Cloud Infrastructure Management: Components, Tools, Benefits

Cloud infrastructure management is the process of managing the lifecycle of your cloud infrastructure. It ensures that resources are provisioned efficiently, operated reliably, and scaled appropriately to meet business needs. Effective management practices help maintain cost-efficiency, security, and performance throughout the lifecycle. This lifecycle includes:

• Creating resources through IaC and other automation practices
• Managing the running resources through the lens of cost, security, performance, observability, scalability, and more
• Decommission resources when they are no longer needed

How does the cloud infrastructure work

Before we can understand cloud infrastructure management, we must define what cloud infrastructure is. In essence, cloud infrastructure is a managed offering of compute, storage, and networking services:

• Compute is the CPU and memory we use to run applications and systems in the cloud.
• Storage is the offering of different types of storage media to store data in the cloud.
• Networking is a set of connectivity options for connecting your applications and systems in the cloud with each other and with your end users.

Types of cloud delivery models

Compute, storage, and networking are packaged and offered in three delivery models:

• Infrastructure as a Service (IaaS) – The delivery of raw compute, storage, and networking services. You request raw CPUs, memory, storage, and network speed and connectivity that your applications require. A typical IaaS example is a virtual machine.
• Platform as a Service (PaaS) –  The delivery of a packaged solution for compute, storage, and networking, where most of the details of the underlying infrastructure are abstracted away and managed by the platform provider. Examples include managed Kubernetes offerings by the major cloud services.
• Software as a Service (SaaS) – The delivery of software that your organization wants to use but has no desire to host and manage yourself. You get access to the software without having to worry about the underlying infrastructure or management.

How does the cloud infrastructure management process work

Organizations starting with cloud infrastructure tend to use manual processes to create and manage it. Most cloud services offer a graphical user interface where you can manage all your infrastructure for that specific cloud provider. This is a good first step for experimentation and learning platform basics, but it does not scale beyond a handful of resources.

To scale your organization’s cloud infrastructure management beyond initial learning and experimentation, you need to adopt the concept of IaC. Good IaC practices form the basis of your full cloud infrastructure management.

Provisioning phase

All cloud infrastructure follows common steps. Creating a new cloud infrastructure is usually called the provisioning phase. This phase includes defining your infrastructure in code and setting up CI/CD pipelines and other automation capabilities.

Maintenance phase

The provisioning phase is followed by the maintenance phase, where you manage the running infrastructure and keep it functioning as intended. In general, the maintenance phase will be the longest one and consume most of your engineering hours.

Decommissioning phase

Eventually, parts of your cloud infrastructure will become redundant. This promptso the decommissioning phase, where the cloud infrastructure is deleted.

The timespan from provisioning to decommissioning varies. Some infrastructure pieces can have a lifecycle of minutes, and other pieces have a lifecycle of months or years. Some parts of your infrastructure will go through multiple phases of provisioning and maintenance before they reach the decommissioning phase.

Cloud infrastructure management usually involves these five key aspects:

1. Resource management
2. Cost management
3. Security and compliance
4. Monitoring
5. Disaster recovery and redundancy

1. Resource management

You can discuss resource management at different levels.

At one level, you manage the cloud infrastructure resources themselves. Collectively you can describe all of your cloud infrastructure in terms of the amount of CPU, memory, storage, and networking. At any point in time, your cloud environment consists of a set number of these resources (number of CPUs, amount of memory and storage, and a given network speed and throughput).

Resource management is essentially the management of distributing and using these raw resources according to your needs. You should ensure you use the resources you are paying for. Otherwise, you could end up with large virtual machines with multiple CPUs and substantial memory that are barely utilized at all.

At a different level, you also manage resources within the context of a given set of other cloud resources. A good example of this is a Kubernetes cluster with its own pool of CPU, memory, and storage. You need a strategy for utilizing these internal resources efficiently to get the most value out of the overall resources (in this case, a Kubernetes cluster). 

It is easy to overprovision Kubernetes cluster nodes of larger sizes than needed, which underutilizes the cluster and the raw resources themselves.

A best practice is to start small and scale up as needed.

2. Cost management

Managing the cost of your overall cloud environment is important.

If you are working within the context of an unlimited cloud budget, then throwing money at any resource or performance issues your environment faces seems like a good idea. This will probably solve the issues you are facing (at least temporarily). However, most organizations do not have access to an unlimited cloud budget.

Managing the cost of your resources efficiently starts with tracking all your resources. The common approach is to set up a resource tagging strategy, where each resource is tagged with a common set of tags to determine its owner and purpose (e.g., development or production resource).

Having a tagging strategy in place allows you to identify applications and/or teams where most of your cloud spending takes place and where you should prioritize optimizing your cloud spending. The cost may be justified, but traceability is necessary to identify opportunities for optimizations.

All major cloud providers support resource tagging for most resources. They also support filtering costs and generating reports based on the values of these tags. Apart from tracking costs in your current environment, you could also benefit from optimizing the types of cloud resources you are using. 

If you are managing multiple virtual machines running multiple different applications that all communicate with each other, a more cost-efficient solution may be to containerize each application and run them in a common Kubernetes cluster. Or perhaps you could rearchitect some of your applications into serverless offerings such as AWS Lambda. 

Rearchitecting has associated costs, mostly in the form of engineering hours. However, such investments can lead to cost savings in the long run.

Keeping track of your costs also helps you spot anything that falls outside of your normal trends. This could be something like a virtual machine that was used for a proof-of-concept long ago and then promptly forgotten. The virtual machine is no longer needed, but it is incurring costs by the minute.

Some costs are unexpected and a bit surprising. Examples of these include:

• Network traffic leaving your cloud environment (egress traffic) and some traffic passing between different regions and/or availability zones of your cloud infrastructure.
• Log ingestion and log storage, even if you use the cloud services’ native logging solutions.
• Data scanning costs can be high when analyzing data with your cloud provider’s native log-searching tools. Careless log queries scanning large amounts of data can lead to high costs.
• IP address resources that are allocated to your environment but not actively used by any resource.

One of the latest trends in cost management is the introduction of FinOps practices. These practices prioritize cost. You don’t have to implement a FinOps program in your organization to save money. 

In general, you can save a lot of money just by continuously tracking your costs from month to month, challenging assumptions, questioning any deviations, and continuously improving and learning. It also helps to talk about cloud costs in the open and have a no-blame culture around them.

Read more: 17 Cloud Cost Optimization Best Practices

3. Security and compliance

Security is arguably the most important component of cloud resource management. If you do not properly secure your environment, all your other efforts will be useless once a major security incident occurs.

There is a conflict between cost management and security management. In general, improving cloud security comes with increased costs. At some point, you need to decide how big a risk you are willing to take.

Security can be built into your IaC templates. You should create infrastructure templates (e.g., in Terraform) where you configure cloud resources according to your organization’s security practices. Creating a common library of cloud resource templates for your organization increases efficiency and improves security. This also allows you to standardize resource tagging (see the previous section on tagging in the context of cost management).

Compliance is the other side of the security coin and is a prerequisite for staying in business. If you do not fulfill certain regulatory compliance frameworks, you might not be able to operate your business as you intend.

The list of compliance frameworks required for your organization depends on your industry. A growing trend is collaboration between your organization’s IT and development departments and the Governance, Risk, and Compliance (GRC) department. 

This collaboration is necessary as more regulatory compliance frameworks that affect cloud environments are introduced. One such framework is the Digital Operations Resilience Act (DORA), which is set for release in January 2025. This framework requires financial institutes to strengthen their digital operations, including their cloud infrastructure.

4. Monitoring

Monitoring is involved in all the other key components of cloud resource management. Proper monitoring can answer questions about your environment, such as:

• How many Kubernetes clusters are you currently operating?
• What is the average resource utilization of all virtual machines?
• What was the cost of your egress network traffic for the past three months?
• How many failed sign-in attempts from risky locations have occurred during the past week?
• How many API requests per second is Application-X receiving?

Implementing proper monitoring in your environment allows you to spot negative trends or unexpected behavior early and make proactive decisions about how to address them.

Monitoring should be built into your cloud infrastructure templates to simplify the process of getting proper monitoring in place for your teams.

Your development and platform teams’ monitoring needs will differ. Your development teams are more interested in monitoring how your apps behave and how your users use the applications. The platform teams are interested in how the cloud infrastructure behaves and the cost of this infrastructure.

As with most other practices, start small and increase your monitoring when you discover gaps or think of questions that the current monitoring data can’t answer.

5. Disaster recovery and redundancy

Being able to set up your cloud infrastructure once is generally not a big issue. Keeping your cloud infrastructure running and functioning for a long time is a bigger challenge.

All cloud providers offer a regional presence in different parts of the world. When you are starting out with the cloud you might be fine with using a single cloud region of a single cloud provider. However, as your user base grows, the demand to be constantly available increases. Eventually, it is no longer sufficient to rely on a single cloud region or even a single cloud provider because even cloud regions and providers can experience issues and become unavailable.

You should have redundancy built in to keep your infrastructure and applications running in the event of failures. The general rule of thumb for redundancy is to avoid having a single point of failure.

Redundancy can be implemented at several different levels. You should run your applications in multiple copies. If your application runs on Kubernetes, you should run it as a deployment with multiple pods. The next step is to run multiple Kubernetes clusters in multiple availability zones of a cloud region. Eventually, you can scale out to run the application in multiple clusters across multiple cloud regions or cloud providers.

Even the most redundant design can fail. To prepare for this, you must have a disaster recovery plan.

Disaster recovery is about preparing for when something drastic happens. What would you do if you accidentally deleted your production database? You need to have a plan for how to get the database back online. 

A minimum requirement is a backup strategy for regularly backing up your database. You should also have processes in place for restoring a backup and practice performing this operation regularly. A great backup strategy is not worth anything if you do not know how to properly restore a backup in an emergency.

Infrastructure as code (IaC) tools are the primary cloud management tools.

A few popular choices are:

• Terraform
• OpenTofu
• AWS CDK
• AWS CloudFormation
• Pulumi
• Kubernetes

Infrastructure as code is the practice of declaring your desired cloud infrastructure using a configuration language, a domain-specific language, or a programming language. This allows you to keep a record of your infrastructure, maintain your infrastructure code in source control, have a history of all the changes, and more.

When selecting an IaC tool, you should consider factors including your target platform, current organizational experience, and skills, preferred IaC philosophy (imperative or declarative), and licensing concerns.

For Kubernetes environments, you declare the desired in-cluster resources using Kubernetes manifests. These can be kept in a Git repository, and you can use a GitOps approach to keep your cluster up to date with your desired state.

Cloud management tools also include tools for configuration management. These tools are not used to create new infrastructure but rather to manage large parts of your existing infrastructure. This could mean keeping a fleet of virtual machines patched or installing and updating applications on your servers.

In the security space, there are many tools to consider depending on your cloud management needs. You can include scanning tools to scan your application dependencies and more.

Your organization might have unique goals when it comes to cloud infrastructure management, but any good cloud infrastructure management approach should strive for these common goals:

• Cost-effectiveness: The cloud infrastructure you provision should be fully utilized, and waste should be minimized.
• Scalability: Cloud infrastructure should be able to scale to accommodate the expected load without incurring downtime.
• Reliability: Cloud infrastructure and applications should be robust and not encounter errors that you could have avoided. You should design to expect certain errors to occur and have ways to handle them gracefully.
• Availability: Cloud infrastructure, applications, and data should be available when your users need it, you should have redundancy built in.
• Security: secure cloud infrastructure will keep your organization in business. Insecure cloud infrastructure leads to data loss, economic costs, and reputational costs.

Your organization will rank these goals according to your unique environmental needs. Some goals work against each other. In general, most goals are in conflict with the cost-effectiveness goal. Increasing cloud infrastructure security comes at a cost, as does increasing its reliability and availability.

Managing your cloud infrastructure in a controlled and structured way allows for efficient use of your cloud environment and a secure environment for your applications to serve your users. This will benefit your organization’s bottom line.

Other benefits include:

• Keep your workforce happy and attract new talented cloud platform engineers who are inspired by your approach to cloud infrastructure management.
• Avoid unnecessary security risks in your environment that can put your organization on a (negative) headline in the news.
• Speed up innovation in your cloud environment with automation and templates for cloud infrastructure ready to go.

Cloud infrastructure management could present several challenges for your organization:

• Scaling – Ensuring applications can handle unpredictable load changes without performance degradation or resource over-provisioning.
• Cost control – Identifying and managing unused or underutilized cloud resources to prevent unnecessary expenses.
• Security – Protecting data against breaches, ensuring encryption, and maintaining access controls across multiple cloud services.
• Downtime and reliability – Implementing strategies to minimize service outages and ensure high availability in case of failures.
• Monitoring and logging – Maintaining visibility into resource usage, errors, and performance issues across distributed systems.
• Vendor lock-in – Avoiding architecture dependencies that make it difficult to migrate workloads to other cloud providers.

The biggest problem with cloud infrastructure management comes with scale.

As you scale from a few cloud resources in a single cloud provider to thousands of cloud resources across multiple cloud providers, private data centers, and edge locations, you need a robust process for managing your cloud resources.

Organizing the work of many teams can also become complex with scale. The more cloud infrastructure your teams create, the more difficult and time-consuming it will be to keep track of this infrastructure and make sure everything is up-to-date, secure, and aligned with your organizational policies.

It is important to establish how you want to work with cloud infrastructure management early on to avoid costly mistakes that can be difficult to fix later.

A different challenge is keeping up with the rate of innovation in the cloud infrastructure management tools space. Existing tools are continuously being improved, and new tools are being released. 

Migrating from one tool to another can be a challenge, but if the benefits in the long run outweigh the immediate cost, it can be worth the effort.

We have already discussed some best practices in cloud infrastructure management. In this section, we will summarize these.

1. Automate as much as possible

Automation ensures repeatability and decreases the number of mistakes that could be introduced due to manual interventions. For cloud resource management, automation starts with using infrastructure as code, which is the practice of defining your desired infrastructure through code. 

To set up cloud infrastructure, you can use tools such as Terraform, OpenTofu, Pulumi, AWS CDK, or CloudFormation. For Kubernetes, you define your desired resources through Kubernetes manifests.

2. Build monitoring into your cloud infrastructure

This allows you to ensure that your cloud infrastructure is utilized correctly and works as intended. You can extend the monitoring to include your overall cloud resources to answer questions such as how many Kubernetes clusters you are currently running. Monitoring your cloud costs is also important to avoid spending more than your budget allows.

3. Prioritize security throughout your development lifecycle

This includes your application source code and the cloud infrastructure where your applications run. The space of security tools on the market is vast. You should handle your cloud and application secrets in a secure way, scan your application and infrastructure dependencies for vulnerabilities, keep your resources patched and up to date, and build security into your IaC templates.

4. Monitor the performance of your infrastructure and implement a disaster recovery plan

Creating cloud infrastructure is just the first step of cloud infrastructure management. You must make sure the infrastructure works as intended throughout its complete lifecycle. You should expect your infrastructure to fail in unexpected ways, and you should have redundancy built in. You must also set up a plan for disaster recovery.

5. Invest in continuous training and development

Invest in continuous training and development for everyone involved in delivering and managing cloud infrastructure in your organization. The field of cloud infrastructure management is continuously developing, with new tools, processes, and practices appearing daily.

Here are some of the key trends shaping the future of cloud infrastructure management:

Artificial intelligence

AI has been a trending topic in the tech space during the past few years. Large language models (LLMs) are virtually everywhere today, and this trend is likely to continue for the foreseeable future.

Areas of application for AI/LLMs in cloud infrastructure management include:

• Intelligent resource utilization, leading to decreased cloud costs
• Improved support in code editors for all IaC tools, leading to faster development and better and more secure cloud resource configurations
• Intelligent security scanning of your environment and detection of possible security issues in real time
• Automatic creation, management, and optimization of whole cloud architectures
• Automatic troubleshooting issues in your environment
• Asking LLMs questions about your infrastructure using natural language; discussing improvements and issues,  discovering anomalies, and more
• Using an LLM as an onboarding tool for new developers and platform engineers to learn about your environment

AI will likely help you streamline and improve all aspects of cloud infrastructure management, from helping you write IaC to troubleshooting ongoing issues in production.

Hybrid cloud, multicloud, edge computing

Global applications and systems make it necessary to move away from using a single cloud region from a single cloud provider.

It is likely that the shift towards hybrid environments and multicloud will continue and become the norm going forward. Building truly resilient applications requires using multiple cloud providers or a hybrid approach.

Edge computing is also likely to increase and become a part of most organizations’ infrastructure. Moving compute operations to the edge allows your applications to respond faster. This is important for applications involving sensors that need to take actions based on what happens in your physical environment (e.g., security cameras).

The cloud infrastructure management practices discussed in this post are equally important in hybrid scenarios and for edge computing.

Sustainability and green computing

Green computing is a growing trend in sustainability that is likely to increase. This can stem from regulatory compliance frameworks or from consumer and stakeholder demands.

The major cloud providers have many data centers around the world, and each data center consumes a lot of electricity. If this concerns you, you should spend time investigating how each cloud provider works with green computing and sustainability. Each cloud provider publishes reports and documentation on its work in this space.

Spacelift is not exactly a cloud automation tool, but it takes cloud automation and orchestration to the next level. It is a platform designed to manage infrastructure-as-code tools such as OpenTofu, Terraform, CloudFormation, Kubernetes, Pulumi, Ansible, and Terragrunt, allowing teams to use their favorite tools without compromising functionality or efficiency.

Spacelift provides a unified interface for deploying, managing, and controlling cloud resources across various providers. Still, it is API-first, so whatever you can do in the interface, you could do via the API, the CLI it offers, or even the OpenTofu/Terraform provider.

The platform enhances collaboration among DevOps teams, streamlines workflow management, and enforces governance across all infrastructure deployments. Spacelift’s dashboard provides visibility into the state of your infrastructure, enabling real-time monitoring and decision-making, and it can also detect and remediate drift.

You can leverage your favorite VCS (GitHub/GitLab/Bitbucket/Azure DevOps), and executing multi-IaC workflows is a question of simply implementing dependencies and sharing outputs between your configurations.

With Spacelift, you get:

• Policies to control what kind of resources engineers can create, what parameters they can have, how many approvals you need for a run, what kind of task you execute, what happens when a pull request is open, and where to send your notifications
• Stack dependencies to build multi-infrastructure automation workflows with dependencies, having the ability to build a workflow that, for example, generates your EC2 instances using Terraform and combines it with Ansible to configure them
• Self-service infrastructure via Blueprints, or Spacelift’s Kubernetes operator, enabling your developers to do what matters – developing application code while not sacrificing control
• Creature comforts such as contexts (reusable containers for your environment variables, files, and hooks), and the ability to run arbitrary code
• Drift detection and optional remediation

If you want to learn more about Spacelift, create a free account today or book a demo with one of our engineers.

In this blog post, we have covered cloud infrastructure management in detail.

Key components of good cloud infrastructure management include efficient use of cloud resources (CPU, memory, storage, networking), tracking your cloud costs, improving environment security, monitoring everything important, and building highly available systems.

The main benefit of an efficient approach to cloud infrastructure management is maximiziing the return on investment (ROI) in the cloud. This will be reflected in your organization’s bottom line.

Even if your cloud infrastructure management starts with infrastructure as code, there is a lot more to it in the areas of processes, practices, and culture.