into the product gear icon

Rapidly detecting and minimizing the impact of new, fringe issues magnifier icon

gear icon Built with hundreds of thousands of pipelines of experience

  • Billion-record Salesforce object extraction checkbox icon
  • Unexpected schema change checkbox icon
  • Ingesting millions of small files from an S3 bucket checkbox icon
  • Redshift cluster being resized checkbox icon
  • AWS EC2 instances being retired checkbox icon
  • Expected a value to be an integer, was a string instead checkbox icon
  • Temporary connection loss to on-premises Oracle database checkbox icon
  • MS SQL database offline for backup checkbox icon
  • Retroactive attribution of data in Google Ads checkbox icon
  • Backfill of webhook events checkbox icon
  • Errors raised while executing a custom Python function checkbox icon
  • Changed order of columns in a CSV file checkbox icon
  • Automatic scaling to handle terabytes of file data backfill checkbox icon
  • Strings too wide for a Redshift varchar column checkbox icon
  • Out-of-date data in the source checkbox icon
  • Transformation SQL no longer valid checkbox icon

Managing data pipelines is a frustrating endeavor. Between infrastructure scaling, API details, source changes, and more, there are countless causes of pipeline failure. Manually writing code to preempt these known issues is a huge, error-prone undertaking.

Etleap ETL customers, on the other hand, increase pipeline uptime and reduce their dependence on internal, specialized ETL developers.

Etleap ETL has automatic detection and guided solutions for these known pipeline challenges, and Etleap’s engineering team constantly incorporates new ones as well.

magnifier icon Architected for the unknown

What about the corner cases? With the large variety of data sources and dynamic data volumes and velocity, it’s often issues that have never been seen before that cause everyday pipeline failures. Etleap ETL minimizes the impact of potential issues, detects them quickly when they do occur, and then mitigates them efficiently.

  1. Minimize Impact

    Etleap ETL's architecture is built with pipeline independence - an issue with one pipeline doesn't affect the operation of another. Examples include separate runtime environments per pipeline and automatic compute scaling in response to increased load of a single pipeline.

    impact icon
  2. Detect Quickly

    In the era of continuous rather than daily ETL, pipeline monitoring requires more sophistication. For instance, different approaches are needed to detect issues with a low-latency Kafka stream than a periodic pull from Google Analytics’ API. Etleap ETL’s monitoring is built to detect issues as soon as they occur and minimize false positives.

    detection icon
  3. Mitigate Efficiently

    Tons of data pipeline instrumentation helps Etleap's team get to the bottom of issues quickly. Perhaps delays are caused by contention from an external process in the destination warehouse or maybe errors are caused by an unannounced API change. Etleap engineers can quickly diagnose these and resolve them accordingly.

    mitigation icon
hand icon easy to use

Effortless Data Ops

An easier path to monitoring, alerting, and issue resolution

Like many ops functions, Data Ops can be framed into three distinct components: Monitoring, Alerting, and Resolution. These steps can quickly consume the time of multiple data engineers as the volume and complexity of data sources and pipelines increase.

Etleap ETL makes it easy to create pipelines and, just as importantly, it boosts Data Ops productivity. Monitoring and alerting are robust and configurable to meet each customer’s needs. Fast resolution of a single pipeline issue can eliminate hours or even days of engineering effort. Etleap automates many solutions and delivers easy-to-follow guidance when user action is needed.

Etleap logo

Without Etleap

monitor icon monitor

alert icon alert

resolve icon resolve

Out of the box

Input email address or SNS topic

Follow detailed steps to address the root cause

Instrument ETL infrastructure and processes

Publish metrics to APM tool

Decide which metrics matter the most

Tune threshold and alert levels

Identify the root cause

Code a fix, test, deploy

Verify that it solves the problem

hub icon flexible

Data Ops that fits each customer’s unique needs

While automation delivers much of the value behind Etleap ETL Data Ops, that does not make it a rigid black box. Etleap ETL is configurable, extensible, and adaptable to match customers’ environments.

Customer Case Studies

See why modern data teams choose Etleap

You’re only moments away from a better way of doing ETL. We have expert, hands-on data engineers at the ready, 30-day free trials, and the best data pipelines in town, so what are you waiting for?

Request a Demo