Network Reliability Engineering Services

Overview

Reliability Isn't Added.
It's Engineered In.

HCLTech's Network Reliability Engineering (NRE) practice brings the discipline of software reliability engineering to enterprise networks—treating infrastructure as code, operations as a product and uptime as a measurable engineering commitment.

By combining NetDevOps, observability, GitOps and Agentic AI, NRE moves network operations from reactive, manual execution to intelligent, self-healing operations. The expected outcomes are higher availability, faster change velocity and lower cost to operate—measured, not claimed.

Networks have outgrown the way we run them. Environments are now multi-vendor, hybrid and software-defined, changing faster than manual operations can safely keep pace with—so failures have moved from hardware to configuration, change and human process.

At the same time, downtime has become a board-level financial risk, the talent to manage this complexity is thinning and alert noise is burying the signals that matter. NRE answers this by treating reliability as an engineering outcome, not an operational afterthought.

From execution to intelligence

Reliability is becoming a business KPI, talent is shifting toward reliability engineers, observability is replacing traditional monitoring and an automation-first approach is spreading across network operations. Analysts expect rapid and broad adoption through the rest of the decade.

HCLTech NRE Enablement Framework and Phased Approach to Adoption

HCLTech enables the ModernOps journey through a three-phase, GitOps-led approach built on three enablement submodules—best practices & culture, tools & platforms and talent & skills—powered by our Network to Code and AI Force.ITOps platforms.

Best Practices and Culture

SLO-driven reliability
Automation-first operations
Chaos engineering and resilience
RCA and closed-loop automation
Blameless culture, toil reduction

Proprietary Platforms and IP Tools

Single Source of Truth with intent layer
GitOps with iAutomate and Big AEX for remediation
SSOT and centralized dashboards with NaaC
Agentic AI with AI Force.ITOps
Cybersecurity and compliance

Talent and Skills

Operations and reliability engineering mindset
Network fundamentals
Knowledge of GitOps, CI/CD, Python
Basics of observability with AI basics
Ecosystem and alliances enablement

Reliability Delivered in a Phased Approach

A phased engagement model moves network operations from assessment to a self-healing, AI-driven state—building reliability in de-risked stages that each deliver value while compounding toward autonomy, up to 30–35% MTTR/MTTD gains and 45–50% toil reduction.

Phase 1	Assess & Baseline (1–3 months)
Focus	Establish the NRE foundation and baseline current maturity.
Key activities	NRE assessment; tools & process review; observability gap analysis; skill-gap & training plan; define NetDevOps goals aligned to SLO or SLI.
Outcomes	Source of Truth, KPI dashboards and a costed roadmap.

Phase 2	Foundation (2–6 months)
Focus	Stand up automation, observability and reliability processes.
Key activities	SoT creation; telemetry-based observability; gold config templates; NetDevOps pipeline & change management; agentic PoC.
Outcomes	50% self-healing, MTTR/MTTD baselining, NRE squads.

Phase 3	Maturity & Beyond (3–6 months)
Focus	Scale to predictive, AI-driven ZeroOps.
Key activities	SSOT expansion; chaos engineering; GitOps maturity; maturing AIOps use cases; policy orchestration via AI Force.ITOps.
Outcomes	30–35% MTTR/MTTD gains, 45–50% toil reduction, end-to-end observability.

Key Capabilities and Benefits for Your Businesses

HCLTech's NRE capabilities aren't features for their own sake—each engineering capability is tied directly to the reliability, cost and performance benefit it delivers

NRE Capabilities and benefits

Infrastructure as Code/NetDevOps

Network-as-code, golden-config templates, GitOps CI/CD pipelines

Safer change and fewer outages: versioned, tested pipelines with automated rollback cut change-related risk.

Single Source of Truth and intent-based automation

NaaC SSOT with continuous drift detection

Configuration consistency: actual state is continuously reconciled to intended state, eliminating drift.

Observability and AIOps

Telemetry with AI-driven event correlation

Faster resolution: correlation replaces manual triage and alert noise, cutting MTTR/MTTD.

Closed-loop, self-healing automation

Automated RCA and remediation (iAutomate, Big AEX)

Fewer, shorter outages and less toil: issues resolve without manual effort.

Agentic AI operations

AI Force.ITOps agents + GenAI multi-OEM provisioning

Lower operating cost: reliability scales through automation, not headcount.

SLO/SLI-driven reliability management

Reliability defined and governed as business KPIs

Predictable performance: reliability becomes measurable and consistent.

Chaos engineering and resilience testing

Digital-twin validation and fault injection

Protected revenue: resilience proven before production, tied to business SLAs.

Security and compliance by design

Governance, compliance checks, log anonymization

Built-in compliance: governance enforced automatically, lowering audit risk.

Reliability engineering talent model

T-shaped NRE engineers via Knowledge Academy and T2iD

Continuous improvement: blameless culture turns every incident into a permanent fix.

Why HCLTech

Reliability Engineered End-to-End

HCLTech delivers value across the entire network lifecycle—from Day 0 design to Day 2 self-healing operations—powered by proprietary platforms, a proven talent model and a mature ecosystem of alliances

Full-lifecycle coverage (Day 0–2)

Reliability designed in from the start—digital-twin validation and SLO-driven blueprints de-risk deployment, while zero-touch, standardized rollout eliminates change-related risk at scale.

Proprietary Platforms and IP

Golden-config templates live in the NaaC Source of Truth; a GenAI/LLM layer enables multi-OEM provisioning while AI Force.ITOps orchestrates incident, change and update agents for closed-loop remediation.

Self-healing operations

Closed-loop automation and unified observability cut MTTR/MTTD and toil, advancing the network up the L1–L4 autonomy ladder toward zero-ops.

NRE talent as a solution

T-shaped reliability engineers built across a defined competency ladder through the Knowledge Academy and T2iD upskilling, reinforced by internal and external certifications.