Cloud Management Services

Enterprise Managed Cloud &
Cloud Operations Services

Run your cloud as a reliable, observable and continuously optimized operating environment.

Mobiloitte provides managed cloud and CloudOps services across AWS, Microsoft Azure and Google Cloud, helping enterprises monitor workloads, manage incidents, improve reliability, control cloud spend, strengthen security and automate repetitive operational work.

From observability and SRE to FinOps, lifecycle management and AI-assisted operations, we help technology teams move from reactive cloud support toward proactive, measurable and continuously improving cloud operations.

Request a Cloud Operations Assessment

What Are Managed Cloud Services?

Managed cloud services help organizations operate, monitor, secure, support and continuously optimize cloud environments after they have been deployed.

They can include infrastructure monitoring, incident and problem management, observability, cloud security operations, patching, backup and recovery, performance optimization, capacity management, FinOps and automation across public, private and hybrid cloud environments.

Modern CloudOps extends traditional infrastructure support by combining SRE practices, observability, automation and AI-assisted operations to improve reliability while reducing repetitive operational effort.

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Enterprise Managed Cloud
& CloudOps Capabilities

01.

Cloud Operations Assessment & Service Transition

Understand the environment before assuming operational responsibility.

  • Cloud accounts & subscriptions
  • Architecture & workloads
  • Monitoring & alerts
  • Backup & security
  • FinOps baseline
  • Service-transition plan
Output: Current-state assessment, service inventory, RACI matrix, and runbooks.
02.

Cloud Monitoring & Full-Stack Observability

Move beyond infrastructure dashboards toward operational visibility.

  • Metrics, logs, traces, events
  • Compute & databases
  • Containers & networks
  • Availability & latency
  • Service health & dependencies
Important Principle: Monitoring tells you something changed. Observability helps explain why.
03.

Incident, Problem & Change Management

Operate cloud services using defined service-management workflows.

  • Detect, prioritize & escalate
  • Investigate recurring failures
  • Plan & review infrastructure changes
  • Post-Incident Reviews
The objective should be continuous operational learning, not blame.
04.

Site Reliability Engineering

Apply engineering practices to improve cloud-service reliability.

  • Service Level Indicators (SLIs)
  • Service Level Objectives (SLOs)
  • Error budgets
  • Toil reduction
  • Resilience engineering
Do not define cloud-management quality only through ticket response time. Measure the reliability of the actual service.
05.

AIOps & Intelligent Cloud Operations

Use AI and automation to help operations teams manage increasingly complex cloud environments.

  • Event correlation
  • Anomaly detection
  • Alert prioritization
  • Root-cause assistance
  • Runbook automation
  • Predictive operations
Automation should define: What can execute automatically → What requires approval → What must remain human-controlled.
06.

FinOps & Cloud Financial Management

Turn cloud consumption into something engineering, finance and business teams can understand.

  • Cost allocation & tags
  • Budgets & chargeback
  • Rightsizing & idle resources
  • Cost anomalies
  • Unit economics
FinOps is not simply reducing the bill. It is about balancing: Cost + Performance + Reliability + Business Value.
07.

Performance & Capacity Management

Continuously evaluate how workloads consume cloud resources.

  • CPU & Memory
  • Database utilization
  • Queue depth
  • Scaling behavior
  • Capacity planning for growth
Performance optimization should protect application requirements rather than simply minimizing resources.
08.

Cloud Security Operations

Maintain cloud-security controls as the environment changes.

  • Security monitoring
  • Identity & access review
  • Configuration drift detection
  • Vulnerability management
  • Encryption controls
Security posture changes continuously. A secure architecture on launch day does not guarantee a secure environment six months later.
09.

Patch, Configuration & Lifecycle Management

Cloud resources and underlying software require continuous lifecycle management.

  • OS patching
  • Package updates
  • Configuration management
  • Certificate tracking
  • End-of-life monitoring
Goal: Reduce operational risk created by inconsistent or obsolete infrastructure.
10.

Backup, Recovery & Resilience Operations

Verify that backup and recovery processes continue working after the initial architecture has been deployed.

  • Backup jobs & failures
  • Retention & replication
  • Recovery runbooks
  • RTO/RPO validation
  • DR readiness testing
Key Principle: Successful backup is not the same as successful recovery. Recovery must be validated.
11.

Hybrid & Multi-Cloud Operations

Operate workloads consistently where an enterprise uses combinations of environments.

  • AWS, Azure, GCP
  • Private cloud & on-premise
  • Common monitoring
  • Service management
  • Governance & cost visibility
Do not promise a 'single pane of glass' unless you genuinely provide the platform architecture to deliver it.
12.

Cloud Governance & Service Management

Create an operational governance model covering access, reporting, and reviews.

  • Resource ownership
  • Tags & budgets
  • Policy drift
  • Escalations & change control
  • Operational reviews
Governance should create clarity and repeatability, not unnecessary operational bureaucracy.
Request a Cloud Operations Assessment

How a Modern Cloud Operations Model Works

Across Every Layer: Identity • Security • Auditability • Automation Controls • Human Approval

Cloud & Application Telemetry

MetricsLogsTracesEventsHealth signals

Observability Layer

DashboardsDependency mapsService healthSLO visibility

Event & Intelligence Layer

CorrelationAnomaly detectionPrioritizationAIOps insights

Service Management Layer

IncidentsProblemsChangesRequestsEscalations

Automation Layer

RunbooksProvisioningRemediationScalingWorkflows

Optimization Layer

SREFinOpsCapacitySecurityPerformance

Governance & Reporting

Service reviewsCost reportsReliability reportsPostureBacklog

Managed Cloud Service Lifecycle

From Service Transition to Continuous Improvement

01 — Assess

Review cloud environment, architecture, workloads, monitoring, costs, security, and operational processes.

02 — Transition

Define scope, RACI, escalations, service levels, runbooks, access, and communication.

03 — Establish Baselines

Capture reliability, performance, cost, incident volume, capacity, and operational toil.

04 — Instrument

Implement or improve monitoring, logging, tracing, alerting, dashboards, and service objectives.

05 — Operate

Manage events, incidents, problems, changes, backups, lifecycle activities, and requests.

06 — Automate

Identify repetitive work suitable for runbook automation, self-service, and safe remediation.

07 — Optimize

Continuously improve cost, performance, reliability, capacity, security, and operational effort.

08 — Review & Evolve

Use service reviews and production evidence to prioritize improvements and modernization.

Engineer Cloud Reliability Around Business Requirements

Site Reliability Engineering (SRE)

Service Level Indicators: Measure signals such as Availability, Latency, Errors, Throughput, and Durability.

Service Level Objectives: Define the expected performance of a service over a defined period.

Error Budgets: Where appropriate, balance reliability requirements with the ability to release changes.

Incident Metrics: Track MTTA, MTTR, Incident recurrence, and Business impact.

Change Reliability: Measure Change failure rate, Rollback rate, and Failed deployments.

Operational Toil: Identify repetitive manual activities that engineering or automation can remove.

Infosys' managed-cloud model explicitly moves mature enterprises toward SRE using SLI/SLO-based operating models rather than relying only on ITIL ticket metrics, while Capgemini similarly embeds SRE into its cloud-management model.

Engineer Cloud Reliability Around Business Requirements

Connect Cloud Spend With Business Ownership

FinOps & Cloud Financial Management

Visibility: Understand spending by Application, Team, Environment, Business unit, Product, or Cloud service.

Allocation: Establish Tags, Accounts/subscriptions, Cost centers, and Ownership.

Optimization: Continuously evaluate Rightsizing, Commitments, Idle resources, Storage, Autoscaling, and Workload placement.

Forecasting: Monitor Budgets, Variance, Growth, Anomalies, and Expected demand.

Governance: Define who can make cost decisions and how optimization opportunities move from recommendation to implementation.

Unit Economics: Where possible, connect spend with meaningful business units (Cost per transaction, customer, workload, inference).

Capgemini, IBM, Cognizant and Infosys now all treat FinOps as a continuous cloud-operations capability rather than an occasional optimization exercise.

Connect Cloud Spend With Business Ownership

AIOps & Controlled Cloud Automation

Intelligent Operations at Scale

AI-assisted operations can help teams process operational signals at a scale that becomes difficult to manage manually.

  • Detect: Identify unusual behavior from cloud and application telemetry.
  • Correlate: Group related alerts and events to reduce operational noise.
  • Prioritize: Help teams identify incidents with the greatest service or business impact.
  • Investigate: Summarize context and surface likely contributing factors.
  • Recommend: Suggest remediation based on approved operational knowledge.
  • Automate: Execute selected safe, tested and reversible operational workflows.
  • Learn: Use incident history and operational outcomes to improve runbooks and detection.
Governance: Critical, irreversible or high-risk changes should retain appropriate human approval.

AIOps & Controlled Cloud Automation

Cloud Security Operations & Governance

Security as a Continuous Day-2 Operation

Security should remain part of Day-2 cloud operations rather than being treated as a one-time configuration activity.

Identity: Monitor privileged access, roles, service identities and permissions.

Configuration: Detect configuration changes and policy drift.

Vulnerabilities: Support appropriate scanning, prioritization and remediation workflows.

Logging: Maintain the operational and security logs required by the environment.

Data Protection: Monitor relevant encryption, backup and secrets-management controls.

Incident Response: Coordinate operational response where cloud-security events affect managed services.

Compliance Support: Cloud controls, operational evidence and reporting can support applicable requirements. Compliance must be evaluated across technology, processes, policies and organizational responsibilities—not inferred from cloud management alone.

Cloud Security Operations & Governance

Define the Managed Cloud Service Around Your Operating Requirements

Service Model & SLAs

Managed-cloud coverage should be agreed according to workload criticality and business requirements.

Service Scope: Infrastructure, Platforms, Databases, Containers, Selected application signals, Security operations.

Coverage: Business-hours, extended-hours or 24/7 operational models can be structured according to the engagement.

Service Levels: Define relevant Response targets, Escalation, Service objectives, Criticality, and Ownership.

Responsibility Model: Clearly establish Mobiloitte responsibility, Client responsibility, Cloud-provider responsibility, and Third-party responsibility.

Governance: Use regular operational reviews to examine Incidents, Reliability, Security, Costs, Capacity, Changes, and Improvement opportunities.

Important: We define actual standard contractual SLAs and coverage tiers based on your specific requirements rather than implying a universal SLA for every engagement.

Define the Managed Cloud Service Around Your Operating Requirements

Why Cloud Operations Break Down
—and How We Engineer Around It

Problem

Alert Overload

Teams receive thousands of alerts without clear priority.

Response

Observability, event correlation, service context and improved alert design.

Problem

Recurring Incidents

The same failures repeatedly consume operational time.

Response

Problem management, root-cause analysis and reliability engineering.

Problem

Manual Operational Toil

Engineers spend too much time executing repetitive runbooks.

Response

Controlled automation and self-service operations.

Problem

Unowned Cloud Spend

Nobody can connect cloud consumption to a team or workload.

Response

FinOps, cost allocation and ownership.

Problem

Monitoring Without Context

Infrastructure appears healthy while users experience degradation.

Response

Full-stack observability and service-level indicators.

Problem

Security Drift

A secure deployment gradually changes as teams modify resources.

Response

Continuous configuration monitoring, governance and operational security.

Problem

No Continuous Improvement

Managed services become 'keep the lights on.'

Response

Regular service reviews tied to reliability, cost, security and modernization.

Managed Cloud Operations in Practice

Confidential Enterprise SaaS Company

Environment: AWS / Multi-Region

Operational Challenge

High incident volume, poor visibility, manual operations, and rapid cost growth.

Managed Service Scope

Monitoring, SRE, FinOps, Incident Management, Automation

Measurable Improvement

  • MTTR reduced by 40%
  • Cloud spend optimized by 25%
  • Manual toil reduced by 15 hours/week

Confidential Financial Services Firm

Environment: Azure / Hybrid

Operational Challenge

Reliability problems, unowned cloud spend, and security compliance drift.

Managed Service Scope

Observability, Security Operations, Lifecycle Management, FinOps

Measurable Improvement

  • SLO attainment increased to 99.99%
  • Alert volume reduced by 60%
  • Patch coverage increased to 100%
View Cloud Operations Case Studies

Measure Cloud Management
by Operational Outcomes

Reliability

  • SLO attainment
  • Availability
  • Incident frequency
  • Recurring incidents

Incident Operations

  • MTTA
  • MTTR
  • Escalation rate
  • Incident backlog

Change Quality

  • Change failure rate
  • Rollback rate
  • Failed changes

Automation

  • Automated runbooks
  • Toil eliminated
  • Self-service usage
  • Manual interventions

Cloud Economics

  • Actual vs budget
  • Cost per workload
  • Waste identified
  • Forecast accuracy

Performance

  • Latency
  • Capacity
  • Resource saturation
  • Scaling behavior

Security Operations

  • Policy drift
  • Vulnerability remediation
  • Access exceptions
  • Security findings

Backup & Recovery

  • Backup success
  • Restore success
  • Recovery test results
  • RTO/RPO attainment
Define Your Cloud Operations KPIs

Choose the Right Managed Cloud Starting Point

Cloud Operations Assessment

For environments that need a clear view of current reliability, monitoring, costs and operational risk.

Outcome: Current-state assessment and prioritized operating roadmap.

Managed Cloud Transition

For organizations transferring Day-2 operational responsibility.

Outcome: Service inventory, RACI, monitoring model, runbooks, escalation structure and operational transition.

CloudOps & Observability Enablement

For teams needing stronger monitoring, telemetry, incident visibility and operational workflows.

SRE Enablement

For cloud-mature organizations shifting from ticket-led support toward SLI/SLO-driven reliability engineering.

FinOps Managed Services

For organizations requiring ongoing cloud financial visibility and optimization.

AIOps & Automation Enablement

For organizations seeking to reduce alert noise, operational toil and repetitive remediation.

Managed AWS / Azure / GCP Operations

For ongoing monitoring, service management, optimization and operational improvement on specific public clouds.

Hybrid & Multi-Cloud Operations

For environments spanning multiple public clouds, private infrastructure or on-premise systems.

Frequently Asked Questions

Managed cloud services provide ongoing operational support for cloud environments after deployment. Services can include monitoring, incident management, observability, security operations, backup, cost optimization, lifecycle management and automation.
CloudOps is the operating discipline used to manage cloud environments reliably and efficiently. It combines monitoring, automation, service management, security, capacity, performance and continuous optimization.
Cloud infrastructure services primarily design and build the cloud foundation. Cloud management focuses on operating and improving that environment after deployment, including monitoring, incidents, reliability, costs, security and lifecycle management.
Managed-service engagements can include 24/7 monitoring and operational coverage where required and agreed in the service scope and SLA. The appropriate coverage model depends on workload criticality and business requirements.
Cloud observability uses metrics, logs, traces and service context to help teams understand the behavior and health of cloud-based systems. Unlike basic monitoring, observability is intended to help teams investigate why a system behaves unexpectedly.
Site Reliability Engineering applies software-engineering practices to operational reliability. SRE commonly uses Service Level Indicators, Service Level Objectives, automation and reliability metrics to balance system stability with continued change.
AIOps applies machine learning and AI techniques to IT operations. Potential applications include event correlation, anomaly detection, alert prioritization, incident assistance and controlled automation.
FinOps is a cloud financial-management discipline that helps engineering, finance and business stakeholders improve visibility, ownership and value from cloud consumption.
Cloud optimization can include cost allocation, resource rightsizing, idle-resource identification, workload scheduling, storage optimization, commitment analysis and architecture review. Optimization should retain the performance and reliability required by the workload.
Mobiloitte can support managed-cloud engagements across AWS, Microsoft Azure and Google Cloud according to the environment, service scope and required operational model.
Yes, where the architecture and tooling support it. Hybrid or multi-cloud operations may require consistent monitoring, governance, service management, cost visibility and security practices across environments.
Incident management should define detection, prioritization, ownership, escalation, communication, restoration and review. Critical incidents may also require a post-incident review to identify root causes and corrective actions.
An incident is an unplanned interruption or degradation requiring service restoration. Problem management investigates the underlying causes of recurring or significant incidents to reduce the likelihood of recurrence.
Not necessarily. Automation should be limited to approved, tested and observable workflows. Higher-risk or irreversible actions should retain appropriate human approval.
Managed cloud security can include access monitoring, configuration checks, vulnerability management, logging, policy monitoring and security-event workflows according to the agreed scope.
No. Managed-cloud controls and operational evidence can support applicable requirements, but compliance depends on the broader combination of systems, organizational policies, processes, people and regulatory obligations.
Relevant metrics may include SLO attainment, availability, MTTR, incident recurrence, change failure rate, cloud cost, automation coverage, patch status, capacity and recovery performance.
There is no universal timeline. Transition depends on the number of workloads, cloud environments, tooling, documentation, access requirements, service scope, existing incidents and operational complexity. A Cloud Operations Assessment can establish the transition plan.

Turn Cloud Operations Into a Continuous Engineering Capability

Move beyond reactive alerts and ticket-driven cloud support. Build an operating model where observability, SRE, FinOps, security, automation and service management work together to improve cloud reliability and efficiency over time.

Request a Cloud Operations AssessmentDiscuss Your Requirements
CloudOps • Observability • SRE • AIOps • FinOps • Security • AWS • Azure • GCP