Cloud Engineering & DevOps
Cloud-Native Engineering: Elastic, Resilient, and Cost-Optimized.Sub-Headline: We build future-proof “Supercloud” architectures. From Platform Engineering to FinOps,we turn your infrastructure into a competitive advantage, ensuring scalability without the financialhangover
Differentiators
Engineering for Value
The cloud powers digital business. Akhila Labs tunes it for scalability, security, and cost efficiency through modern
text-align: center;cloud-native engineering.Through cloud-native engineering, containerization, platform automation, and FinOps-driven cost governance
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The Platform Engineering Mindset
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FinOps & Unit
Economics
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Multi-Cloud & Hybrid Mastery
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Embedded
Platforms delivered
Engineering for Value
Every design choice is guided by business impact
The Platform Engineering Mindset:
We don’t just hire DevOps engineers; we build “Product Teamsfor Infrastructure.” We create IDPs that treat developers as customers, providing golden paths fordeployment that ensure compliance and security by default.
FinOps & Unit Economics:
We move the conversation from “How much is the bill?” to “What is thecost per transaction?” We implement tagging strategies, budget anomalies alerts, and auto-scalingrules (including Spot Instance orchestration) to ensure your cloud spend aligns perfectly withbusiness value. 27
Multi-Cloud & Hybrid Mastery:
Leveraging the concept of “Supercloud,” we design architecturesthat are portable. Whether you need to run on AWS, Azure, or a secure on-premise cluster due todata sovereignty regulations, our containerized solutions (Kubernetes)ensure consistency. 25
Technical Capabilities Deep Dive
We deconstruct monoliths.
- Microservices Architecture: Designing loosely coupled services that can be deployedindependently.
- Serverless: Utilizing AWS Lambda, Azure Functions, and Google Cloud Run to build event-drivenapplications that scale to zero when not in use, eliminating idle capacitycosts. 25
- SaaS Re-platforming: Converting single-tenant legacy apps into multi-tenant SaaS platforms with
Automation is our religion.
- Infrastructure as Code (IaC): We define all infrastructure using Terraform, Ansible, or Pulumi. Thisensures environments (Dev, Test, Prod) are identical and eliminates”configuration drift.”
- CI/CD Pipelines: Building robust pipelines (Jenkins, GitLab CI, GitHub Actions) that includeautomated testing, security scanning (SAST/DAST), and blue/green deployment strategies to ensurezero-downtime releases. 26
Turning raw data into insights.
- Data Lakes & Warehouses: Architecting scalable storage on S3/Data Lake or Snowflake/Redshift.
- ETL/ELT Pipelines: Orchestrating complex data flows using Apache Airflow or AWS Glue to clean,transform, and prepare data for AI/ML consumption
Embedded Engineering That Unlocks
the Full Potential of Silicon
Cloud Providers
Amazon Web Services (AWS), Microsoft Azure,Google Cloud Platform (GCP)
Containerization
Docker, Kubernetes (EKS, AKS, GKE), Helm, Istio(Service Mesh)
Infrastructure as Code
Terraform, AWS CloudFormation, Ansible,Pulumi, Crossplane
CI/CD
Jenkins, GitLab CI, CircleCI, ArgoCD (GitOps),GitHub Actions
Monitoring/Observability
Prometheus, Grafana, ELK Stack (Elasticsearch,Logstash, Kibana), Datadog, AWS CloudWatch
Database/Data
PostgreSQL, MySQL, MongoDB, DynamoDB,Snowflake, Apache Kafka, Redis
Industries Served
FinTech
High-frequency trading platforms requiring low latency; PCI-DSS compliant paymentgateways; Fraud detection pipelines.
Healthcare
HIPAA/GDPR compliant cloud storage for medical records (EHR); Interoperability layersusing FHIR standards.
E-Commerce
Auto-scaling architectures to handle “Black Friday” traffic spikes; Recommendation
engines.
Frequently Asked Questions
At Akhila Labs, embedded engineering is the foundation of everything we build. We go beyond writing firmware that runs on hardware—we engineer systems that extract
maximum performance, reliability, and efficiency from the silicon itself.
Can you integrate LiDAR, cameras, and other sensors for autonomous navigation?
Yes. We design sensor fusion pipelines using EKF/UKF, implement SLAM for GPS-deniedenvironments, and integrate multiple sensor modalities (LiDAR, RGB, depth, radar) for robustautonomous navigation.
How do you test autonomous drone behavior before real-world deployment?
We use simulation-first development with PX4 SITL/HITL in Gazebo/Ignition for virtualenvironments, hardware-in-the-loop rigs, and staged field trials with progressive autonomylevels
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