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Transforming IT Operations

Site Reliability Engineering Model

Helping IT Teams reduce incidents, eliminate repetitive tasks, and optimize costs.

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What is Site Reliability Engineering?

SRE applies software engineering principles to operations to create more reliable, scalable, and efficient systems. At Nisum, we integrate AI, machine learning, automation, and reliability metrics (SLIs/SLOs) to move from reactive management to predictive and proactive operations, designed to scale without losing stability.

Confiabilidad por diseño

Reliability by design

Architectures and operations designed to minimize failures and maximize availability from the start.

 

Execution Gaps

Automation and TOIL reduction

We eliminate manual and repetitive tasks through intelligent automation and self-service.
Observabilidad de extremo a extremo

End-to-end observability

Unified visibility of technical and business metrics to detect, correlate, and anticipate incidents.
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Our SRE Model

Shared responsibility and data-driven decision-making.

SLI SLO SLA

SLI / SLO / SLA

Error Budgets

Error Budgets

Observability and Telemetry

Observability and Telemetry

Automation and Runbooks

Automation and Runbooks

Incident Management

Incident Management

Blameless postmortems

Blameless Postmortems

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Key Benefits

Nisum’s SRE approach enables organizations to operate with greater stability, reduce operational costs, and respond faster to incidents—without slowing innovation or digital growth.

+30%

Reduction in operational costs

Average across enterprise clients

95%

Reduction in detection time (MTTD)

80%

Reduction in resolution time (MTTR)

Higher availability of critical platforms

Higher availability of critical platforms

Better incident prioritization

Better incident prioritization

Reduced operational load (TOIL)

Reduced operational load (TOIL)

Decisions based on technical and business metrics

Decisions based on technical and business metrics

Scalability without linear team growth

Scalability without linear team growth

SRE Model Components

A structured architecture that enables intelligent, governed, and scalable AI agents.

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Reliable Design and Architecture

Architectures designed to scale without compromising stability.

  • Scalable (microservices-based)
  • High availability and redundancy
  • Integration with internal and external systems
Observability and Operational Intelligence

Observability and Operational Intelligence

Clear visibility to detect, understand, and anticipate issues.

  • Monitoring of applications, infrastructure, and business data
  • Custom dashboards
  • Anomaly detection and root cause analysis with AI/ML
Automation and Continuous Improvement

Automation and Continuous Improvement

Fewer manual tasks, greater operational efficiency.

  • Automation of incidents, changes, and validations
  • Continuous TOIL reduction
  • Evolution toward predictive operations and self-remediation
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Nisum

 

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