Zero-Downtime Deployments: How They Work [2026 Guide]

Unplanned downtime costs Global 2000 companies $400 billion per year — roughly $200 million per company. A significant portion of that downtime happens during deployments: the brief window where the old version shuts down and the new version boots up.

Zero-downtime deployment eliminates that window entirely. The old version keeps running until the new one is verified and ready. No dropped requests, no broken WebSocket connections, no users seeing error pages.

This guide breaks down exactly how zero-downtime deployment works, why it matters at every scale, and how to implement it without managing blue-green scripts or complex orchestration.

TL;DR: Zero-downtime deployment keeps the old application version running until the new one passes health checks. Rolling updates, health check gating, and connection draining work together to ensure users never see errors during a deploy. Elite engineering teams deploy multiple times per day with a 5% change failure rate.

What Is Zero-Downtime Deployment and Why Does It Matter?

Zero-downtime deployment is a release strategy that ensures your application remains fully available throughout every deploy. According to ITIC, 91% of mid-size and large enterprises report that a single hour of downtime costs over $300,000. Even brief deployment gaps — five seconds repeated ten times a day — compound into real revenue loss and eroded user trust.

The 2024 DORA report found that elite-performing teams deploy on-demand (multiple times per day), recover from failures in under one hour, and maintain a change failure rate of just 5%. Low performers, by contrast, deploy weekly to monthly and take one to six months to recover, according to DORA's research. The gap between these two groups comes down to deployment automation — and zero-downtime deployments are the foundation.

The Stop-Start Problem

Most basic deployment workflows follow this pattern:

1. Stop the old version
2. Start the new version
3. Wait for it to be ready

The gap between steps 1 and 2 is downtime. During that window:

• Active requests drop — in-flight HTTP requests return connection errors
• WebSocket connections break — real-time features disconnect every connected client
• Background jobs crash — long-running tasks are killed mid-execution
• CDN caches poison — requests during the gap hit a dead origin and cache error responses
• Health checks fail — load balancers route traffic to a container that isn't ready

How Does Zero-Downtime Deployment Work?

Zero-downtime deployment combines three techniques: rolling updates, health check gating, and connection draining. Together, they ensure the old version keeps serving traffic until the new version is verified and ready. No user ever hits a dead endpoint.

Rolling Updates

Rolling deployment upgrades one instance at a time while the others continue serving traffic:

Time 0:  [v1] [v1] [v1]     <- All instances running v1
Time 1:  [v1] [v1] [v2...]  <- One instance starts v2 (not yet ready)
Time 2:  [v1] [v1] [v2]     <- v2 passes health check, receives traffic
Time 3:  [v1] [v2] [v2...]  <- Next instance starts upgrading
Time 4:  [v1] [v2] [v2]     <- Second v2 ready
Time 5:  [v2...] [v2] [v2]  <- Final instance upgrading
Time 6:  [v2] [v2] [v2]     <- All instances on v2. Zero dropped requests.

At no point are zero instances available. Traffic always has somewhere to go.

Health Check Gating

A new container joins the load balancer only after it passes health checks:

Container starts -> Runs health check -> Passes -> Receives traffic
                                      -> Fails  -> Retry (up to timeout)
                                                 -> Roll back if persistent

This prevents traffic from reaching a container that's still initializing — loading config, warming caches, or establishing database connections.

Connection Draining

When removing an old container, the system doesn't kill it immediately. Instead:

1. Stop sending new requests to the old container
2. Wait for in-flight requests to complete (up to a configurable timeout)
3. Shut down the container only after all connections close

This ensures that a user mid-checkout doesn't get an error because their server disappeared.

How Do You Set Up Zero-Downtime Deployments?

Setting up zero-downtime deployments typically requires configuring rolling update policies, health check endpoints, and drain timeouts across your container orchestrator. 82% of container users now run Kubernetes in production, but managing all that configuration is the hard part.

With a self-hosted platform like Temps, zero-downtime deployment is the default. No configuration needed:

git push origin main
# or
bunx @temps-sdk/cli deploy my-app -e production -y

Behind the scenes, every deploy follows this five-step pipeline:

1. Build — Your application builds in a fresh container. The old version keeps serving traffic.
2. Health check — The new container starts up. HTTP requests hit your health endpoint (default: /) until a 200 response comes back.
3. Traffic shift — Once healthy, the new container joins the load balancer. The old container is marked for draining.
4. Drain — The old container finishes serving in-flight requests. New requests go to the new container only.
5. Cleanup — After draining completes (or timeout), the old container is removed.

Total user-visible downtime: zero.

Default Health Check Configuration

Writing Better Health Checks

Your health endpoint should verify real dependencies, not just return 200. According to New Relic's Observability Forecast, organizations with full-stack observability experience 71% fewer outages annually. Honest health checks are the first step toward that observability:

// app/api/health/route.ts (Next.js)
import { db } from "@/lib/database";
import { redis } from "@/lib/redis";

export async function GET() {
  try {
    await db.execute("SELECT 1");
    await redis.ping();

    return Response.json({
      status: "healthy",
      timestamp: new Date().toISOString(),
      checks: { database: "ok", redis: "ok" },
    });
  } catch (error) {
    return Response.json(
      { status: "unhealthy", error: error.message },
      { status: 503 },
    );
  }
}

The new container won't receive traffic until the database and Redis connections are verified. Configure the health check path in your project settings.

What Happens When a Deployment Fails?

Deployment failures are inevitable. The DORA report introduced a new metric — Deployment Rework Rate — specifically to track how often teams need to fix failed deployments. The difference between elite and low performers isn't that elite teams never fail. It's that they recover in under an hour while low performers take months.

Automatic rollback is the safety net that makes fast recovery possible.

Automatic Rollback Triggers

The platform automatically rolls back when:

• Health checks fail — The new container never becomes healthy after three consecutive failures
• Error rate spikes — The new version produces significantly more errors than the previous one
• Crash loops — The new container keeps crashing and restarting

Deploy v2 -> Health check fails 3x -> Automatic rollback
  Result: v1 continues serving. Users never saw v2.

Deploy v2 -> Passes checks -> Error rate spikes 10x -> Automatic rollback
  Result: v2 removed, v1 takes all traffic again.

In both cases, users experience zero downtime. The broken version never reaches them — or gets removed before it causes meaningful damage.

Manual Rollback

Sometimes you discover issues that automated checks miss — a visual bug, a wrong calculation, a feature that shouldn't have shipped:

# Roll back to the previous deployment
bunx @temps-sdk/cli deployments rollback -p my-app -e production

# Roll back to a specific deployment
bunx @temps-sdk/cli deployments rollback -p my-app --to 42

Rollback completes in seconds because the previous container image is cached locally. No rebuild required.

How Do You Handle Database Migrations Without Downtime?

Database migrations are the trickiest part of zero-downtime deployment. Both GitHub's June 2025 outage and Cloudflare's November 2025 global outage were caused by database changes that cascaded into platform-wide failures. If your new code expects a column that doesn't exist yet — or your old code breaks when a column disappears — rolling deployment fails.

The Expand-and-Contract Pattern

The safe approach splits every breaking database change into three deploys:

Phase 1: Expand (backward-compatible)

-- Add the new column without removing the old one
ALTER TABLE users ADD COLUMN full_name TEXT;

-- Backfill data
UPDATE users SET full_name = first_name || ' ' || last_name;

Deploy code that writes to both columns but reads from the new one.

Phase 2: Migrate

Deploy code that only uses the new column. Both old and new application versions coexist safely because the old column still exists.

Phase 3: Contract (cleanup)

-- Safe to remove after all instances run the new version
ALTER TABLE users DROP COLUMN first_name;
ALTER TABLE users DROP COLUMN last_name;

During a rolling deployment, both v1 and v2 run simultaneously. The expand-and-contract pattern ensures both versions work with the same database schema at every step.

How Do Deployment Strategies Compare?

Choosing the right deployment strategy depends on your team's resources and risk tolerance. Here's how the four main approaches stack up:

Rolling deployment offers the best balance: zero downtime, automatic rollback in seconds, and only 1.3x resource overhead — and only during the deploy itself. No duplicate infrastructure running 24/7.

Does Zero-Downtime Work for Every App Type?

Zero-downtime rolling deployments work across all major application types. Each framework has specific characteristics that affect the transition, but all benefit from health check gating and connection draining.

Next.js and Server-Rendered Apps

Server Components render on the new container once traffic shifts. Client-side React hydration handles the transition seamlessly. For a walkthrough, see our Next.js deployment guide.

API Servers (Express, Fastify, Django, FastAPI)

Health checks verify the API responds before traffic shifts. In-flight requests complete on the old container via connection draining. If you're running FastAPI specifically, our FastAPI deployment tutorial covers the setup.

WebSocket Applications

WebSocket connections to the old container are maintained during draining. New connections route to the new container. Most WebSocket libraries handle reconnection automatically:

const socket = io("wss://myapp.com", {
  reconnection: true,
  reconnectionDelay: 1000,
  reconnectionAttempts: 5,
});

Background Workers

Long-running jobs on the old container get a grace period to complete. Configure the drain timeout based on your longest expected job through the deployment settings in the dashboard.

How Should You Monitor Deployments?

According to New Relic, organizations with full-stack observability experience 71% fewer annual outages and detect high-impact issues in a median of 37 minutes. Deployment monitoring is a critical piece of that observability.

Deployment Timeline

Every deploy produces a detailed timeline:

14:30:00  Build started
14:30:45  Build completed (image: 142MB)
14:30:48  New container starting
14:31:02  Health check passed (attempt 3)
14:31:03  Traffic shifting to new container
14:31:03  Old container draining (12 active connections)
14:31:18  All connections drained
14:31:18  Old container removed
14:31:18  Deployment complete. Zero errors.

Key Metrics to Track

After each deployment, track these five metrics:

• Deploy duration — Total time from push to live
• Health check time — How long until the new version was ready
• Drain time — How long in-flight requests took to complete
• Error rate — Before, during, and after deployment
• Response time — Any latency impact from the deployment

Don't assume a successful deploy means everything is fine. Watch error rates and response times for at least 15 minutes after each deployment.

Setting Up Alerts

# Slack notifications for deployment events
bunx @temps-sdk/cli notifications add --type slack --name "Deploy Alerts" \
  --webhook-url https://hooks.slack.com/... --channel "#deploys" -y

# Email notifications
bunx @temps-sdk/cli notifications add --type email --name "Deploy Email" \
  --smtp-host smtp.gmail.com --smtp-port 587 \
  --smtp-user user@gmail.com --smtp-pass apppassword \
  --from alerts@example.com --to team@example.com -y

For a deeper look at infrastructure security — including the network layer that supports safe deployments — see our guide on securing your VPS with Tailscale.

What Are the Most Common Zero-Downtime Mistakes?

According to the Uptime Institute, 80% of operators believe their most recent downtime event was preventable. Most zero-downtime failures come from a handful of common mistakes. Here's how to avoid them.

1. Fake Health Checks

A health endpoint that always returns 200 defeats the purpose of health check gating. Always verify real dependencies:

// Bad: always returns healthy
app.get("/health", () => ({ status: "ok" }));

// Good: verifies actual readiness
app.get("/health", async () => {
  await db.query("SELECT 1");
  await cache.ping();
  return { status: "ok" };
});

2. Breaking Database Changes in One Deploy

Never drop a column in the same deploy that stops using it. Always use the expand-and-contract pattern across multiple deploys. GitHub and Cloudflare both learned this lesson in 2025.

3. Infrequent, Large Deploys

Small, frequent deploys are easier to roll back and less likely to cause cascading failures. The DORA data consistently shows that elite teams deploy multiple times per day — not once a week. If your deployment costs are a concern, self-hosting makes frequent deploys free.

4. Skipping Post-Deploy Monitoring

A deploy that passes health checks can still have subtle issues: a visual regression, a slow database query, an edge case in a new feature. Watch metrics for 15 minutes after every deployment. Use preview environments to catch issues before production.

5. No Rollback Plan

If you can't roll back in seconds, you don't have zero-downtime deployment — you have zero-downtime deployment with a single point of failure. Always keep the previous container image cached and test your rollback process regularly.

Frequently Asked Questions

What is the difference between zero-downtime and blue-green deployment?

Blue-green deployment maintains two identical production environments and switches traffic between them. Zero-downtime deployment is the broader goal — blue-green is one strategy to achieve it. Rolling deployment achieves the same result with 1.3x resources instead of 2x, making it more cost-effective for most teams.

Can I achieve zero-downtime deployment without Kubernetes?

Yes. While 82% of container users run Kubernetes in production, you don't need to manage Kubernetes directly. Self-hosted deployment platforms handle rolling updates, health checks, and connection draining automatically — without requiring you to write YAML manifests or manage cluster state.

How long does a zero-downtime deployment take?

Deployment time depends on your build step and health check configuration. A typical Next.js application builds in 30-60 seconds, with health check verification adding another 10-15 seconds. The traffic shift itself is instantaneous. Total time from push to live is usually under two minutes.

Does zero-downtime deployment work with database migrations?

Yes, but you must follow the expand-and-contract pattern. Never make breaking schema changes in a single deploy. Add new columns first, migrate code, then remove old columns in a separate deploy. This ensures both old and new application versions work with the same schema during the rolling update window.

What happens if my new deployment keeps crashing?

The platform detects crash loops automatically and rolls back to the previous healthy version. The old container image is cached locally, so rollback completes in seconds — no rebuild needed. Users never see the broken version.

Getting Started

Zero-downtime deployment is the default. No configuration needed:

# Install
curl -fsSL https://temps.sh/deploy.sh | bash

# Login and deploy
bunx @temps-sdk/cli login
bunx @temps-sdk/cli deploy -p my-app -e production -y

Every deploy, every time, zero downtime. For teams evaluating self-hosted alternatives to Vercel or comparing deployment platform options, zero-downtime deployment comes built in — not as an add-on.

Want to learn more? Check our deployment documentation for advanced configuration, or explore the Temps CLI reference for the full command set.