Real observability. Real control.
The Erathos Summer Release 2026 introduces new capabilities to operate data ingestion pipelines with greater visibility and control in production environments.
Watch the video to see everything that’s new.
Observability
As data operations grow, simply knowing that a pipeline executed successfully is no longer enough. Data teams need to understand how pipelines behave over time, identify patterns of instability, and investigate specific executions when something changes.
To address this need, the Summer Release introduces two new operational views: All Jobs and All Runs. Together, these views provide observability into data ingestion both at the job level and at the execution level.
All Jobs + Job Detail
The All Jobs view provides a centralized overview of all data ingestion pipelines running in the environment.
Instead of navigating connector by connector, teams can access a consolidated dashboard where every job is visible in a single place. This makes it easier to monitor operational health and identify potential issues across the ingestion layer.
The interface allows teams to customize the columns displayed, enabling each team to tailor the view to the operational metrics that matter most to their workflows.
Execution history is also surfaced directly in the table, making it easy to identify patterns of instability or changes in pipeline behavior.
When selecting a specific job, users can access the Job Detail view, which provides additional context about the pipeline.
In Job Detail, teams can analyze:
execution history
job health and stability
configuration details
pipeline behavior over time
This makes ingestion pipelines significantly easier to monitor and investigate in production environments.
All Runs + Run Detail
While the All Jobs view focuses on pipeline-level visibility, the All Runs view provides insight into individual pipeline executions.
This view presents a chronological list of all ingestion runs, making it possible to analyze operational behavior across time. Teams can quickly identify anomalies, investigate unexpected behavior, or review execution history when debugging issues.
Each execution can be inspected through the Run Detail view.
Run Detail provides a complete operational context for a specific execution, including:
execution timestamp
total duration
number of requests performed
retry activity
whether the run was incremental or a full refresh
the cursor used during extraction
I
nstead of treating executions as simple log entries, Erathos exposes them as structured operational events that can be inspected and analyzed.
Control
Observability is only one side of operating ingestion pipelines in production. Teams also need the ability to adjust pipeline behavior when source systems change or when operational requirements evolve.
Data sources can behave unpredictably, schemas change, and business requirements frequently require data to be reprocessed. When these situations occur, data teams need precise operational controls rather than rigid default behaviors.
The Summer Release introduces new capabilities designed to give teams greater control over how data ingestion pipelines execute.
Custom Run
When issues occur in upstream systems, many ingestion tools require a full refresh to recover data. However, full refreshes are often unnecessary and can introduce additional load or operational complexity.
With Custom Run, teams can edit the cursor used for a pipeline execution and reprocess only the specific range of data that needs to be updated.
This capability is particularly useful when:
reprocessing a specific time window
recovering records affected by schema changes
rebuilding data after upstream deletions
correcting inconsistencies discovered downstream
By allowing targeted reprocessing, Custom Run enables data teams to resolve issues more precisely without restarting the entire ingestion pipeline.
Retry & Buffer Strategy
Source systems do not always behave consistently. Some data sources are highly stable, while others may occasionally return errors due to rate limits, temporary outages, or infrastructure issues.
Most ingestion tools apply a fixed retry strategy across all pipelines. However, pipelines often have different operational requirements and priorities.
With the new Retry & Buffer Strategy, teams can configure retry behavior to better match the characteristics of each source system.
Retry settings can be configured at two levels:
Connection level, applying to all pipelines using a specific source
Job level, allowing individual pipelines to override the default behavior
Teams can define:
the number of retry attempts before a run fails
the backoff multiplier, which determines the waiting time between retries
This flexibility allows ingestion pipelines to adapt to the operational characteristics of each source system rather than relying on a fixed retry configuration.