What is MultiCloud Monitoring & Management?

Learning Objectives

Learn how multicloud monitoring and multicloud management play a vital role in today's complex tech stacks. Understand how they work, key capabilities of each, and the importance of choosing a multicloud strategy.

What is Multicloud Monitoring and Management?

What is multicloud monitoring?

Multicloud monitoring is the practice of observing, collecting, analyzing, and managing metrics, logs, traces, and events across multiple cloud service providers within a single environment.

Multicloud monitoring typically includes:

  • Centralized visibility: Unified dashboard to view data across clouds
  • Performance tracking: Monitoring compute, storage, network, and application performance across different providers
  • Log and telemetry aggregation: Collecting logs, traces, and metrics from diverse sources into one system
  • Incident detection and alerting: Identifying anomalies, failures, or degradation in real time regardless of the cloud vendor
  • Security and compliance tracking: Ensuring data handling, access, and configurations meet standards across platforms

Multicloud monitoring plays a vital role in today’s complex tech stacks. First, it helps manage the complexity that comes from multicloud setups. It also helps reduce risk by overseeing all cloud environments simultaneously so failures or vulnerabilities can be detected more quickly. Multicloud monitoring also helps optimize cloud spend because it can track usage and spending patterns across cloud services. Operational efficiency is improved because teams can now identify underperforming services, misconfigurations or downtime across platforms. And finally multicloud monitoring supports compliance efforts by tracking policy violations and security drift across multiple clouds.

What is multicloud logging?

Multicloud logging is the practice of collecting, aggregating, managing, and analyzing log data from multiple cloud service providers in a unified, centralized way.

Multicloud logging focuses on capturing and handling logs from applications running across different clouds, infrastructure components such as VMs, containers, and serverless functions, cloud-native services, and security and audit logs from each provider. It ensures that logs from each environment are standardized and normalized, stored centrally, searchable/queryable, and correlated with other telemetry like metrics and traces.

Multicloud logging offers a number of advantages to teams. It avoids fragmented visibility across cloud platforms because it is possible to see all logs in one place. With multicloud logging, DevOps/SREs can monitor apps and infrastructure consistently across clouds, and, when problems arise, troubleshooting is faster because events are correlated across services and clouds. Teams can also capture and retain audit and access logs across environments for compliance requirements. And it’s a simple matter to monitor log volumes and patterns to optimize retention policies and control cloud logging costs.

The role of a shared responsibility model in the cloud

The shared responsibility model in cloud computing defines the division of security and operational responsibilities between the cloud service provider and the customer. It ensures both parties understand their roles in maintaining security, compliance, and availability of the systems hosted in the cloud.

While cloud providers offer the infrastructure, customers retain control over what they build on it. The model varies based on the type of cloud service:

Cloud Service Model Responsibilities
Shared Responsibility Model

This table outlines the division of responsibilities between the Cloud Service Provider (CSP) and the customer for different cloud service models (IaaS, PaaS, SaaS).

Cloud Model CSP is Responsible For Customer is Responsible For
IaaS (e.g., AWS EC2, Azure VMs) Physical infrastructure, virtualization, storage, networking OS, applications, data, identity, access management
PaaS (e.g., Azure App Service, Google App Engine) IaaS + runtime, middleware, OS Application code, data, identity/access, configurations
SaaS (e.g., Office 365, Salesforce) Everything up to the application level Data, user access, configurations, compliance usage


What is the difference between multicloud and hybrid cloud?

The difference between multicloud and hybrid cloud lies in the types of environments involved and how they are used together.

Multiclouds have public only-environments (AWS, GCP, etc.), and companies choose this strategy because they’re looking for vendor diversity, to avoid lock-in and to optimize services. Multiclouds aren’t necessarily interoperable and the data and workload movement is limited or siloed between clouds. Hybrid cloud, on the other hand, refers to a public and private cloud and/or an on-prem infrastructure. Companies choose a hybrid model because they’re looking for flexibility, control, and integration with their legacy systems. Hybrid options are typically very interoperable, offering tight integration across environments, and they tend to have seamless workload and data movement across environments.

To think about it slightly differently, multicloud is like owning multiple cars for different tasks, and each is used separately. A hybrid cloud model is like a hybrid vehicle - systems work together as a unified engine.

How does multicloud management work?

Multicloud management is the process of coordinating, monitoring, securing, and optimizing workloads and services across multiple cloud service providers through a centralized strategy or toolset. It enables organizations to control and streamline operations across clouds from a single pane of glass, avoiding complexity, silos, and inefficiencies.

Organizations can employ multicloud management in a number of ways. It can tackle discovery and inventory, automatically detecting cloud assets, services, configurations, and workloads across all cloud accounts and regions. Multicloud management offers a unified dashboard to manage resources, policies, costs, and performance from one interface. It can automate provisioning, scaling, and lifecycle management of cloud resources across providers, and deploy workloads using Infrastructure as Code (IaC) tools like Terraform, Pulumi, or Ansible. Teams can use multi-cloud management to collect and correlate metrics, logs, and traces from all cloud environments. It can also apply consistent identity and access policies (IAM), encryption, and security rules across clouds. And multicloud management will also track and analyze cloud spending across providers.

Multicloud management provides a number of benefits including:

  • Unified visibility across all cloud environments
  • Reduced operational complexity
  • Improved security posture with consistent policy enforcement
  • Cost savings through optimization and resource control
  • Faster delivery with automation and orchestration
  • Vendor flexibility and reduced lock-in

Why choose a multicloud architecture/strategy?

Choosing a multi-cloud architecture or strategy allows organizations to distribute workloads across two or more public cloud providers to maximize flexibility, performance, and resilience. It’s a strategic approach to avoid vendor lock-in, enhance availability, and tailor services to business and technical needs.

More choices

Companies can optimize for best-of-breed services that leverage each cloud provider’s strengths and also choose the most performant or cost-effective option for each workload.

Less vendor lock-in

A multicloud strategy will prevent over-reliance on a single provider’s ecosystem. Organizations can maintain flexibility to switch or add services without major reengineering.

Greater reliability

A multicloud strategy will enhance resilience and availability. Teams can build redundancy and failover mechanisms across providers, and minimize the risk of outages by spreading workloads.

Location-based services

Multicloud is ideal for global organizations - they can serve users closer to their physical location using the nearest provider data centers thereby reducing latency and improving user experience.

Observability in multicloud management

Observability in multicloud management is the ability to gain deep, end-to-end visibility into applications, services, infrastructure, and dependencies across multiple cloud providers from a single unified system.

It ensures that teams can monitor, understand, and act on the health and performance of distributed systems, regardless of where they run.

Multiple cloud environments are inherently complex, so observability is key to streamlining management of all the different moving parts. Observability helps detect issues faster, understand root causes across clouds, optimize performance and costs, and ensure consistent reliability and security. 

When it comes to multicloud, think of observability in terms of three practical “pillars”: logs, metrics and traces, all of which are enriched with metadata for filtering by cloud, region, service or tenant. This strategy will allow teams to practice unified telemetry collection, correlated data across clouds, run centralized dashboards, detect and alert on anomalies, and implement contextual troubleshooting.

What capabilities should your multicloud management have?

A robust multicloud management solution should provide a comprehensive, unified, and secure approach to managing resources, workloads, and services across multiple cloud platforms. Below are the essential capabilities your multicloud management should have:

Real-time data collection platform

Start with a real-time data collection platform that includes unified dashboards to monitor infrastructure, services, and applications across clouds. Be sure to include real-time performance metrics, logs, and availability data, as well as support for visualizing resource health across multiple providers.

Flexible data collection mechanism

It’s important to cast the net broadly: Ensure there is auto-discovery of assets and services in each cloud, and include resource tagging, grouping, and mapping for cost centers or business units as well as cross-cloud topology mapping.

Data adaptability

Any data management platform must be open to receiving a variety of data and working with a number of tools. Consider options that include end-to-end observability across clouds with integrated logs, metrics, and traces, as well as distributed tracing and service correlation. Also look for integration with OpenTelemetry and third-party observability tools.

Data correlation

The multicloud management platform also needs to be able to make the data work together. Look for tools that understand service-to-service and cross-cloud dependencies and offer visual maps to trace failures or performance issues. The goal is to identify bottlenecks across interconnected services.

Data interrogation

Data interrogation, including support for containerized and serverless workloads and easy movement or duplication of workloads across cloud platforms, is also a key attribute to a multicloud management platform.

Visualization

Your multicloud management should include visualization because it transforms complex, distributed environments into clear, actionable insights. With resources, services, and dependencies spread across providers like AWS, Azure, and GCP, visualization is essential for making sense of it all quickly and accurately.

Action

Your multicloud management should include the option for action - not just visibility - because observing problems without being able to fix them is not enough in fast-paced, complex cloud environments. Actionable management means you can not only detect issues but also respond, remediate, and optimize operations in real time across multiple cloud platforms.

Other capabilities your multicloud management should have include cost management and optimization, policy enforcement and governance, security and compliance, and a vendor-agnostic architecture.

What are the challenges of multicloud?

Multicloud strategies offer flexibility, resilience, and vendor independence, but they also introduce significant complexity and risk. Organizations must manage diverse services, configurations, and security requirements across diverse cloud providers and that of course creates challenges.

For starters, it’s really complicated. Each cloud provider has different services, APIs, tools, and billing models, and managing multiple environments increases the burden on DevOps, IT, and SRE teams. Also, each provider handles identity and access management differently. Misaligned policies or misconfigurations increase the risk of data breaches. Cost is *always* a factor with cloud and that’s even more true with multi-cloud because now teams are dealing with different cloud pricing models from different providers, and they are all complex. Without centralized tracking, costs can spiral due to overprovisioning, idle resources, or duplication.

Multicloud can obscure observability - logs, metrics, and traces are often siloed by cloud providers - and differences in APIs, data formats, and architectures make it hard to move workloads between clouds. Teams often rely on each cloud's native tools, resulting in siloed operations and duplicated efforts. And even CI/CD and deployments can get tricky: automation pipelines may require cloud-specific logic, increasing maintenance overhead.

As if that wasn’t enough, meeting regulatory requirements (such as GDPR, HIPAA, or PCI-DSS) across providers can be complex. And all of the above translates into most teams needing expertise in multiple cloud ecosystems, which increases onboarding and operational costs.

It’s time to let data charge