Varanasi, UP- IN
DevOps & Cloud Engineering
Ship faster, fail safer, and run lean—automation, observability, and security by design.
DevOps & Cloud Engineering
We build cloud platforms and delivery pipelines that turn releases into routine, not roulette. From IaC (Infrastructure as Code) and CI/CD to Kubernetes/serverless and policy-as-code, our approach is pragmatic: shorter lead times, fewer incidents, tighter feedback loops, and predictable costs. We design with clear SLOs (service level objectives), SLIs (latency, errors, saturation), and error budgets so engineering velocity and reliability stay in balance.
Under the hood: Terraform-based environments; GitHub Actions/GitLab CI with parallel tests and artifact caching; progressive delivery (blue/green, canary, feature flags); EKS/GKE/AKS or serverless (Lambda/Cloud Functions) where it fits; OpenTelemetry tracing with Prometheus/Grafana and log pipelines; hardened IAM, VPC segmentation, KMS-backed encryption, and secrets hygiene (Vault/SM). We align with compliance needs (ISO/SOC, PCI-DSS, HIPAA where applicable, India’s DPDP Act/GDPR) and wire cost guardrails from day one.
Architecture & Automation that Scale Without Drama
We start with a reference architecture tuned to your workloads: multi-account projects, least-privilege IAM, secure network topologies, and environment parity (dev/stage/prod) expressed entirely in Terraform. Delivery flows are automated end-to-end—build, test, scan, sign, deploy—with quality gates (SAST/DAST/dependency checks), container image hardening, and SBOMs for provenance. On the runtime side, we use Kubernetes with autoscaling, HPA/VPA, and resource quotas—or managed/serverless services for spiky or event-driven systems. Progressive rollouts, database migration strategies, and zero-downtime playbooks are standard, so releases stay boring and reversible.
Reliability, Security, and Cost You Can Measure
Operations run on numbers, not vibes. We define SLOs and alerts that reflect user experience; add golden signals (latency, traffic, errors, saturation); and expose dashboards for p95/p99, error budgets, deploy frequency, MTTR, and change failure rate. Backups/DR are explicit (RPO/RTO), with cross-region replication and tested restores. Security baselines follow CIS benchmarks, KMS-managed keys, rotation policies, WAF and rate limits, and policy-as-code (OPA/Conftest). FinOps is built in: tag taxonomies, budgets and alerts, rightsizing and autoscaling, storage lifecycle policies, and commitment strategies (Savings Plans/CUDs) with unit-cost telemetry per product or team.
Frequently Asked Questions
A typical greenfield baseline (accounts, networking, Terraform, CI/CD, observability, security guardrails) takes 2–4 weeks, depending on scope and compliance.
Primarily AWS and GCP (Azure on request). Tooling includes Terraform, Docker, Kubernetes (EKS/GKE/AKS), GitHub Actions/GitLab CI, Argo CD/Flux, Helm, OpenTelemetry, Prometheus/Grafana, and Vault/Secrets Manager.
Least-privilege IAM, VPC isolation, KMS encryption, secret management, vulnerability scanning, SBOMs, and audit logs. We map controls to ISO/SOC, PCI-DSS, HIPAA (where needed), and data-protection laws like GDPR and India’s DPDP Act.
Yes. We implement cost tagging, budgets and anomaly alerts, rightsizing, autoscaling, storage lifecycle tiers, and commitments (Savings Plans/CUDs)—guided by SLOs so savings don’t hurt user experience.
We can run SLO-backed managed services with on-call rotations, runbooks, escalation paths, and post-incident reviews to keep learning compounding.
Absolutely. We begin with a posture and cost audit (security, reliability, performance, spend), stabilize the hot spots, then migrate to IaC and progressive delivery without disrupting teams.
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