I Tested 30+ Cloud Monitoring Tools: Here Are My Picks

I’ve spent the last three years writing about IT and cloud security, talking to DevOps teams, IT admins, and security pros about their biggest cloud headaches. One thing is clear: managing cloud infrastructure without the right cloud monitoring tools is like flying blind.

I’ve heard stories of teams scrambling to diagnose downtime, dealing with endless alerts that lead nowhere, and struggling with surprise cloud bills. If you’re here, you’re probably facing the same issues. You need a cloud infrastructure monitoring software that doesn’t just flood you with data but helps you take action before things break.

So, I did what I do best. I researched. I also talked to the people who rely on these tools the most: cloud engineers, DevOps teams, and security professionals. Their insights helped me separate the truly useful cloud monitoring tools from the noise.

Whether you’re trying to prevent outages, optimize performance and costs, or strengthen security, I’ve researched 30+ tools to find the best cloud monitoring tools for 2025. Here’s what you need to know.

5 best cloud monitoring tools I recommend  

If you people ask me, “What exactly do cloud monitoring tools do?” I like to keep it simple: they give you a real-time window into your cloud environment, so you’re not flying blind.

From my conversations with IT admins and DevOps teams, I’ve learned that cloud monitoring is all about visibility and control. You don’t just want raw data. You need insights that actually help you take action before issues spiral into full-blown outages.

What makes the best cloud monitoring tools: My criteria

To separate the best from the rest, I focused on key factors that define effective, reliable, and scalable cloud monitoring. 

• Real-time performance monitoring: Cloud environments are dynamic, and performance bottlenecks can escalate quickly. I looked for tools that provide real-time visibility into CPU, memory, network traffic, and storage usage across cloud workloads. The best solutions offer granular monitoring at the instance, container, and Kubernetes pod levels to detect anomalies before they impact applications.
• Intelligent alerting and automation: Alert fatigue is a real problem. A good cloud monitoring tool should prioritize critical alerts and suppress noisy, low-priority ones. I looked for platforms that support AI-driven anomaly detection, threshold-based alerting, and auto-remediation capabilities, such as auto-scaling resources or restarting failed instances without manual intervention.
• Multi-cloud and hybrid cloud support: Most businesses use multiple cloud providers, but not all monitoring tools can handle that complexity. I prioritized solutions that natively support AWS, Azure, Google Cloud, and hybrid deployments without requiring excessive configuration. Cross-cloud visibility, unified dashboards, and API integrations were key factors in this evaluation.
• Security and compliance monitoring: Cloud environments introduce new attack surfaces, so monitoring should include security posture analysis, misconfiguration detection, and compliance auditing for frameworks like SOC 2, ISO 27001, HIPAA, and PCI DSS. The best tools go beyond basic logs and include threat detection, identity monitoring, and automated security policy enforcement.
• Log management and distributed tracing: In modern cloud-native environments, logs and traces provide critical insights. I looked for solutions that support centralized log aggregation, real-time log analysis, and distributed tracing to pinpoint bottlenecks in microservices architectures. The best platforms integrate with ELK Stack, OpenTelemetry, or native log services like AWS CloudTrail.
• Ease of deployment and integration: A monitoring tool should work out of the box without requiring hours of setup. I prioritized solutions with agentless monitoring options, simple API-based integrations, and support for containerized workloads in Kubernetes environments. The ability to integrate with DevOps tools like Terraform, Prometheus, and CI/CD pipelines was also a key factor.
• Cost optimization and resource management: Cloud bills can spiral out of control without proper monitoring. I looked for tools that offer cost analytics, anomaly detection for unexpected spikes, and resource right-sizing recommendations to eliminate wasted cloud spend. The best platforms provide predictive insights that help IT teams optimize resource allocation before costs escalate.

With this in mind, I explored 30+ cloud infrastructure monitoring solutions and found the top 5 that ticked off most of the boxes. While they might not be perfect in every sense, they bring some unique strengths to the table. 

The list below contains genuine user reviews from the cloud infrastructure monitoring software category. To be included in this category, a solution must:

• Monitor the performance of cloud-based applications or services.
• Visually map or display resources and cloud infrastructure.
• Identify abnormal activity or performance.
• Provide best practices to ensure optimal performance.

1. Datadog

Datadog is one of those tools that you can’t ignore when looking for cloud monitoring solutions, it’s everywhere, and for good reason. It offers real-time dashboards, deep observability, and solid integrations, making it a strong choice for cloud infrastructure monitoring.

One of the biggest benefits I see is how much visibility it gives in cloud environments. The ability to deploy Datadog across multi-cloud and on-premise environments and get detailed insights into infrastructure, network traffic, and application performance is a huge plus. 

Based on my research and real user feedback, deploying Datadog is easy, thanks to its straightforward agent installation and extensive pre-built integrations.

I'd say one of the biggest advantages is its wide range of integrations. It connects seamlessly with NGINX, Kubernetes, Docker, AWS, Azure, Google Cloud, and CI/CD pipelines. For incident management and alerting, it syncs with ServiceNow, Slack, Microsoft Teams, Jira, and other tools, so alerts and issues get directed to the right people in real time.

And I highly value how its features work together. The tight integration between logs, metrics, application performance monitoring (APM), database monitoring (DBM), profiling, real-time user monitoring (RUM), and Synthetics means one can easily jump between different data points without switching tools or piecing insights together manually. Whether you are troubleshooting an application slowdown or investigating an infrastructure issue, everything flows seamlessly, making the whole experience far more efficient.

Another thing I appreciate the most is Datadog's alerting system. It’s highly flexible, allowing users to set alerts based on custom conditions. If you tune it right, it makes a huge difference in reducing alert fatigue.

But not every tool is perfect and Datadog also has some quirks. The biggest pain point I've heard from users? The cost. Many have pointed out that it gets expensive fast, especially for growing teams or large-scale deployments. While the pricing is usage-based, it quickly adds up. So, while it’s great, it’s not cheap.

Another issue I’ve observed is the overwhelming UI. While it’s powerful, it can be a lot to take in, especially if you’re new to cloud monitoring. Navigating the interface and setting up custom dashboards can feel clunky at times.

That being said, Datadog stands out as the gold standard for cloud monitoring tools. Would I recommend it? Absolutely, but with a caveat. If you’re a large enterprise or a DevOps team managing a complex cloud environment, Datadog’s visibility and automation can save you time and prevent costly outages.

But if you’re a small team or working on a tight budget, you might find yourself watching your monitoring costs as closely as your cloud performance metrics.

What I dislike about Datadog:

• From what I observed, it’s powerful but not cheap. The pricing is usage-based, and if you’re monitoring a large infrastructure, the costs can skyrocket before you even realize it.
• Based on my research, while Datadog offers tons of data, navigating the dashboard can be intimidating, especially for new users. Some customization options feel a bit clunky.

What G2 users dislike about Datadog: 

"Sometimes, the UI is very overwhelming, especially at the beginning. So many buttons and features make the platform very complex to use, so the learning curve is a bit hard at the beginning. Once you learn to use it, it is really simple and intuitive." 

- Datadog Review, Diego P.

2. LogicMonitor

When it comes to cloud monitoring solutions that "just work" out of the box, LogicMonitor stands out to me. It offers automated discovery of cloud resources, pre-configured monitoring templates, and built-in integrations with AWS, Azure, Google Cloud, and hybrid infrastructure.

At the same time, if the default setup isn’t enough, there’s plenty of room to customize. In fact, what really sets it apart for me is its flexibility. LogicMonitor gives teams the ability to fine-tune almost every aspect of their monitoring setup.

You can customize dashboards, create custom monitoring scripts, adjust alert thresholds, and integrate with third-party tools like ServiceNow, Slack, and PagerDuty. The flexibility allows teams to scale and adapt LogicMonitor to their specific needs while still benefiting from its ease of deployment, in my opinion.

But customization comes with a tradeoff, both in terms of cost and complexity. From what I’ve gathered, while LogicMonitor makes customization possible, it doesn’t always make it easy. Setting up advanced custom monitoring requires time and expertise, and the UI isn’t always intuitive.

LogicMonitor upgraded its UI in late 2023, but users have mixed feelings about it from what I found. While some find it an improvement, while others feel it has added unnecessary friction to their workflow. 

And like Datadog, cost is another factor that frequently comes up when evaluating LogicMonitor. From what I’ve gathered, it’s not the most budget-friendly option on the market. Of course, it replaces multiple monitoring tools, consolidating observability into a single platform. For larger enterprises, this can justify the cost, but for smaller teams with simpler needs, it might be difficult. 

Despite these limitations, LogicMonitor is a strong contender if your team needs deep customization and is willing to invest in fine-tuning.

What I dislike about LogicMonitor:

• From my observation, the UI redesign is a mixed bag. While some users find it an improvement, others say it adds unnecessary friction to workflows
• I agree that LogicMonitor is undeniably a great tool, and that comes with a premium price tag. While the value is there for larger enterprises that need deep customization and hybrid monitoring, smaller teams with simpler needs might find it hard to justify the cost

What G2 users dislike about LogicMonitor:

"The new interface stinks. It's quirky. Hiding Datasources under LogicModules makes it more difficult to view the details.

Most annoying is the navigation of the Resource Tree regardless of the interface. If a device is in multiple high-level groups and you navigate backward, it does not bring you to the folder structure that you used to navigate down."

- LogicMonitor Review,  Tad G. 

3. IBM Instana

From what I learned, IBM Instana has a solid reputation as a real-time observability and application performance monitoring tool for modern hybrid and multicloud environments. It is simple to deploy with a single Instana agent that automatically monitors the entire tech stack. 

Another major advantage is how well Instana provides real-time feedback. Unlike some monitoring tools that introduce delays in surfacing issues, Instana delivers instant visibility into latency problems, slowdowns, and service failures. This makes troubleshooting significantly faster because teams don’t have to dig through logs manually to pinpoint the problem.

From what I found, Instana excels in root cause analysis by automatically correlating application issues with infrastructure performance, making it easier to track down the exact component or service causing the problem. Instead of just displaying raw data, it maps out dependencies between services, traces transactions across distributed systems, and highlights bottlenecks in real time.

This level of automation eliminates much of the guesswork, helping DevOps teams reduce mean time to resolution (MTTR) and address issues before they escalate into full-blown outages, in my view

When it comes to UI, though, the feedback is mixed based on what I found.  While the tool is easy to use, the UI could use some improvements. Finding specific features or configuring dashboards isn’t as smooth as it should be. Also, I think it can provide deeper customization when it comes to alerts and dashboards. Not having this can be frustrating for teams that require deeper customization to match specific workflows. 

Another drawback I found is there's an initial adjustment period to get up to speed with Instana.  The initial complexity may require additional training or onboarding, which can be a challenge for teams that need an out-of-the-box solution. 

 Overall, I'd say IBM Instana is a great choice for real-time application performance monitoring.

What I dislike about IBM Instana:

• While Instana is easy to deploy, I realized fully mastering its features takes time. Advanced configurations, integrations, and monitoring rules aren’t always intuitive, and teams may need extra training to unlock the platform's full potential.
• Based on what I heard from users, Instana’s alerting system works well for basic monitoring, but it doesn’t offer enough granularity for fine-tuned notifications. If you need highly customized alert conditions and thresholds, it can feel restrictive compared to other solutions.

What G2 users dislike about IBM Instana: 

"Initial complexity might require additional time and training for teams to fully exploit the platform's capabilities. Depending on the scale of the deployment, the cost may become a significant factor for some users." 

- IBM Instana Review, Yannick K. 

4. Site24x7

Site24x7 by ManageEngine was a new find for me in this list. It offers a complete suite of monitoring features, from websites, servers, and applications to cloud infrastructure and networks, all in one place.

I really appreciate its ability to keep an eye on multiple resources simultaneously. I think it is particularly useful for smaller IT teams or organizations that need affordable, all-in-one observability. It reduces tool sprawl and makes it easier to track everything from a single pane of glass. 

Another strength I observed is how easy it is to set up and integrate. The onboarding process is quick. It supports agent-based and agentless monitoring, and once deployed, it automatically discovers new resources and starts collecting data. 

Cost-effectiveness is also a major factor that makes Site24x7 stand out in my opinion. Compared to high-end tools like Datadog, which can get expensive fast, Site24x7 offers a much more budget-friendly alternative. It’s especially appealing for startups, SMBs, and IT teams that need robust monitoring without enterprise-level pricing. It may not have all the advanced features of more premium solutions, but for most organizations, the price-to-performance ratio makes it an attractive choice.

But there are some downsides. The UI, while functional, feels outdated, and I think it could use a refresh. Navigation and configuration aren’t as intuitive or user-friendly as I’d like, making some workflows take longer than necessary. Setting up dashboards and fine-tuning alerts, in particular, could be more streamlined.

I also noticed that it is difficult to get started and hard to understand, especially when configuring advanced monitoring settings. While onboarding is fairly quick, getting the most out of Site24x7 takes effort. Once everything is set up, it runs smoothly, but tweaking settings and finding specific features can feel more complicated than it should be.

Regardless of these issues, Site24x7 is still a solid choice for IT teams and businesses looking for a versatile, multi-cloud monitoring solution, especially for those on a budget. 

What I dislike about Site24x7:

• While the UI gets the job done, it isn’t as modern or polished. Navigation and customization could be smoother, and some workflows take longer than they should, based on my observations.
• Fine-tuning alerts and advanced monitoring settings isn’t as intuitive as I’d hoped. Getting started is easy, but fully optimizing the platform takes time and effort.

What G2 users like about Site24x7: 

"Editing user settings on Site24x7 can be a bit cumbersome and less intuitive than expected, requiring multiple steps that could be streamlined for better usability."

- Site24x7 Review, Yuvraj G.

5. Dynatrace

Dynatrace stands out to me for its depth, automation, and AI-driven insights. From what I found, it’s a powerhouse for full-stack observability, making it a great choice for large enterprises that need deep visibility into complex infrastructures.

From what I gathered, it’s easy to integrate Dynatrace’s observability tools with existing infrastructure, making it a good fit for hybrid and multi-cloud environments. Once deployed, the platform provides real-time insights into application performance, infrastructure health, and security risks, all from a single dashboard. It also helps teams keep a pulse on system availability, reducing the likelihood of unexpected outages.

I was impressed by the level of intelligence it brings to monitoring with its Davis AI, an AI engine, and Grail, its database for storing logs, metrics, traces, events, etc. The Problems app, with AI-driven problem detection, automatically identifies performance issues and pinpoints root causes without requiring teams to sift through endless logs, making troubleshooting significantly faster.

Another major strength is Dynatrace’s request tracing capabilities, which provide deep visibility into service dependencies and transaction flows across cloud environments. This allows teams to find bottlenecks, optimize performance, and prevent issues from cascading into larger failures.

But Dynatrace takes time to master. While Davis AI simplifies troubleshooting in the long run, the platform’s sheer depth of features can feel overwhelming at first, requiring training and a structured onboarding process.

Also, the pricing structure is a bit difficult to understand. While Dynatrace offers flexible, per-hour pricing for various features and functionalities, understanding the overall cost can be challenging without a clear grasp of your specific usage patterns. It can make it difficult to predict expenses accurately. And like LogicMonitor and Datadog, if you have high-volume monitoring needs, the price can quickly go up. 

Nonetheless, I'd recommend Dynatrace for enterprises that need deep observability, AI-driven automation, and full-stack monitoring. 

What I dislike about Dynatrace:

• I'd say Dynatrace isn’t the easiest tool to learn right away so many features and settings. While automation makes things easier over time, navigating and fine-tuning dashboards, metrics, and alerts takes effort to fully master.
• Based on what I saw, Dynatrace's pricing structure can be a bit tricky to understand, especially when you're just starting out. The flexibility of per-hour pricing for different features is great, but without a clear understanding of usage patterns, costs can add up faster than expected. 

What G2 users dislike about Dynatrace: 

"They know the value they provide and charge you accordingly, it can be very difficult to digest the cost of the tool, and it can be difficult to manage your organization's consumption of licensing."

- Dynatrace Review, Andrew H.

If cost is your major concern, or if you are a small or medium business with a reasonably manageable cloud infrastructure, I'd suggest going with open-source options like Prometheus, Grafana Labs, Zabbix, or Nagios. These tools may require more manual setup and maintenance, but they offer relatively good monitoring capabilities without recurring subscription fees.

Frequently asked questions (FAQ) on cloud monitoring tools

1. What is cloud monitoring?

Cloud monitoring is the process of tracking and analyzing cloud infrastructure, applications, and services to ensure performance, security, and availability. Using cloud monitoring tools, IT teams can detect issues like slowdowns, outages, and security vulnerabilities before they impact users. These tools provide real-time insights into cloud resources such as servers, databases, and networks.

2. What are the best cloud monitoring tools?

The best cloud monitoring tools offer real-time performance tracking, automated alerting, security monitoring, and cost optimization features. Some top options include Datadog, AWS CloudWatch, Dynatrace, and LogicMonitor. The right tool depends on whether you need cloud application monitoring tools, cloud security monitoring tools, or cloud infrastructure monitoring tools for multi-cloud environments.

3. How do cloud monitoring services work?

Cloud monitoring services collect and analyze performance metrics from cloud-based resources such as virtual machines, containers, and applications. These tools use log management, network monitoring, and anomaly detection to provide visibility into cloud health and security. Some platforms, like AWS CloudWatch and Azure Monitor, are cloud-native, while others, like New Relic and Datadog, support multi-cloud monitoring.

4. How do cloud performance monitoring tools improve efficiency?

Cloud performance monitoring tools track key metrics like CPU usage, memory consumption, disk I/O, and application response times to ensure optimal performance. They help prevent slowdowns, reduce downtime, and automatically scale resources based on demand, making them essential for DevOps and IT operations teams.

5. What are multi-cloud monitoring tools?

Multi-cloud monitoring tools allow IT teams to manage and monitor workloads across multiple cloud providers, such as AWS, Azure, and Google Cloud, from a single dashboard. These tools offer cross-platform performance tracking, cost analysis, and security monitoring, helping businesses maintain consistent performance across different cloud environments.

6. What are the best AWS cloud monitoring tools?

The best AWS cloud monitoring tools include both native AWS services and third-party solutions. AWS CloudWatch provides built-in performance monitoring and logging for AWS resources, while AWS CloudTrail focuses on security and compliance by tracking API activity. Other native tools include AWS  Config, Inspector, and Security Hub.

For more advanced monitoring, third-party tools like Datadog, New Relic, Dynatrace, and LogicMonitor offer deeper observability, AI-powered insights, and multi-cloud support.

7. What are the best Azure cloud monitoring tools?

Like AWS, the best Azure cloud monitoring tools include both native Azure services and third-party solutions. Azure Monitor is the primary built-in tool for tracking performance, security, and logs across Azure resources, while Azure Security Center focuses on threat detection and compliance monitoring. For more advanced observability, third-party tools like Datadog, New Relic, Dynatrace, and LogicMonitor offer deeper insights, AI-driven anomaly detection, and multi-cloud compatibility.

8. What are the best open-source cloud monitoring tools?

Some of the best open-source cloud monitoring tools include Prometheus, Zabbix, Nagios, Grafana, and VictoriaMetrics.

Prometheus is widely used for metrics-based monitoring in cloud-native environments, while Zabbix and Nagios offer full-stack infrastructure monitoring.

Grafana is a powerful visualization tool that integrates with various data sources, and VictoriaMetrics provides a high-performance alternative to Prometheus for large-scale monitoring.

While these tools eliminate licensing costs, they require manual setup, maintenance, and configuration, making them ideal for teams with the resources to manage an open-source solution.

Eyes on the cloud

When it comes to the cloud, I agree that the more complex the environment, the easier it is to lose track of costs, performance bottlenecks, and security risks. But I strongly insist that affordability and necessity should guide your choice of a cloud monitoring tool.

Ask yourself: Why do you need monitoring? What are you tracking? And what value do you expect from it? These non-functional aspects are hard to price but critical for budgeting.

If you're monitoring a single app generating $10K/month, a $2K/month monitoring tool might not be justified. But if you're managing a dozen apps driving $500K/month, that investment could pay off by improving uptime, reducing maintenance costs, and scaling efficiently.

For large-scale enterprises, premium solutions like Dynatrace or Datadog automate workflows and improve response times. But if cost is a concern, open-source options like Prometheus, Grafana Labs, Zabbix, or VictoriaMetrics are better.

At the end of the day, choosing a cloud monitoring tool isn’t just about features. It’s about aligning with your operational needs, budget, and long-term strategy. The right tool should give you confidence in your infrastructure, not just another dashboard to stare at.

Still on the hunt? Explore our categories of monitoring software, from application performance to network, to find the right match for your needs.