Every cloud infrastructure engagement covers the full path from architecture design to operational handover. We don’t deliver architecture diagrams and wish you luck — we build the system, deploy it, test it under load, and prove it works before your team takes over.
Cloud Infrastructure
Cloud platforms that survive production, not just demos
We design distributed backend systems, build deployment pipelines, instrument observability, and hand over cloud platforms your team can actually operate. When we hand over a system, the client’s team can run it. We don’t create dependency.
Why Clients Come to Us
Your platform shouldn’t keep you up at night
The clients who find us share common patterns: a platform that drops under load spikes, an infrastructure team that’s strong on features but too small to architect for scale, observability that’s fragmented across five different dashboards with no unified view, or deployment processes that are still manual and error-prone.
These aren’t failures of talent — they’re failures of infrastructure design. The system was built for launch, not for the traffic it’s handling now.
- 01
Platform goes down under unpredictable load
- 02
Infrastructure team is too small to architect at scale
- 03
System needs to scale without a full rewrite
- 04
Observability is fragmented or missing critical signals
- 05
Deployments are manual and error-prone
- 06
No capacity planning — scaling is reactive, not predictive
Technical Scope
Architecture, pipelines, and observability for production workloads
- Architecture design for distributed backends
API-centric platform engineering with clear service boundaries, failure isolation, and horizontal scaling paths.
- Multi-cloud deployment
AWS and GCP environments designed for workload-appropriate placement, not vendor lock-in.
- High-availability foundations
Failover architecture, redundancy engineering, and degradation paths that keep the system functional when components fail.
- Monitoring and observability stacks
Unified telemetry, structured logging, distributed tracing, and alerting that surfaces real problems instead of generating noise.
- CI/CD and deployment automation
Deployment pipelines that are repeatable, auditable, and fast enough that deployments stop being events.
- Capacity planning and load testing
Baseline performance measurement, load characterization, and scaling thresholds established before production, not after the first outage.
Engagement Model
From assessment to operational handover
Every engagement follows a structured arc designed to reduce risk and build confidence at each stage. We don’t disappear after deploying code — we prove the system works under production conditions before anyone calls it done.
- 01
Infrastructure assessment
Evaluate the current architecture, identify failure points, and establish performance baselines.
- 02
Architecture design
Design the target system with clear scaling paths, observability requirements, and operational handover criteria.
- 03
Iterative build
Build in stages with continuous validation, not a waterfall delivery six months from now.
- 04
Load testing
Prove the system handles production-level traffic before it sees production traffic.
- 05
Observability instrumentation
Instrument every critical path so your operations team has visibility from day one.
- 06
Deployment pipeline
Build CI/CD automation that makes deployments repeatable, fast, and auditable.
- 07
Operational handover
Transfer operational knowledge, runbooks, and ownership to your team. We don’t create dependency.
Proof of Delivery
GetLead: stabilizing cloud-native ad operations
GetLead, an ad operations platform by Mobility Media, came to CHERNOMOR with campaign stability issues and observability gaps. Their infrastructure was functional but fragile — traffic spikes caused cascading failures, and the team lacked visibility into root causes.
We redesigned the cloud infrastructure with high-availability architecture, built production-grade observability across the campaign pipeline, and established monitoring that surfaces real problems instead of generating alert noise. The result: stabilized campaign infrastructure and an operations team that can see exactly what’s happening in their system.
- SectorAdTech / Performance Marketing
- ChallengeCampaign instability and observability gaps under production load
- ScopeCloud infrastructure redesign, observability engineering
- OutcomeStabilized campaign infrastructure with production-grade observability
Connected Services
AI monitoring and compliance controls for cloud systems
Cloud infrastructure doesn’t exist in isolation. Our cloud platforms connect to two supporting capabilities that make them more resilient and audit-ready.
AI-assisted monitoring
ML-driven analysis applied to infrastructure telemetry — detecting anomalies before they become incidents and reducing alert fatigue for operations teams.
AI & Automation →Compliance controls in architecture
Audit trails, access controls, and traffic visibility designed into the cloud platform from day one — not retrofitted before an audit.
Compliance & Onboarding →Need a cloud platform that handles production load?
Tell us about your current infrastructure, what’s breaking, and what scale you need to reach. We’ll give you an honest assessment of what it takes.
Book an Infrastructure Review