ERCOT
ERCOT engineering guides
Practical engineering notes for collecting, validating and operating ERCOT market-data pipelines.
These guides focus on the problems that appear after the first successful API request: rate limits, incomplete datasets, publication latency, historical backfills, retries, cloud deployment, and proving that the data you expected actually arrived.
Get the data
Connecting to ERCOT and choosing where each dataset comes from.
API
Getting started with the ERCOT Public API in Python
Registration, authentication, a first request, pagination, and the pieces a collector needs to run unattended.
Read the guideArchitecture
ERCOT API vs file downloads for market data pipelines
When to use API queries, when to use published report files, and how to combine the two.
Read the guideOperations
Why an ERCOT API collector can work locally but fail in the cloud
A troubleshooting method for 403s after deployment: egress IP, region, client stack and authentication.
Read the guideKeep it running
Collectors that survive rate limits, failures and long historical runs.
API
Building a reliable ERCOT API pipeline under rate limits
Why ERCOT API 429s appeared in March 2026, and how to collect in small, resumable windows without hardcoding limits.
Read the guideReliability
How to make an ERCOT data pipeline survive 400s, 429s, 500s and timeouts
An error taxonomy for ERCOT collectors: backoff with jitter, retry budgets, persisted state and quarantine.
Read the guideReliability
ERCOT API timeouts: what we learned downloading a 655,389-record report
Why a 30-second read timeout isn’t always enough, why a timeout isn’t a 429, and how pagination metadata can set the timeout.
Read the guideArchitecture
ERCOT historical backfills need a different pipeline design
Resumable, verifiable backfills with deterministic windows, checkpoints, raw artifacts and idempotent loads.
Read the guideProve it arrived
Knowing the data is complete before anything downstream relies on it.
Data Quality
How to detect missing ERCOT market data before it reaches your models
Validate ERCOT datasets for missing intervals and entities, repair only the gaps, and promote only verified periods.
Read the guideData Quality
Why ERCOT API data can lag behind ercot.com
What ERCOT has said about publication lag, and how to tell late data from missing data.
Read the guideHow these guides are sourced
Each guide is grounded in problems ERCOT API users have raised publicly on ERCOT's api-specs discussion board, together with ERCOT's official documentation. Every guide lists its sources, gives dates where timing matters, and separates ERCOT staff replies from community reports. Unanswered questions are treated as evidence that a problem exists, not as facts about ERCOT's systems.
ERCOT's APIs, publication behavior and access policies change over time. Treat dated figures as history, and verify current requirements against ERCOT's documentation before building production systems.
SteadyState Data
Need this running reliably?
SteadyState Data builds and operates focused power-market data pipelines for trading, analytics and energy teams. Start with the market, dataset and destination. We can help determine the smallest reliable system required to collect, validate and deliver it.