Do we need Kubernetes if we only have 1–2 servers?

Not necessarily. For small services, server pairs are enough: two servers behind a load balancer with automatic failover. Kubernetes is justified when there are multiple microservices, frequent deployments, or unpredictable load.

Server pairs or Kubernetes: which is the right choice?

It depends on the application architecture and the pace of change. A monolith on one or two machines suits server pairs: simpler to operate. Microservices or a high deployment frequency calls for Kubernetes: more expensive to launch, but provides autoscaling and consistent rollout rules. The choice is made after analysis.

Can you plug into our existing GitLab or GitHub?

Yes. CI/CD pipelines are configured in GitLab CI or GitHub Actions on top of the existing repository. No changes to the developers' code are required; only the pipeline configuration is added.

What if we already have CI/CD on Jenkins or TeamCity?

The existing tool can be kept or migrated to GitLab CI/CD. The decision is made based on the audit: pipeline scope, team convenience, and cost of ownership are evaluated. No forced migration.

How do we migrate production without downtime?

Migration runs in phases: the new stack is deployed in parallel, traffic is shifted gradually via DNS or load balancer. Rollback to the old stack remains possible at any time. Downtime is minimized to the cutover window.

How long does CI/CD launch take?

A basic pipeline with build, tests, and manual deploy launches in 1–2 weeks. Full automation with blue-green deployment, monitoring, and rollback takes 4 weeks and up. Specific timelines are fixed in the contract after the audit.

An NDA is signed before any work begins. Access to repositories and infrastructure runs through secure channels. Connections to client systems are restricted to assigned engineers only.

What happens if we cancel?

All access, configurations, pipelines, and documentation remain with the client. Handover follows an agreed schedule. There is no lock-in to our tools; the infrastructure runs on standard open solutions.

DevOps - Continuous Delivery Infrastructure

Deployment automation, fault-tolerant infrastructure, continuous delivery. New product versions ship faster. On failure, traffic switches to backup nodes automatically. Around-the-clock support.

Discuss the project

Who it fits - Formats for Different Team Maturity Levels

DevOps engages at different stages of development maturity: from a first CI/CD pipeline to complex cluster infrastructure.

SaaS product with frequent releases

The team deploys several times a day. Automation, blue-green, second-scale rollback are required.

Frequent deployments
CI/CD pipeline
Minimal downtime

Web services with unpredictable load

Marketplaces, media, e-commerce. Peak periods require autoscaling and high availability.

Autoscaling
Load balancing
High availability

Legacy infrastructure without CI/CD

Manual deployments, incomplete documentation, risk of errors at rollout. Transition to a reproducible model is needed.

Migration to CI/CD
Containerization
Documentation

Reinforcement for in-house development

Developers are in place, but a dedicated DevOps engineer is missing or overloaded. We take the infrastructure side.

Alongside development
Release support
No hiring needed

Kubernetes: service stays online through any failure

Your application runs across multiple servers. One server goes down - the service keeps running. Traffic reroutes to healthy nodes automatically in seconds.

Resources scale with real demand. Peak hours - capacity increases automatically. Off-peak hours - resources are released. No manual intervention required.

Implementation

Kubernetes
Automatic failover
Load balancing
Autoscaling
Zero-downtime updates
Helm
Redis

Server pairs: continuous availability for your business

Two servers run in parallel. If one fails, the other takes the full load automatically. Users keep working without interruption. Data syncs in real time.

Web servers, databases, and load balancers run in pairs. Failover takes seconds. Configuration stored in code. Recovery takes minutes.

Typical configurations

Web servers. Two or more servers behind a load balancer. A single failure is invisible to users.
Databases. Database servers run in sync. Primary fails - the standby accepts requests automatically. Data preserved.
Entry point. Load balancers run in pairs. Requests are never lost when a node goes down.

Technologies

HAProxy
Nginx
keepalived
MariaDB Galera
Redis Sentinel
GlusterFS

Infrastructure as code

Server configurations stored in code. Any server rebuilt from scratch in minutes using a ready template. Human error minimized.

Around-the-clock node management. Incident response, component updates, capacity planning. Scheduled maintenance in agreed windows. Monthly reports included.

Automation

Ansible
Git
Server provisioning
Service configuration
Cluster deployment
Access management
Network rules

CI/CD: from code to production in minutes

Updates move through an automated pipeline: build, test, deploy. Deployment automation via GitLab CI/CD. Manual steps eliminated. Deployment errors reduced to near zero.

GitLab CI/CD pipeline records test and deploy results. Rollback to a previous version takes seconds. Full change history available for audit.

Automation stages

Build and test. Code is built and tested automatically on every change. Bugs caught at an early stage.
Automated deploy. Update deployed to staging, verified, then promoted to production. Blue-green deployment eliminates downtime.
Health checks and rollback. Application metrics tracked after every deploy. Anomalies trigger automatic rollback to the stable version.

Technologies

GitLab CI/CD
Docker
Docker Registry
Blue-Green Deploy
Automatic rollback
Staging environment

Business impact - What this means for your company

Infrastructure that runs continuously and lets the business move faster.

Service continuity. One server failure does not stop operations. Failover happens automatically in seconds.
Faster releases. Deployment automation via GitLab CI/CD. Release cycles shortened, manual errors at deployment eliminated.
Predictable scaling. Resources grow with load. Peak periods do not degrade service performance.
Full reproducibility. Configuration lives in code. Losing a server is a routine procedure - recovery in minutes.
Management visibility. Monthly report: infrastructure status, incidents, response times, and recommendations.