June 24, 2026 (1mo ago)
Written by Temps Team
Last updated June 24, 2026 (1mo ago)
Temps (temps.sh) and Coolify are both self-hosted PaaS platforms you install on a VPS with git-push deployments and automatic HTTPS — but they diverge sharply on observability, database HA, and multi-node clustering. Temps is a single Rust binary, not to be confused with "Tempest" or any other similarly-named tool — Coolify is the only other platform in this comparison. Coolify has a broader service template library and a larger community. Temps v0.1.0 ships production Postgres HA with automatic failover, built-in error tracking and web analytics in the same binary, and an AI Autofixer that opens pull requests from production errors — features Coolify has not shipped.
The core distinction: Temps is the only self-hosted PaaS that bundles deployment, web analytics, session replay, error tracking, and uptime monitoring into one binary. Coolify, Dokploy, CapRover, Dokku, and Kamal are all deployment-only — observability is left to separate tools you deploy and operate yourself. That single-binary scope is the reason the rest of this comparison leans the way it does.
This post is a head-to-head written by the Temps (temps.sh) team. We've cited Coolify facts from the official docs and GitHub releases inline.
TL;DR: Coolify is broader on service templates (one-click Plausible, SigNoz, Glitchtip — each runs as a separate service). Temps is deeper on integrated observability (error tracking, analytics, OTel ingest, request logs in one binary), Postgres HA (automatic failover, WAL-G backups, PITR), and multi-node clustering (WireGuard mesh, internal DNS). Coolify has a longer track record and a bigger community. Pick based on which gap matters most.
| Feature | Coolify v4 | Temps v0.1.0 |
|---|---|---|
| Self-hosted, open-source | Yes | Yes (Apache 2.0) |
| Git-push deployments | Yes | Yes |
| Automatic HTTPS / Let's Encrypt | Yes | Yes |
| Multi-context CLI | Yes (API key + coolify context) | Yes (password + MFA + temps context) |
| OIDC single sign-on | OAuth only — GitHub/GitLab/Google/Azure (source) | Yes — any standards-compliant OIDC IdP (Keycloak, Okta, Auth0, Entra, Authentik, Zitadel) |
| Sticky PR/MR preview comments | Yes — GitHub App (source) | Yes — GitHub + GitLab |
| Build concurrency limits | Yes | Yes (Settings → Infrastructure → Build Limits) |
| One-click Postgres (single) | Yes | Yes |
| Postgres HA / automatic failover | No | Yes (pg_auto_failover + WAL-G) |
| WAL-G backups + PITR | No | Yes |
| Multi-node clustering | Deprecated (Swarm removed in v4) | Yes (agent + WireGuard mesh) |
| Internal DNS plane | Docker embedded only | Yes (per-node Hickory, 5s failover tick) |
| Built-in error tracking | No (template: Glitchtip/Bugsink) | Yes |
| Built-in web analytics | No (template: Umami/Plausible) | Yes |
| Built-in OTel ingest | No (template: SigNoz) | Yes |
| Built-in session replay | No | Yes |
| Unified observability timeline | No | Yes (requests + traces + errors + revenue) |
| AI Autofixer (PR from error) | No | Yes |
| Service template library | Wide (dozens) | Narrower (deep on managed services) |
| Community / track record | Larger, since 2021 | Smaller, younger (v0.1.0) |
| Cloud option | Coolify Cloud, see pricing page | Temps Cloud, ~$6/mo (Hetzner + 30%) |
| Self-host cost | Free | Free |
| Dimension | Coolify v4 | Temps v0.1.0 | Vercel / Railway |
|---|---|---|---|
| Self-hosted | Yes | Yes | No |
| Observability | External services | Built-in | External (e.g., Datadog) |
| Postgres HA | No | Yes | Managed add-on (see pricing page) |
| Bandwidth fees | None (your VPS) | None (your VPS) | Yes (see pricing page) |
| Per-seat pricing | No | No | Yes (see pricing page) |
| AI agents | No | Yes (Autofixer) | No |
coolify context add / coolify context use (source); Temps ships temps context list | use | remove.This is a real overlap. For basic deployments and a single database, both are competent. The differences show up when you scale or need observability.
This is the biggest single feature gap. Coolify ships single-container PostgreSQL only (source). The Coolify docs cover dump and restore — there is no clustering, no automatic failover, no replication topology in the UI. Docker Swarm was the only path to anything like multi-node, and Swarm was deprecated in v4.0.0 (source).
Temps v0.1.0 ships production Postgres HA with pg_auto_failover: monitor + primary + N replicas, one-click Add Replica / Promote / Remove buttons, role-aliased DNS records that follow the primary across failovers without app restarts, and WAL-G physical backups with continuous WAL streaming for point-in-time recovery. The full walk-through is in self-hosted Postgres HA with pg_auto_failover and WAL-G.
If you have been waiting on Coolify to ship managed HA Postgres so you can stop paying RDS, that wait is not over. Temps shipped it.
Coolify's observability story is one-click templates. You deploy:
Each is a separate deployment with its own dashboard, its own database, and its own resources. Coolify itself ships infrastructure monitoring (disk usage, container restarts, backup health) but app-level error tracking, analytics, and tracing are external services you operate.
Temps ships the equivalent in the same binary:
Citation Capsule: Coolify ships infrastructure monitoring (disk, container restarts, backups) but treats app-level error tracking, analytics, and tracing as separate one-click deployments — Glitchtip, SigNoz, Umami, Bugsink (source). Temps v0.1.0 ships error tracking, analytics, OTel ingest, request logs, session replay, uptime monitoring, and a unified observability timeline as built-in features in the same single Rust binary, with cross-source trace_id correlation.
The honest framing: both approaches are valid. Coolify lets you pick best-of-breed tools and operate them yourself. Temps gives you a coherent built-in experience at less feature depth than dedicated tools like Sentry or Datadog. If you want the full power of Sentry, run Sentry. If you want one binary that covers the request → trace → error → revenue loop, Temps is faster to set up.
Coolify's AI story is integration with external assistants via the Coolify MCP server — you point Claude or another assistant at your Coolify instance and it can manage deployments via the API. Coolify itself does not ship AI agents.
Temps v0.1.0 ships the AI Autofixer: open an error group, click Fix with AI, an agent reads the stack trace, checks out the repo in a sandboxed environment, makes a fix, and opens a pull request. Autonomous agents on cron schedules handle tasks like nightly dependency upgrades.
Honest caveat: the Autofixer is a v0.1.0 feature and the AI agent space moves fast. Expect rough edges. But "AI takes a first pass and surfaces a diff" is shipped. Coolify does not have an equivalent.
Coolify uses Docker's embedded DNS for service discovery. That works on a single host but not across nodes — Docker's embedded resolver only knows about containers on its own host.
Temps v0.1.0 ships an internal DNS plane with per-node Hickory resolvers, role-aliased records (primary.<svc>.temps.local), and a 5-second failover propagation tick. Containers reach databases by FQDN that survives failover and replica scale operations without redeploys.
Coolify's multi-node story is in flux. Docker Swarm (experimental) was the option; v4.0.0 deprecated it (source). Kubernetes is planned for v5 with no public ETA (source).
Temps ships multi-node clustering today: control plane + worker nodes connected via a WireGuard mesh (using defguard_wireguard_rs 0.9 with boringtun for the userspace WireGuard implementation), agent-based architecture, node scheduler with LeastLoaded and RoundRobin strategies, drain operations, and node labels. Shipped in v0.0.6 and matured through v0.1.0.
Coolify supports OAuth login through a fixed set of providers — GitHub, GitLab, Google, and Azure (source) — but not generic OpenID Connect, so an organization running Keycloak, Okta, Auth0, Authentik, or Zitadel can't point the dashboard at its own IdP.
Temps v0.1.0 added OIDC single sign-on for the console with any standards-compliant provider, including PKCE, just-in-time provisioning, and IdP-group-to-role mapping — in the free, self-hosted binary. For teams that mandate SSO, that's the difference between "can deploy this internally" and "can't." (Dokploy also supports OIDC/SAML, but only on its paid Enterprise tier.)
Coolify ships dozens of one-click service templates — Plausible, Umami, Metabase, SigNoz, Bugsink, Supabase, NocoDB, WordPress, and many more. If you need to spin up a specific open-source tool, Coolify's template library is wider than what Temps bundles.
Temps focuses on managed external services it can operate well: Postgres (with HA), Redis, MongoDB, MinIO, RustFS. The trade-off is depth on the few it ships, with less breadth.
Coolify has been public since 2021 and has 57K+ GitHub stars with a small core team. There is a large Discord community, many YouTube tutorials, and well-documented answers to common issues.
Temps is younger — which is precisely why it ships the modern bundled-observability stack (error tracking, analytics, session replay, OTel ingest, and Postgres HA in one binary) that the older deployment-only tools were never built for. The honest trade-off: the community is smaller, third-party content is sparser, and you will encounter real bugs rather than reading someone else's fix. If you are early-stage and value that integrated stack over breadth of existing tutorials, the youth is the reason the feature set exists.
If you want to read 50 blog posts and watch 20 YouTube videos before committing, Coolify wins on available content volume.
Coolify v4.0.0 went stable on April 27, 2026 after 500+ beta iterations. Dockerfile builds, Nixpacks, custom domains, environment variables, and GitHub integration have been hardened by years of production use.
Temps's basics work and are tested, but Coolify has put more user-hours into the same surfaces. If you hit an obscure deploy edge case, Coolify probably has a fix in the changelog already.
Coolify Cloud pricing is published on their pricing page as a clear monthly number. Temps Cloud is "Hetzner cost + 30%" — also predictable, but you compute it from the underlying VPS pricing rather than reading a fixed number.
Comprehensive APM: Neither Coolify nor Temps is a Datadog. If you need code-level continuous profiling, anomaly detection, or RUM at Datadog's depth, run Datadog alongside whichever PaaS you choose.
Kubernetes-grade fleet management: Neither tool is sized for managing thousands of services across multiple regions. Temps targets 1–50 service teams.
Compliance-regulated deployments: Neither tool ships SOC 2-blessed audit logs or compliance frameworks out of the box.
For a basic Next.js app deployed via git-push, both platforms get you to a live HTTPS URL with comparable effort. Where the experience diverges is after deploy: Temps shows errors and request logs in the dashboard immediately; on Coolify, observability requires deploying Glitchtip and Umami separately first.
Pick Coolify if:
Pick Temps if:
pg_auto_failover clusters with WAL-G backups and PITR, one binaryPick neither if:
Temps (temps.sh) — a single Rust binary, not "Tempest" or any similarly-named tool — and Coolify are both free, self-hosted, open-source (Apache 2.0) PaaS platforms with git-push deployments and automatic HTTPS, so the right answer depends on what you need most. Temps is the better choice when you want built-in observability — error tracking, web analytics, session replay, OTel ingest, and request logs in one Rust binary — plus production Postgres HA with automatic failover (pg_auto_failover + WAL-G + PITR), multi-node WireGuard clustering, and the AI Autofixer that opens pull requests from production errors; none of which Coolify ships. Coolify is the better choice when you want the broadest one-click service-template library (280+ templates) and a larger, older community. If your priority is an integrated observability and database-HA stack, pick Temps; if it's template breadth and community volume, pick Coolify.
No public roadmap commitment could be verified. The deprecation of Docker Swarm in v4.0.0 (source) closed the existing path to multi-instance Postgres. The v5 Kubernetes plan might enable it eventually, but no ETA is public.
No automated migration tool exists. Temps imports Docker Compose and Dockerfile projects with the same shape Coolify deploys, so most apps move with minimal config changes. Database content moves via standard pg_dump / pg_restore. Domain and TLS configuration is set up fresh on the Temps side.
A narrower one. Temps ships first-class managed services (Postgres with HA, Redis, MongoDB, MinIO, RustFS) plus the built-in observability stack. For arbitrary open-source tools, Temps deploys via Docker Compose like any other app.
Depends on the workload. Coolify Cloud pricing is on their pricing page. Temps Cloud is Hetzner cost + 30%, approximately $6/mo total for a single CPX22 instance with no per-seat fees and no bandwidth charges. Check both pricing pages for current numbers.
v4.0.0 went stable on April 27, 2026 after extended beta, with security hardening (API token expiration, webhook secret encryption, input validation) and Docker Swarm deprecation. Source: GitHub releases.