30 Cloud Computing Tools To Simplify Cloud Management

Cloud computing empowers organizations to access IT resources on demand, over the Internet, and on a pay-per-use basis. Thus, your company does not need to purchase, install, operate, and upgrade hardware for physical data centers.

Instead, you can rent resources as needed from cloud service providers such as Amazon Web Services (AWS). For instance, AWS provides compute, storage, database, networking, machine learning, data lake, analytics, security, and IoT resources/services.

This means you can get to market faster, spend less money on owning computing hardware, and only pay for what you use once you use it.

What Are The Types Of Cloud Computing Tools Available?

Cloud computing tools support different service models: Software-as-a-Service (SaaS), Infrastructure-as-a-Service (IaaS), and Platform-as-a-Service (PaaS). They also align with public, private, hybrid, and multicloud cloud environments.

We’ve covered the cloud computing services in more detail here.

Here are some of the best cloud computing tools organized into different categories:

Cloud Tools By Service Model

These tools provide the infrastructure, software, and other dependencies needed to do specific jobs in the cloud.

1. CloudZero – Cloud cost intelligence platform (SaaS)

With CloudZero, SaaS companies can gain better visibility into cloud usage and costs, lower AWS costs, and increase their ROI. CloudZero helps them align cloud costs with the people, processes, and features that generate them. 

You can zoom in and view cost intelligence at a granular level, such as:

CloudZero also offers Budgets, a Migration Acceleration Program Dashboard for AWS MAP customers, and more, so it’s a complete cloud cost intelligence platform. See how CloudZero works in this demo. 

If you want to optimize your AWS Reserved Instances and Savings Plans, we’ve teamed up with ProsperOps to help you save up to 40%. If you want to automate replacing On-Demand Instances with Spot Instances to save more, check out Xosphere Instance Orchestrator.  

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2. Amazon Web Services – Infrastructure-as-a-Service (IaaS)

AWS provides over 200 cloud computing services, including compute, storage, analytics, IoT, AI/ML, and database services. With over 33% market share in cloud infrastructure services, AWS is the most popular IaaS today. It’s also popular because it offers infinite resources and services across the entire cloud spectrum.

Other Infrastructure-as-a-Service examples are Digital Ocean, Microsoft Azure, Alibaba Cloud, Google Compute Engine, Vultr, IBM Cloud, Oracle Cloud Infrastructure, Linode, etc.  

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3. Google App Engine – Cloud application platform

Google’s App Engine offers organizations and developers a platform for building, running, and hosting web applications. As a fully managed environment, App Engine means zero configuration and server management for your developers. With App Engine, you can deploy in minutes and access an extremely scalable serverless PaaS environment. 

More Platform-as-a-Service examples include Heroku, SAP Cloud, AWS Elastic Beanstalk, Dokku, etc. 

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Infrastructure As Code (IaC) And Automation Tools

As cloud environments grow more complex, automating infrastructure setup and management becomes essential. IaC tools enable you to define, provision, and update your cloud infrastructure with code. This improves speed, consistency, and scalability across deployments. The best include:

4. Terraform – Scalable IaC tool

Terraform is an open-source IaC tool built by HashiCorp. It uses HCL — a simple, readable language — to describe what your cloud environment should look like. You write the code once, and Terraform applies it the same way every time, across any cloud.

It figures out the steps needed to match your environment to your code. Want to add servers? Rename a database? It plans and applies the changes for you. Teams love how consistent it is — and how easy it is to reuse setups with modules.

Terraform also tracks your current setup using a state file. That helps prevent mistakes and surprises. When your code lives in version control, your infrastructure becomes shareable, reviewable, and easy to roll back if something breaks.

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5. Ansible – Cloud infrastructure automation

Red Hat’s Ansible suits organizations looking for a comprehensive platform that is also relatively easy to use. The platform lets you automate cloud provisioning, infrastructure configuration, container orchestration, application deployment, and security. Ansible is agentless, dependable, secure, and goal-oriented (no scripting required).

Ansible competitors include Jenkins, CFEngine, Puppet, Microsoft Azure Automation, Chef, and Google Cloud Deployment Manager. 

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6. Pulumi – IaC platform for  any programming language

With Pulumi, you can define and manage cloud infrastructure using popular programming languages such as Python, TypeScript, Go, C#, Java, and YAML.

The platform uses real programming constructs like loops, functions, and classes to create reusable and modular infrastructure components. This flexibility enables handling complex scenarios and promotes best practices in infrastructure management.

Pulumi also integrates with CI/CD pipelines, allowing for automated deployments and updates as part of your development workflow.​

For advanced automation, Pulumi offers the Automation API, which exposes the Pulumi engine as an SDK. This feature enables you to create, update, and manage infrastructure programmatically. It is most suited for building custom cloud interfaces, self-service portals, and dynamic provisioning systems.

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CI/CD And DevOps Platforms

Modern development teams rely on continuous integration and delivery (CI/CD) to ship code faster and reliably. DevOps platforms help automate builds, run tests, and deploy changes with minimal manual effort. Here are some of the most trusted tools in this space.

7. GitHub  – Source code management

GitHub is the most popular cloud-based version control, collaboration, and source code repository hosting for Git developers. Git’s distributed version control model enables distributed teams to build, deploy, and improve software from anywhere. The platform is also popular among developers as a social network, a repository for open-source projects, and a coding project management tool. 

GitHub alternatives include GitLab, BitBucket, AWS CodeCommit, etc.

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8. PagerDuty

PagerDuty’s end-to-end incident response tools enable cross-functional teams to stay on top of incident management at scale. PagesDuty offers solutions, from DevOps and AIOps to security and customer service. The real-time on-call management and alerts make it easy for teams to schedule the right people for the right tasks at the right time.

Similar tools to PagerDuty include Big Panda, Splunk On-Call, Lightstep Incident Response by ServiceNow, etc.

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9. Jenkins – CI/CD for complex workflows

Jenkins is a free, open-source automation server that helps teams build, test, and deploy code automatically. It supports multiple languages and tools, making it ideal for complex or custom workflows. You define pipelines using Groovy-based scripts or the visual editor. Jenkins then runs each step, from code checkout to deployment.​

With over 1,800 plugins, Jenkins integrates with tools like Git, Docker, Kubernetes, Maven, and Slack. You can run it on any OS, cloud, or on-premises. It also supports distributed builds, letting you run jobs across multiple machines to speed things up.​

Jenkins is also quite popular with DevOps and QA teams needing complete CI/CD process control. It’s not the easiest to set up, but once configured, it can handle almost any automation task you throw at it.

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10. GitHub Actions – Native CI/CD built into GitHub

GitHub Actions is a CI/CD tool built right into GitHub. You can run tests, build code, or deploy apps automatically by pushing to your repository. Workflows are written in YAML, and everything lives inside your GitHub project.

Its biggest appeal? Simplicity. You never have to leave GitHub. It works out of the box, supports any language, runs on Linux, macOS, or Windows, and integrates with Docker. You can test multiple versions of your app using matrix builds.

GitHub Actions also has a vast library of prebuilt actions. Need to deploy to AWS, send a Slack message, or install dependencies? There’s probably already an action for it.

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11. CircleCI – Fast, flexible CI/CD platform

CircleCI is built for speed and automation. It helps teams run tests, create code, and deploy changes automatically. You write simple YAML files to define steps, and CircleCI takes care of the rest.

It supports Linux, macOS, Windows, and Docker. You can speed up builds with caching, run jobs in parallel, and reuse setups with orbs — small, shareable automation packages.

It also works with GitHub and Bitbucket. The Insights dashboard shows real-time build metrics, so you can catch slowdowns, fix issues fast, and keep your DevOps pipeline running smoothly.

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Cloud Testing Tools

Cloud testing tools simulate traffic, test performance, and reveal system weaknesses before release. They let teams run large-scale tests without managing servers or hardware. Here are some of the best:

12. Gremlin – Chaos engineering platform

Chaos engineering is a proactive strategy to prevent system failures in cloud computing. Software developers use controlled experiments to identify weaknesses, study what could go wrong, and practice what to do if something does go wrong.

With Gremlin, you can use CPU spikes, server shutdowns, latency injections, process killers, and blocked DNS access to expose vulnerabilities in your system. Additionally, you can test your disaster recovery procedures to prevent a false sense of security.

Gremlin competitors include Chaos Toolkit, Litmus, ChaosMesh, etc. 

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13. Apache JMeter – Open-source load testing for web and APIs

Apache JMeter helps teams simulate real-world traffic and measure how applications behave under stress. It supports testing for web apps, APIs, databases, and more, and runs on any system with Java.

You can simulate thousands of users by configuring thread groups and test plans. JMeter supports protocols like HTTP, HTTPS, FTP, JDBC, and SOAP. It also integrates with cloud services like AWS and Azure for distributed testing. 

JMeter’s GUI lets you build tests visually, while its CLI mode supports automation and CI/CD pipelines. With plugins and dashboards, you can monitor performance metrics and identify bottlenecks. It’s a go-to choice for teams needing scalable, flexible testing without vendor lock-in.​

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14. BlazeMeter – Scalable cloud-based load testing platform

With the ability to simulate over two million virtual users from 56 global locations, BlazeMeter helps identify performance issues and ensure application scalability. Its intuitive UI and real-time analytics provide insights into response times, error rates, and throughput.

BlazeMeter integrates with CI/CD tools like Jenkins and TeamCity to facilitate automated performance testing within development pipelines. Its compatibility with various protocols and support for distributed testing also make it an ideal choice for organizations aiming to improve their DevOps practices. ​

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15. LoadRunner – Performance testing software tool

LoadRunner by OpenText is built for high-scale, complex testing. It simulates thousands of users from global locations to test how applications perform under heavy traffic, without needing to manage test infrastructure yourself.

What sets it apart is support for over 50+ protocols — far beyond most cloud testing tools. It handles web, mobile, SAP, Citrix, and legacy systems. That makes it ideal for large enterprises with diverse tech stacks or regulated environments.

LoadRunner also integrates with Jenkins and Azure DevOps, offers real-time dashboards, and supports shift-left testing for early-stage load validation.

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Cloud Provisioning Tools

Cloud provisioning tools help teams deploy infrastructure using code, automating resource setup, reducing errors, and keeping environments consistent. It’s important to note: provisioning is not the same as configuration. Provisioning prepares cloud resources; configuration defines how they behave after deployment.

Here’s our in-depth guide on provisioning and the difference between provisioning and configuration.

And here are the most commonly used tools across AWS, Google Cloud, and Azure.

16. AWS CloudFormation

AWS CloudFormation enables you to model, provision, and manage AWS resources using infrastructure as code. By defining your infrastructure in JSON or YAML templates, you can automate the setup of AWS services such as EC2, RDS, and S3, ensuring consistent and repeatable deployments.

With CloudFormation, you can also manage resources as a single unit called a stack. This approach simplifies the orchestration of complex environments, enabling you to update or delete all related resources together. Additionally, features like change sets let you preview modifications before applying them, reducing the risk of unintended changes.

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17. Azure Resource Manager – Native Provisioning for Azure

Azure Resource Manager (ARM) is Microsoft’s native IaC service for deploying and managing Azure resources. Using JSON-based templates, ARM enables you to define and provision infrastructure components such as virtual machines, storage accounts, and networks consistently and repeatedly.

ARM organizes resources into resource groups, enabling centralized management, access control, and monitoring. It integrates with Azure services, supporting RBAC, tagging, and policy enforcement to maintain governance and compliance across your deployments.

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18. Google Cloud Infrastructure Manager – Native Terraform provisioning for GCP

Google Cloud Infrastructure Manager (Infra Manager) is a managed service that automates the deployment and management of Google Cloud resources using Terraform. It enables users to define IaC and deploy resources programmatically. This eliminates the need for a separate Terraform toolchain.

Infra Manager works with Cloud Build to run Terraform commands in a temporary, clean environment. This helps keep deployments consistent. You can store your configs in Git or Cloud Storage for easy version control and teamwork. It also offers previews, auto-retries, and detailed logs for every deployment.

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If you’re looking for tools that support multi-cloud provisioning, Morpheus Data, Scalr, CloudBolt, Rundeck, Apache CloudStack, and Ansible are some of the best candidates.

19. Cloudsfer – Cloud migration tool

If you are planning to move to the cloud, check out our complete guide to cloud migration here. Cloudsfer offers on-premises-to-cloud and cloud-to-cloud migration services. You can migrate data from multiple sources to 20+ cloud storage services. The backup tool lets you sync cloud services, and the archiving tool enables you to copy data from cloud storage and replicate it locally.

Whether you need a cloud-to-cloud, on-premise-to-cloud migration, or a tool that supports both, see more cloud migration services here. Here are seven AWS migration strategies if you want to learn specific methods for migrating to the AWS public cloud. 

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Kubernetes cost optimization

Kubernetes is robust, but without cost visibility, it can quietly drain your cloud budget. As clusters scale, so do inefficiencies: overprovisioned nodes, idle pods, and underused resources.

Here are the tools leading the way in keeping Kubernetes efficient and cost-aware.

20. Kubernetes – Container orchestration and management  

Kubernetes, or K8s, is an open-source, production-grade platform for orchestrating containers. You can use it as a platform and tool to deploy, scale, and manage containerized applications. Its self-healing, automated rollbacks and rollouts, load balancing, and batch execution capabilities make Kubernetes particularly well-suited to managing container orchestration at a massive scale. 

Kubernetes alternatives include Docker, Amazon Elastic Kubernetes Service (EKS), Red Hat OpenShift, and Rancher.

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21. Harness – Kubernetes Cost Control With Built-In Intelligence

Harness Cloud Cost Management helps teams monitor and reduce Kubernetes spend across clusters. It breaks down costs by pod, namespace, workload, and environment, so you can see exactly where waste is hiding — and address it fast.

It uses AI to spot idle resources and overprovisioned workloads, then recommends rightsizing actions. You can automate these changes or review them manually. Harness also supports showback and chargeback, making aligning costs with teams or products easier.

For DevOps and FinOps teams, Harness adds auto-governance, budget alerts, and forecasting. You can set policies and stop overspending before it starts. It works across AWS, GCP, Azure, and hybrid Kubernetes environments — all from one platform.

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Related read: 5 Powerful Harness.io Alternatives For CI/CD, Security, And Cloud Cost Optimization

22. Densify – Kubernetes resource optimization

Densify uses machine learning to analyze Kubernetes workloads and recommends precise resource settings. It helps you rightsize pod CPU and memory requests so you’re not overpaying for unused capacity or under-resourcing critical services.

It continuously monitors your clusters and suggests adjustments to avoid waste and performance issues. These recommendations are tailored to your usage patterns and can be integrated into CI/CD pipelines for automated efficiency.

Densify also helps with node optimization and bin-packing, making better use of available compute. It’s a strong fit for platform teams managing large-scale, cost-sensitive Kubernetes environments.

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Data And Analytics Platforms

Modern cloud environments generate massive amounts of data, but raw data isn’t enough. Data and analytics platforms help teams centralize, clean, model, and analyze that data to drive decisions. Here is the best:

23. Civis Analytics – Big data and analytics tool

If you are looking for a service to help your data team centralize, clean, enrich, and apply data at scale, Civis Analytics may be a good choice. This service lets you collect data from trusted third parties to fill knowledge gaps in your data, share it across your organization, and inform decision-making. You can also work with data in your favorite language, from SQL to Ruby to Python.

More Big Data analytics tools include Apache Hadoop, OpenRefine, RapidMiner, Amazon EMR, etc.  

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Multi-Cloud Management Solutions

Multi-cloud tools help unify management across providers. They simplify operations, boost visibility, and enforce security and governance, no matter where your workloads run. Below are some of the leading platforms built for multi-cloud control.

24. Lacework  FortiCNAPP – Cloud security tool

Lacework FortiCNAPP provides continuous cloud security and compliance management at scale. You can collect, analyze, and correlate security threats across multiple cloud platforms, such as AWS, Google Cloud Platform, and Azure, so you can prioritize addressing them. 

This Infrastructure-as-a-Code security service provides vulnerability, security posture, and compliance management for all your environment’s apps, workloads, containers, processes, machines, accounts, and users.

Lacework alternatives include Fugue, Orca Security, Synk, Threat Stack, etc. 

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25. Cloudify – Open-source, multi-cloud orchestration platform

With Cloudify, users leverage YAML blueprints to define full-stack environments — then deploy, scale, and update them from a single control layer.

One of Cloudify’s standout features is that it acts as an “orchestrator of orchestrators.” This means it integrates with existing tools such as Terraform, Ansible, and Kubernetes to facilitate automation across different platforms.

DevOps and platform teams use it to build self-service environments or manage hybrid infrastructure. It also supports role-based access control, identity integration, and monitoring via Prometheus for enterprise governance.

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26. CoreStack – Next-gen cloud business accelerator

CoreStack aggregates cost, security, operations, and compliance into one clean dashboard. You can manage AWS, Azure, Google Cloud, and more without juggling different tools.

CoreStack is also built around a smart, modular approach. It offers FinOps to cut waste, ecOps for security and compliance, and CloudOps for operational efficiency. These modules provide real-time insights, automate routine tasks, and enforce policies across diverse cloud environments.

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IT System Monitoring Tools For DevOps

Monitoring and observability tools give teams real-time visibility into system health, performance, and uptime. They help detect issues early, reduce downtime, and keep services running smoothly. T

27. Sematext – Cloud monitoring service

There are dozens of cloud monitoring tools, but Sematext provides an all-in-one monitoring platform. 

You can monitor front-end and back-end logs, APIs, applications, and multiple cloud environments from one place. Sematext lets DevOps teams monitor everything from networks, containers, microservices, databases, and servers. 

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Data Protection And Backup Tools

In the cloud, protecting your data is as important as storing it. These tools help prevent data loss, enable fast recovery, and ensure business continuity, whether from accidental deletion, system failure, or cyber threats.

28. Carbonite by OpenText – Data governance platform

Carbonite offers data protection, migration, and backup services for homes, small businesses (professionals), and enterprises (business solutions). 

The service replicates virtual, cloud, and physical workloads with push-button failover to ensure that business-critical systems are always available. Carbonite’s automatic cloud backup service supports various environments, devices, and cloud platforms, such as MySQL, Hyper-V, and Oracle.

Other Data protection, backup, and recovery services include Zscaler, Google Cloud Storage, Forcepoint, Dropbox, and OneDrive.  

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Collaboration And Productivity Tools

Cloud-native collaboration tools help teams stay organized, share knowledge, and work together in real time, no matter where they are. 

29. Notion – Document collaboration and file-sharing

Notion provides a workspace, collaboration tool, knowledge base, and file-sharing platform in one. Teams can easily share knowledge, workflows, schedules, project progress, etc., and get work done without putting together multiple tools. Instead of starting from scratch, you can choose and modify a template.

Notion is also well-known for its note-taking capabilities. It enables you to record insights, ideas, and progress statuses from meetings, brainstorming sessions, etc., and share them with others or edit them later.  

Some Notion alternatives include Confluence, Bit.ai, Google Workspace, ProofHub, etc.

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Data Integration And Management Platforms

These platforms help organizations unify data from multiple sources, clean it, and prepare it for analytics and reporting. They support ETL/ELT workflows, ensure data quality, and power modern business intelligence in the cloud.

30. Informatica – Cloud data integration platform

Informatica can combine data from multiple sources for analysis and business intelligence with ELT, ETL, Spark processing, or a fully managed serverless solution. It’s also available on-premises. The platform also features application integration, data cleansing/quality, API management, etc., in one platform and usage-based pricing. 

More data integration tools include Talend Cloud Integration, Oracle Integration Cloud Service, SnapLogic, etc. 

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Related read: 30+ Essential ETL Tools For Data Pipelines

Now that you know the top tools by category, here’s how to pick the one that fits your cloud strategy.

How To Choose The Right Cloud Computing Tool

Choosing a cloud tool isn’t about finding the most features but finding the right fit. Here are key things to consider before you decide:

What next?

Optimize Your Cloud Computing Usage And Costs With CloudZero

Cloud computing is one of the best developments in modern business. Cloud users can leverage IaaS, PaaS, and SaaS to get to market quickly, utilize managed cloud services, and enjoy pay-per-use pricing. 

But while the cloud offers nearly limitless elasticity, it can quickly become a complex maze with little visibility into costs and usage. Unless you can see which specific features, customers, environments, teams, projects, etc., are driving those costs, you won’t know how to optimize them without hurting customer experiences. 

to see how to reduce your cloud computing costs within a week or two, not months.