Dedicated DevOps & Cloud Team

DevOps engineers who turn half-day deployments into 15-minute automated pipelines.

Manual deployments, inconsistent environments, and no observability are engineering taxes your team pays every sprint. We embed senior DevOps engineers, AWS, GCP, Docker, Kubernetes, Terraform, GitHub Actions, directly into your team. CI/CD pipelines that test, build, and deploy automatically. Infrastructure as code so environments are reproducible. Monitoring that tells you about production problems before your customers do.

  • CI/CD pipelines on GitHub Actions, GitLab CI, or CircleCI, automatic on every merge to main

  • Docker containerisation and Kubernetes orchestration with identical dev, staging, and production environments

  • Infrastructure as code using Terraform, reproducible, version-controlled, auditable

  • Monitoring and alerting with Datadog, Grafana, or CloudWatch configured from day one

Recent outcomes

Voice AI · Research

6× deeper insights

Text-based interviews converted to automated phone calls

AI Automation · Ops

20k+ txns day one

Manual invoice OCR across 40+ gas stations

Loyalty · Retail

1,062 users in 4 weeks

SuperValu & Centra loyalty platform with receipt validation

SaaS · Logistics

2,000+ shipments yr 1

Multi-carrier shipping hub for Indonesian eCommerce

4.9
on Clutch
See our work

The problem

Sound familiar?

  • How many production incidents last quarter were caused by environment configuration differences?

  • How long does your current deployment process take, and how often does it require manual intervention?

Short answer

RaftLabs embeds dedicated DevOps and cloud engineers skilled in AWS, GCP, Docker, Kubernetes, Terraform, and GitHub Actions. They build CI/CD pipelines, containerise applications, define infrastructure as code, and set up monitoring against the four DORA keys: deployment frequency, lead time, change failure rate, and time to restore service. Engagements start within one week at a fixed monthly rate.

Key takeaways

  • Dedicated DevOps engineers embed in your team and start within one week at a fixed monthly rate.
  • CI/CD pipelines on GitHub Actions, GitLab CI, or CircleCI run automatically on every merge to main.
  • Infrastructure as code with Terraform makes every environment reproducible and version-controlled.
  • Docker containerisation and Kubernetes orchestration deliver identical dev, staging, and production environments.
  • Monitoring covers infrastructure metrics, application RED method metrics, and business metrics like payment success rate.
  • SOC 2 and HIPAA compliance controls are built into infrastructure from the start, not retrofitted.

Trusted by

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Aldi logo
Nike logo
Microsoft logo
Heineken logo
Cisco logo
Calorgas logo
Energia Rewards logo
GE logo
Bank of America logo
T-Mobile logo
Valero logo
Techstars logo
East Ventures logo
TuneClub logo

Infrastructure problems are disproportionately expensive because they compound: a manual deployment process means deployments are infrequent and risky, infrequent deployments mean large diffs, large diffs mean harder rollbacks, and harder rollbacks mean longer outages. A DevOps engineer who fixes the pipeline isn't just saving deployment time, they're changing the risk profile of every future release.

The DORA research program (Google Cloud) measures delivery performance across four keys, and elite teams beat low performers on every one. According to Google's 2024 DORA State of DevOps Report, elite teams deploy on demand multiple times per day with lead times under one hour, while low performers deploy less than once per month. The gap is not talent, it is process: CI/CD automation, infrastructure as code, and monitoring are the structural differences separating a 15-minute pipeline from a half-day manual deployment.

We instrument and work to move all four DORA keys, not just deployment speed. Shipping fast means little if every third release breaks production.

Deployment frequency
How often you ship to production. DORA's elite performers deploy on demand, often several times a day; low performers ship less than once a month.
Lead time for changes
Time from a committed change to running in production. Elite performers measure this in under an hour; a manual pipeline stretches it to days.
Change failure rate
The share of deployments that cause a failure needing a fix or rollback. Elite performers keep it the lowest of DORA's four performance tiers; fragile pipelines fail often.
Time to restore service
How long it takes to recover after a failed change, sometimes called MTTR. Elite performers restore in under an hour because rollbacks and monitoring are automated.

The engineers we embed are senior enough to know the infrastructure decisions that are cheap to make upfront and expensive to retrofit: stateless application servers, secret rotation processes, environment parity, and the monitoring that tells you what broke before your customers start the support ticket.

What we deliver

How embedded DevOps engineers work

  • 01
    CI/CD pipeline setup and automation

    CI/CD pipelines that test, build, and deploy automatically on every push, with layer caching cutting a 3-minute install to 15 seconds and tagged releases hitting production behind a manual approval gate. Security scanning is wired into the pipeline and runs in parallel, so checks add no sequential time.

    Built with
    GitHub Actions · GitLab CI · Trivy · Snyk · Semgrep
  • 02
    Infrastructure as code with Terraform

    Infrastructure defined in code and committed to version control, so every VPC, database, and service is reproducible from a single apply and every change is a reviewed pull request with a plan showing exactly what will change. Misconfigurations are caught before production, each PR is annotated with its monthly cost impact, and drift detection flags resources changed outside the pipeline.

    Built with
    Terraform · tfsec · Checkov · Infracost
  • 03
    Container orchestration and Kubernetes

    Docker containerisation with multi-stage builds that shrink a 1.2GB development image to a 180MB production image with a smaller attack surface. Kubernetes deployment with charts parameterised per environment, autoscaling matched to the workload, and resource limits that come from profiling, not guesses.

    Built with
    Docker · Kubernetes · Helm · KEDA
  • 04
    Monitoring, alerting, and incident response

    Observability at three levels: infrastructure metrics, application metrics, and business metrics like payment success rate that surface failures infrastructure monitoring cannot see. Distributed tracing turns a 2-hour latency hunt into a 2-minute diagnosis, alerts fire on sustained conditions rather than single events, and runbooks document the most likely failure scenarios before an incident.

    Built with
    OpenTelemetry · RED method

Dedicated team vs staff augmentation vs managed service

Dedicated DevOps team (RaftLabs)Staff augmentationManaged service
Who owns deliveryEngineers embed and own the outcome with your teamYou direct each contractor task by taskVendor runs it behind an SLA, off your board
Context retentionLearns your stack and stays across the engagementRamp-up cost repeats with every new contractorLimited to what the runbook already covers
Where the knowledge livesIn your team, documented in Terraform and runbooksLeaves when the contract endsHeld by the vendor, not you
Best fitBuilding CI/CD, IaC, and observability you keepFilling a short-term seatHands-off ops once the platform is stable
PricingFixed monthly rate per engineerHourly or dailyMonthly SLA fee

Pitfalls we plan around

Most infrastructure damage is self-inflicted. These are the failure modes we design against from day one, not after they page someone at 2am.

Kubernetes before you need it
A single service on stable traffic does not repay the operational overhead of a cluster. We right-size to AWS ECS or Cloud Run when that fits, and reach for Kubernetes only when microservices or variable load justify it.
Alert fatigue
An alert on every 5xx trains the team to ignore the pager. We alert on sustained conditions tied to user impact, so a page means something is actually wrong.
Infrastructure drift
Resources changed by hand in the console diverge from what Terraform believes exists. We run drift detection and route every change through a reviewed pull request.
Secret sprawl
Credentials in env files, CI logs, and Slack messages leak eventually. We centralise secrets in a managed store with rotation and least-privilege access.

Need DevOps engineers embedded in your team?

Tell us what your current deployment process looks like, where infrastructure is causing pain, and what cloud environment you're running on. We'll match you with the right engineers and get them started within a week.

What clients say

What our clients say

Three-year average engagement. Founders and operators describing the work in their own words. No marketing varnish.

Charles E.
Charles E.
USA flagUSA
Entrepreneur at Aggie Technologies

All of the sprints were completed on schedule and on budget. We highly recommend RaftLabs!

Stay on topic

More on dedicated teams & hiring

Frequently asked questions

Kubernetes solves specific problems: running multiple service instances, automatic failover, rolling deployments without downtime, and auto-scaling based on load. If your application is a single service running on one or two servers with stable traffic, Kubernetes adds operational complexity without meaningful benefit. AWS ECS, Google Cloud Run, or Railway is simpler and cheaper. If you have microservices, variable traffic, or need multi-region resilience, Kubernetes is the right foundation. We assess your architecture, traffic patterns, and team before recommending.

Infrastructure as code means your cloud environments (VPCs, subnets, security groups, databases, load balancers, compute instances) are defined in Terraform files committed to version control. The practical outcomes: you can recreate any environment in minutes, not days. Every infrastructure change is a reviewed pull request with a plan output showing exactly what will change. New environments (staging, a new region, a client-specific deployment) are spun up from the same config. No more 'I think I set that up six months ago and I'm not sure what it is.' We use Terraform with remote state in S3 or GCS and workspace separation between environments.

We set up monitoring at three levels: infrastructure metrics (CPU, memory, disk, network), application metrics (request rate, error rate, latency, the RED method), and business metrics (orders processed, payments succeeded, jobs completed). For alerting: PagerDuty or OpsGenie integration with sensible thresholds, not an alert for every 5xx, but an alert when error rate crosses a threshold for a sustained period. We document runbooks for the five most likely failure scenarios so your team knows how to respond before an incident happens.

A senior DevOps engineer typically runs $4,000 to $7,000 per month depending on the cloud platform, tooling depth (Terraform, Kubernetes, security automation), and engagement scope. Project-based engagements (pipeline setup, Kubernetes migration, IaC build) are scoped at a fixed cost. Ongoing embedded support retainers are priced by the week. We quote after a call to assess your current infrastructure and what the engagement needs to deliver.

Yes. Most engagements start with an audit of what exists, what's defined in code, what was created manually, what's undocumented. We then decide together what to migrate to IaC, what to leave as-is, and what to replace. We don't insist on a full rebuild. If your EC2 setup is working and the only issue is a missing CI/CD pipeline, we fix the CI/CD pipeline.

We build compliance-aligned infrastructure from the start rather than retroactively mapping controls to an existing setup. For SOC 2: encryption at rest and in transit, IAM least-privilege policies, audit logging (CloudTrail, AWS Config), automated evidence collection for change management controls, and network segmentation. For HIPAA: PHI encryption at rest (AES-256), encrypted backups with access controls, audit trails for all PHI access, and a BAA in place with cloud providers. We document the controls we put in place so your compliance team has the evidence they need for audit.

Work with us

Tell us what you need. We'll tell you what it would take.

We scope Dedicated DevOps & Cloud Team in 30 minutes. You walk away with a clear cost, timeline, and approach. No commitment required.

  • Scope and cost agreed before work starts. No surprises. No obligation.
  • Working prototype within 3 weeks of kickoff.
  • Pay by milestone. You see progress before each invoice.
  • 60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
  • All conversations are NDA-protected.