01 - Platform architecture
Cloud-native design and rollout
Reference architecture, environment strategy, and migration paths from legacy infrastructure to containerized platforms.
Cloud native reliability engineering
Mode: Production
SLO: 99.95%
Signal: Healthy
Engineer resilient platforms your team can run with confidence.
InfraYantra Labs designs and implements production systems across Docker, Kubernetes, PostgreSQL HA replication, JMeter performance testing, Prometheus, and Grafana. We combine architecture, implementation, and team enablement so your platform remains fast, observable, and recoverable.
- Discipline
- Evidence-led delivery with practical documentation
- Stack ethos
- Open tooling, cloud-native and portable patterns
- Engagement
- Advisory through implementation and handover
Trusted delivery model
Runbook-first operations
Training embedded in scope
Signal - topology
Live model
Illustrative model: interfaces, observability, and persistence aligned - how we think about resilient systems.
Capability pillars
Execution capability across platform, data, and operations
Beyond tools, these are the working capabilities we bring into every engagement to ensure delivery quality, operational reliability, and long-term ownership.
02 - Delivery engineering
Automation-first implementation
Repeatable build, release, and configuration workflows with guardrails that reduce deployment risk and manual drift.
03 - Data reliability
HA-first PostgreSQL operations
Replication design, failover readiness, and recovery discipline to keep data services resilient under real-world failure modes.
04 - Observability
Metrics, alerts, and diagnostics
Prometheus and Grafana ecosystems with actionable alerting, clear SLO signals, and low-noise incident workflows.
05 - Performance engineering
Capacity and bottleneck insight
JMeter-driven workload modeling, benchmark baselines, and tuning loops tied to latency, throughput, and scale targets.
06 - Team enablement
Training and documentation systems
Structured handover with runbooks, SOPs, onboarding docs, and role-based training so teams operate confidently without dependency risk.
Outcomes
What changes after engagement
We focus on measurable operational outcomes: lower incident noise, better recovery, predictable releases, and documented ownership across engineering teams.
Reliability posture
SLO-aligned
Alerting and dashboards tied to critical user journeys and business risk.
Release confidence
Predictable
Deployment runbooks, rollback paths, and environment parity from staging to production.
Failure recovery
Faster MTTR
Incident workflow, escalation routes, and failover drills practiced before critical events.
Team autonomy
High ownership
Technical training and documentation designed for onboarding and day-two operations.
Service matrix
What we deliver in execution order
The services below are arranged in the same sequence we execute in real client engagements: assessment, foundation, platform rollout, reliability hardening, performance validation, and team enablement.
Phase 1
Plan and baseline
Phase 2
Build and scale
Phase 3
Stabilize and transfer
Phase 1 - Strategy
Architecture, audit & delivery roadmap
Current-state assessment, target architecture, risk register, and phased implementation roadmap aligned to business priorities.
- Discovery
- Gap analysis
- Execution plan
Phase 1 - Foundation
Installation & configuration baseline
Secure installation and configuration of Linux services, middleware, and platform dependencies with verification checklists.
- Hardening
- Validation
- Standards
Phase 2 - Platform
Docker platform engineering
Container image strategy, secure base images, registry workflows, and runtime configuration for predictable releases.
Learn more ->- Dockerfiles
- Registries
- Runtime hardening
Phase 2 - Orchestration
Kubernetes operations
Cluster setup, workload deployment, ingress, autoscaling, secrets, and day-two governance for stable Kubernetes environments.
Learn more ->- Installation
- Configuration
- Upgrades
Phase 2 - Automation
DevOps implementation
CI/CD modernization, release governance, infrastructure workflows, and deployment automation that teams can sustainably own.
- CI/CD
- GitOps-ready
- Release controls
Phase 2 - Engineering
Application engineering & integration
Production-minded backend services, APIs, automation scripts, and integration workflows that support platform goals.
- APIs
- Automation
- Integration
Phase 3 - Data reliability
PostgreSQL HA replication
High-availability architecture, streaming replication, failover planning, and resilient backup/restore workflows.
Learn more ->- Primary/standby
- Failover drills
- Recovery targets
Phase 3 - Observability
Monitoring & observability
Instrumentation design and production dashboards with Prometheus and Grafana for fast diagnosis and confident operations.
Learn more ->- Prometheus
- Grafana
- Telemetry
Phase 3 - Operations
Alerting & incident readiness
Actionable alert rules, severity models, escalation paths, and response playbooks tuned to your service objectives.
Learn more ->- Thresholds
- On-call runbooks
- Postmortems
Phase 3 - Performance
JMeter performance engineering
JMeter test architecture, baseline and stress scenarios, bottleneck diagnostics, and optimization loops tied to business SLAs.
Learn more ->- Load / stress
- Soak tests
- Capacity planning
Phase 3 - Enablement
Technical training
Role-based technical training for SRE, platform, backend, and operations teams with guided labs and practical checklists.
Learn more ->- Kubernetes labs
- Postgres drills
- Observability workshops
Phase 3 - Knowledge systems
Documentation systems
Operational documentation that is searchable, versioned, and reliable under pressure across onboarding and incident scenarios.
Learn more ->- Architecture docs
- Runbooks
- SOPs
Integrated engagements
We can own complete delivery from architecture to production handover: platform setup, automation, database HA, monitoring, alerting, performance testing, documentation, and team training.
Engagement model
Advisory + implementation
Delivery format
Milestone-driven sprints
Handover quality
Runbooks + team readiness
Operations telemetry
stream: activeDeploy success
99.4%
Last 30 days
MTTR target
< 20m
Playbook-driven recovery
Alert quality
High
Actionable, low-noise rules
Training closure
100%
Labs + documentation handoff
Delivery framework
How we execute high-stakes platform work
A structured method with clear outputs at every stage. You always know current status, next milestone, and what your team receives at handover.
Operating principle
No black-box delivery: architecture, decisions, and runbooks stay transparent.
Control points
Weekly checkpoints with risk, progress, and acceptance criteria review.
-
1
Discover and align
We baseline architecture, constraints, risks, and business priorities to define an execution scope your stakeholders can approve quickly.
Output: assessment brief + risk map + delivery plan
-
2
Design and baseline
We define target architecture, standards, and reliability controls including rollout, rollback, observability, and security baselines.
Output: architecture spec + standards + acceptance criteria
-
3
Implement and validate
We execute in milestones: platform setup, automation, HA data paths, monitoring, alerting, and performance validation with evidence.
Output: production-ready stack + test evidence + runbooks
-
4
Transfer and scale
We complete structured handover with training, documentation, and operational drills so your team can scale delivery independently.
Output: trained team + SOPs + ownership handoff
FAQ
Frequently asked questions
Practical answers for teams evaluating platform engineering, reliability upgrades, and end-to-end DevOps implementation support.
What type of companies do you usually work with?
We typically work with product teams, SaaS companies, and enterprises that need stronger platform reliability, better release quality, and clearer operational ownership.
Do you install and configure Docker and Kubernetes from scratch?
Yes. We support greenfield setup, secure baseline configuration, workload onboarding, ingress setup, upgrades, and operational handover with runbooks.
Can you implement PostgreSQL high availability replication?
Yes. We design and implement PostgreSQL HA replication topologies, backup and recovery plans, failover playbooks, and validation drills.
Do you set up Prometheus, Grafana, and alerting pipelines?
Yes. We build metrics pipelines, dashboards, SLO views, alert rules, and escalation-ready incident documentation to reduce MTTR and alert fatigue.
Do you provide JMeter performance testing and tuning recommendations?
Yes. We create JMeter scenarios for load, stress, and soak tests, then convert findings into prioritized tuning actions for infrastructure and application teams.
What is included in technical training and documentation handover?
We include role-based training sessions, architecture notes, SOPs, runbooks, onboarding guides, and operational checklists tailored to your internal team structure.
How long does a typical engagement take?
Most focused implementations run from 4 to 12 weeks depending on complexity, existing stack maturity, and whether migration and team enablement are included.
How do you price projects?
We generally work on milestone-based scopes with clear deliverables. For ongoing support, we can define monthly retainers with agreed service boundaries.
Can you support after go-live?
Yes. We offer post-implementation stabilization, observability tuning, performance follow-ups, and advisory support while your team fully takes ownership.
Do you work with security and compliance requirements?
Yes. We align with security baselines, access controls, audit-ready documentation, and change governance practices required by regulated environments.
Contact
Build a platform your team can trust
Share your architecture, reliability goals, and delivery constraints. We will respond with a practical execution plan.
admin@infrayantra.comInfraYantra Labs - infrayantra.com