DeployAngel
Know when a release is safe to stop watching, or what broke.
A startup from the United States.
Know when a release is safe to stop watching, or what broke.
A startup from the United States.
This page is designed to help you find out whether DeployAngel is good and if it is the right choice for you.
DeployAngel answers one question after every deploy--is this release working in production, or did it quietly break something?
Most deploy problems that get past CI don't raise an exception. A callback fires in the wrong order, a webhook stops arriving, a scheduled job skips a run, a route gets slower. Error trackers see nothing because nothing errored. DeployAngel catches these by comparing each release with the last one it cleared, per route and per job, using fixed rules with explicit sample sizes. There is no health score, and the optional AI investigation only explains a failure after the rules have found it.
Every release gets one of three outcomes. Cleared, with a report of what was exercised, what wasn't, and what is still being watched. Failed, naming the routes or jobs involved, the changed files most likely behind it, and the last good release. Not cleared yet, saying exactly what evidence is missing. A quiet app or an after-hours deploy waits for real traffic instead of passing on too little data.
The agent sends counts and latency histograms only, never request bodies, parameters, or cookies, and never makes a network call in a request path. DeployAngel never sends traffic to your app and never rolls anything back. Verdicts are available on the dashboard, by email and Slack, through a signed webhook, and to coding agents through a CLI, an MCP server, and CI exit codes, so a deploy pipeline or an agent can wait on the result and a person makes the final call on anything it flags.
Agents are open source under the MIT license for Rails, Hanami, Sinatra, Django, FastAPI, Flask, and ASP.NET Core. Deploys are detected automatically on Heroku and GitHub Actions, or registered with a one-line deploy hook anywhere else. DeployAngel works alongside Sentry, Honeybadger, AppSignal, and similar tools rather than replacing them.
Listed in
Deploy verdict
Every production deploy ends Cleared, Failed, or Not cleared yet, with the evidence behind it
Release-to-release baseline
Compares each release with the last one it cleared, not with the hour before the deploy
HTTP regression detection
5xx rate and p95 latency per route, with explicit sample sizes and thresholds
Exception detection
New exception fingerprints and spikes in existing ones, stable across deploys
Background job verification
Job failure rate and duration regressions, per job class
Scheduled job monitoring
Missed or failed recurring runs, during a release and between releases
Silent failure detection
Routes, jobs, and webhooks whose traffic collapses while nothing errors
Worker and agent silence alerts
Alerts when workers stop picking up jobs or an app stops reporting
Clearance report
What was exercised, what wasn't, and what DeployAngel is still watching
Latency watch
Keeps comparing latency through the release's first day and alerts on late regressions
Critical flows and checkpoints
Name the paths that matter more than their traffic suggests and verify they ran
Human-only acceptance
An intentional drop is accepted by a person on the dashboard with a reason, never by an agent
AI investigation
Optional explanation of a failure, run only after the deterministic rules have found it
Rollback guidance
Names the last cleared release and the migrations a rollback would cross
Coding agent integration
CLI, MCP server, and CI exit codes so an agent can wait on the verdict
GitHub integration
GitHub Action for deploy pipelines and commit checks on the repository
Notifications
Slack, email, PagerDuty, signed webhook, Honeybadger Insights, AppSignal markers
Deploy detection
Automatic on Heroku and GitHub Actions, one-line deploy hook anywhere else
Staging promotion
Tracks a release from staging to production and shows the staging verdict
Shareable release pages
Public read-only link to any release's verdict and report
Fire drill
Tests the whole alert path without sending traffic or writing telemetry
Open-source agents
MIT-licensed for Rails, Hanami, Sinatra, Django, FastAPI, Flask, and ASP.NET Core
Privacy by design
Aggregated counts and histograms only, no request bodies, parameters, cookies, or logs
Hands off production
Never sends traffic to your app and never rolls anything back
We have collected here some useful links to help you find out if DeployAngel is good.
Check the traffic stats of DeployAngel on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of DeployAngel on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of DeployAngel's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of DeployAngel on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
The latest comments about DeployAngel on Reddit. This can help you find out how popualr the product is and what people think about it.
Do you know an article comparing DeployAngel to other products?
Suggest a link to a post with product alternatives.
Is DeployAngel good? This is an informative page that will help you find out. Moreover, you can review and discuss DeployAngel here. The primary details have been verified within the last quarter. So they could be considered up to date. If you think we are missing something, please use the means on this page to comment or suggest changes. All reviews and comments are highly encouranged and appreciated as they help everyone in the community to make an informed choice. Please always be kind and objective when evaluating a product and sharing your opinion.
