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MicrocosmWorksInnovere og Arkitektere Digitale Kosmos
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MicrocosmWorksInnoverer og arkitekterer digitale kosmos

Leverer IT-løsninger, der betyder noget. Vi brænder for teknologi, sikkerhed og at hjælpe virksomheder med at vokse gennem pålidelig, innovativ IT-infrastruktur.

[email protected]
+91 7011868196
New Delhi, India

Løsninger

BygAI ProduktudviklingSaaS ProduktudviklingSkræddersyet Softwareudvikling
ModerniserSoftwaremoderniseringAI-moderniseringCloud App-modernisering
SkalerBackend & Distribuerede SystemerCloud YdelsesingeniørPålideligheds- og YdelsesingeniørAI-infrastruktur
UdvidProduktudviklingsteams
Alle løsningerAI AgentudviklingAI VideoplatformSundhed & Fitness Apps

Tjenester

Digital RådgivningCloud InfrastrukturSaaS UdviklingAI UdviklingVideo Teknologi
ERP UdviklingZoho TilpasningOdoo UdviklingSalesforce-integrationTilpasset CRM Udvikling
QuickBooks-integrationIoT LøsningerBlockchain Udvikling
Cybersikkerhed RådgivningIT-support - L3

AI Væksthub

AI HubStartup-innovationVirksomhedsaccelerator

Ressourcer

IndsigterIndustri GuiderBrugssag BlueprintsArkitektur MønstreCase Studier

Virksomhed

Om OsKontaktDiskuter dit projektVores Arbejde

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Scale • Cloud & Performance Engineering

Cloud & Performance
Engineering

Optimize cloud infrastructure for performance, reliability and cost efficiency - ensuring applications run fast, stay available and scale economically.

Discuss Your Cloud PerformanceView Case Studies
25+
Engineers
40+
Clients
58
Case Studies
Cloud
Infrastructure • DevOps • Performance
P95 Latency
<50ms
Throughput
3x Faster
Cost Reduced
40%
Infrastructure
Auto-Scale

Cloud Engineering Services

From cost optimization and performance tuning to auto-scaling architecture and full observability - we engineer cloud infrastructure for efficiency at scale.

Cloud Architecture Optimization

Review and redesign cloud architecture for performance, cost and operational efficiency

Auto-Scaling Design

Implement horizontal and vertical auto-scaling based on CPU, memory, request rate and custom metrics

Cost Optimization & FinOps

Audit cloud spend, implement right-sizing, reserved instances, spot instances and cost governance

Engineering Capabilities

We combine performance analysis, cost optimization, infrastructure architecture, database tuning and SRE practices into a unified cloud engineering capability.

Performance Analysis

  • Application profiling
  • Bottleneck identification
  • Latency analysis
  • Resource utilization audit

Cloud Optimization Approach

A structured approach to cloud optimization - from performance audit through infrastructure tuning, load testing and continuous improvement.

01

Performance & Cost Audit

Analyze current infrastructure, identify waste, measure performance baselines

02

Optimization Strategy

Prioritize improvements by impact - quick wins and architectural changes

03

Infrastructure Optimization

Implement right-sizing, auto-scaling, caching and cost governance

04

Performance Tuning

Application-level optimization - query tuning, caching, CDN and connection management

05

Load Testing

Comprehensive testing to validate improvements and identify remaining bottlenecks

06

Monitoring & Alerting

Implement observability stack with dashboards, alerts and SLO tracking

Technology Stack

The exact stack is selected based on infrastructure requirements - not a fixed technology mandate.

Cloud Platform

☁️AWS EC2 / ECS
⚡AWS Lambda
🗄️AWS RDS / ElastiCache
🌐AWS CloudFront / S3

Infrastructure

🏗️Terraform
🐳Docker / Kubernetes

Related Solutions

Explore related capabilities that complement cloud performance engineering.

Reliability & Performance Engineering

SRE practices, observability, incident response and SLO management for production systems.

Explore

Backend & Distributed Systems

Scale backend architecture with event-driven systems, microservices and distributed processing.

Explore

Cloud Performance Use Cases

We optimize cloud infrastructure across industries and use cases - from cost reduction and auto-scaling to multi-region deployment and full observability.

Cloud Cost Reduction

Reduce monthly cloud spend through systematic optimization

Application Performance

Improve response times and throughput for production applications

Auto-Scaling Design

Implement demand-based scaling that balances performance and cost

Database Optimization

Resolve database bottlenecks through tuning, caching and architecture

CDN & Caching Strategy

Optimize content delivery and caching for global performance

Load Testing Program

Establish continuous load testing to prevent performance regression

FinOps Implementation

Build cost governance practices, budgets and optimization reviews

Infrastructure Right-Sizing

Match compute resources to actual workload requirements

Engineered for Efficiency

We engineer cloud infrastructure for production - optimized for cost, performance, scalability and reliability.

Cost Reduction

Systematic optimization to reduce cloud spend while maintaining performance

Performance

Latency optimization, caching, CDN and efficient resource utilization

Scalability

Auto-scaling architecture that grows and shrinks with demand

Engineering Team Model

The team is structured around your infrastructure needs, not a fixed package. Team composition adapts based on optimization requirements.

2-Person Squad

Focused optimization initiative. Performance audit, cost reduction or specific infrastructure improvement.

3-Person Squad

Comprehensive cloud optimization. Infrastructure modernization, auto-scaling and observability implementation.

5-Person Squad

Full cloud engineering with Technical Lead, Cloud Engineer, SRE, Backend Engineer and DevOps.

How We Work Together

A flexible engagement model that grows with your infrastructure - from initial audit to long-term cloud engineering partnership.

1

Performance & Cost Audit

Analyze infrastructure, identify optimization opportunities, measure baselines

2

Optimization Plan

Prioritize improvements, design architecture changes, estimate impact

3

Implementation

Execute optimizations with a dedicated cloud engineering team

4

Cloud Engineering Team

Ongoing team embedded in your infrastructure for continuous optimization

5

Relevant Case Studies

Serverless Video Processing Pipeline with AWS MediaConvert
Video Encoding

Serverless Video Processing Pipeline with AWS MediaConvert

The video platform needed a scalable, cost-effective way to handle variable encoding workloads, from quiet periods with few uploads to peak times with hundreds of simultaneous jobs.

AWS LambdaAWS MediaConvertAWS S3

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An end-to-end streaming infrastructure built for Maponga Studios — spanning a React Web App for asset and channel management, a sister Encoder App with SSO, a NestJS backend, and two AWS Lambda functions orchestrating MediaLive, MediaPackage, MediaTailor, and MediaConvert for one-click FAST channel deployment with SCTE-35 ad insertion.

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Need Better Cloud Performance?

Tell us about your cloud infrastructure, performance challenges and cost concerns. We will audit your setup and recommend optimizations.

Discuss Your Cloud PerformanceView Case Studies

Performance & Load Testing

Design and execute load testing strategies that establish baselines and identify breaking points

CDN Optimization

Implement and optimize content delivery for static assets, API responses and media files

Database Performance Tuning

Optimize through query analysis, indexing, connection pooling, read replicas and caching layers

Caching Strategy Design

Multi-layer caching - CDN, API response caching, application-level caching and cache invalidation strategies

Monitoring & Observability

Comprehensive monitoring covering infrastructure metrics, application performance and cost tracking

CI/CD Pipeline Optimization

Optimize deployment pipelines for speed, safety and reliability with automated testing and canary deploys

Security Hardening

IAM policies, network security, encryption, secrets management, vulnerability scanning and compliance

Capacity planning

Cost Optimization

  • Resource right-sizing
  • Reserved instance planning
  • Spot instance strategies
  • Auto-scaling optimization
  • Cost allocation and governance

Infrastructure Architecture

  • Multi-AZ and multi-region design
  • Container orchestration (ECS/K8s)
  • Infrastructure as Code (Terraform)
  • Environment management
  • Disaster recovery planning

Database Optimization

  • Query performance tuning
  • Index optimization
  • Read replica and caching strategies
  • Connection pool management
  • Database scaling patterns

Observability & SRE

  • Monitoring stack implementation
  • SLO/SLA definition and tracking
  • Alerting and escalation policies
  • Incident response procedures
  • Capacity planning and forecasting
07

Ongoing Optimization

Continuous cost reviews, capacity planning and performance improvement

📦
AWS CDK
🔧Pulumi

Performance Testing

📊k6
🎯Artillery
🦗Locust
⚙️AWS Load Testing

Monitoring

🐕Datadog
📈Prometheus / Grafana
👁️CloudWatch
🔔PagerDuty

Cost Management

💰AWS Cost Explorer
🏥CloudHealth
📉Custom FinOps Dashboards

Cloud Application Modernization

Migrate on-premise systems to cloud infrastructure before optimizing performance.

Explore

Multi-Region Deployment

Distribute applications for global latency and availability

Observability Implementation

Full monitoring, alerting and SLO tracking

Reliability

Multi-AZ deployment, health checks, failover and disaster recovery

Observability

Complete monitoring with metrics, logs, traces and custom dashboards

Governance

Cost allocation, budget alerts, optimization reviews and compliance

Production Reference

Optimized cloud infrastructure for production applications, reducing monthly costs while improving response times and establishing auto-scaling for demand fluctuations.

Custom Team

Team composition adapts to infrastructure requirements. Can include database, security or FinOps specialists.

Long-Term Partnership

Strategic infrastructure partner for scaling, reliability and cost management

Fixed-scope engagements are available when requirements are sufficiently defined. The right investment depends on infrastructure scope, technical complexity, team composition and roadmap.

+6
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Vector Databases

Milvus Autoscaling on Kubernetes with EC2 and S3-Backed Persistent Storage

An AI platform with rapidly growing vector data (embeddings for search, recommendations, and RAG) needed their Milvus vector database to scale automatically based on query load and data volume — with durable, cost-effective storage that wouldn't be lost if pods restarted or nodes were replaced.

MilvusAmazon EKSKubernetes HPA+8
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On-Off Scaling Pattern for AI & Video Processing Workloads
GPU Infrastructure

On-Off Scaling Pattern for AI & Video Processing Workloads

An AI-powered video processing platform needed to handle highly variable workloads — from zero jobs during off-hours to hundreds of concurrent video processing and AI inference tasks during peak times — without paying for idle GPU and compute resources.

Node.jsMongoDBRunPod API+7
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An integrated fitness and nutrition platform delivering personalized coaching, meal planning, and workout management with AI-driven recommendations and multi-agent coaching system.

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Wellness Coach: Personalised Health & Wellness Platform

A comprehensive platform that empowers users to improve their overall health and well-being through personalised coaching and wellness programs with challenges, rewards, and real-time communication.

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