Ship to production without holding your breath
Cloud application deployment is everything between a merged pull request and code serving real traffic. When it works, releases are boring. When it does not, teams ship on Friday nights, roll back by hand, and treat every deploy as a small emergency — which quietly slows the whole product down.
Willowark builds deployment pipelines as production software: versioned, tested, and observable. We start by mapping your current release path — including the manual steps people forget to mention — then automate it stage by stage, so the team keeps shipping while the pipeline hardens underneath them.
Cloud & InfrastructureHow the work gets done
The same way every time: scope, build, hand over.
The build typically includes CI pipelines in GitHub Actions, GitLab CI, or similar; reproducible container image builds; environment promotion with automated smoke tests; and a release strategy matched to your risk profile — blue/green for clean cutovers, canary for gradual rollout, rolling updates where brief mixed versions are acceptable. Database migrations get their own path, with backward-compatible steps so a rollback never strands the schema.
In production, the pipeline is the only way code ships — no SSH, no hand-edited configs. Success looks like deploy frequency going up while release incidents go down: a change merged in the morning is in production by lunch, and a bad release is rolled back in minutes by pressing the same button that shipped it.
Scoping begins with a walkthrough of a real release, ideally watching one happen. We record every step — the build, the manual approvals, the config edited on the server, the chat message that tells support to expect trouble — and rank them by risk and time. The trade-offs we weigh are mostly about speed versus safety: how many test gates before an automated promotion, whether staging mirrors production closely enough to trust, and how much traffic a canary should take before the pipeline calls it good. We also look at what the team can realistically maintain; a pipeline that only we understand is a liability, not a deliverable.
The things that usually break a deployment pipeline are the ones outside it: a migration that locks a large table, a cache that serves stale objects after cutover, a background worker still running the old version. We design against these with expand-and-contract migrations, health checks that exercise real dependencies, and versioned queues so old and new workers coexist. Success is measured in the rate of releases and the rate of rollbacks, both of which we baseline before starting. Handover includes the pipeline code in your repository, a runbook for the failure cases, and at least one release where your team drives while we watch.
Scope it in writing
What we agree before work starts
- CI/CD pipeline with build, test, and promotion stages
- Blue/green or canary release setup with automated rollback
Build with checkpoints
Working results, not slide decks
- Database migration strategy that survives rollbacks
- Secrets management and per-environment configuration
Hand over something you own
Documentation, source, and training
- Deployment runbook and team handover session
- Smoke and post-deploy verification tests that run automatically against each environment
Sound familiar?
Where cloud application deployment earns its keep.
A team that deploys quarterly because every release breaks something
A web app deployed by copying files to a server that one person knows how to touch
An API with customers in three time zones and no window for downtime
A rollback procedure that exists only in a senior engineer's head
Ask about Cloud Application Deployment
Describe the problem. Get a straight answer.
One line is enough. An engineer replies within a business day.
Related work
AI operating software for training operations
Components:
- Schedulers (training ops): The people running the training operation.
- Operating software (AI assistance): The operating software, with AI assistance built in.
- Cloud services (distributed): Distributed cloud services behind the application.
- Training game (learning): The training game the software connects to.
Connections:
- Schedulers to Operating software
- Operating software to Cloud services
- Operating software to Training game
A global automotive manufacturer's training operation · Automotive
AI operating software for training operations
AI operating software for the manufacturer's training schedulers — removing manual scheduling labor and logistics tracking, saving hundreds of hours per year — plus a training video game built to help trainers perform better. Used across the manufacturer's training organization.
Read the case study →Common questions
Asked before every cloud application deployment project.
What is the difference between blue/green and canary deployment?
Blue/green runs two identical environments and switches traffic all at once — instant cutover, instant rollback. Canary shifts a small slice of traffic to the new version first and watches error rates before rolling out further. We recommend based on your traffic patterns, tolerance for mixed versions, and how quickly your monitoring can catch a regression.
Can you achieve zero-downtime deployments for us?
For most web applications and APIs, yes — with load balancer draining, health checks, and backward-compatible database migrations. The honest caveat is stateful components: long-lived connections and in-flight jobs need specific handling, and we design for those cases rather than pretending they do not exist.
Do we need Kubernetes for this?
No. Plenty of teams get excellent deployment automation with ECS, Cloud Run, or plain VMs behind a load balancer. Kubernetes earns its complexity at a certain scale and organizational shape; we will tell you plainly if you are not there yet.
Can you work with our existing CI provider, or do we have to switch?
We work with what you have. GitHub Actions, GitLab CI, Bitbucket Pipelines, Jenkins, and CircleCI all support the patterns we build, and switching providers mid-engagement adds risk without much benefit. The exception is when the existing tool is genuinely the bottleneck — an unmaintained Jenkins server with plugins nobody dares update, for instance. In that case we lay out the migration cost honestly and let you decide.
How do you handle secrets and environment-specific configuration?
Secrets live in a dedicated store — AWS Secrets Manager, Vault, Azure Key Vault, or the CI provider's own encrypted variables — and are injected at deploy or runtime, never committed to the repository or baked into images. Configuration that differs between environments is kept as data separate from the application code, so the same tested artifact moves from staging to production unchanged. We also set up rotation and audit logging so a leaked credential is a contained event rather than a rebuild.
Where this sits
Cloud Application Deployment, inside a cloud & infrastructure system.
The lit component is the part of the system this service delivers; the rest is what it has to work with.
Hover or focus a component to see what it is and what it talks to. Arrow keys move between them.
Plant systems reach the cloud over an encrypted tunnel; services run in containers over managed data stores, and monitoring alerts a person before a customer notices.
Components:
- Plant network: OT network, segmented from IT.
- Tunnel (VPN / private link): Encrypted, allow-listed, no inbound ports on the plant side.
- Services (containers): Deployed from CI, rolled back in one command.
- Data stores (DB, objects): Managed database and object storage with backups tested, not assumed.
- Monitoring (logs, metrics): Health, latency, error rate, cost.
- On-call: Someone is paged before a customer emails.
Connections:
- Plant network to Tunnel over VPN
- Tunnel to Services over MQTT
- Services to Data stores over SQL
- Services to Monitoring over events
- Monitoring to On-call over push
Strategy. Software. Systems.
Have a system that should exist?
Tell us what your operation is doing manually, what isn't connected, or what you're trying to build. We'll tell you plainly whether and how we can help.