Best CloudWatch Alternatives to Improve Monitoring and Visibility

Amazon CloudWatch is often a tool teams inherit rather than choose. It comes pre-wired with AWS, captures basic resource health out of the box, and supports single-cloud monitoring with minimal configuration. For teams running entirely within AWS at modest scale, that's usually enough.

The moment the cracks appear is usually when infrastructure gets more complex. A second cloud gets added, Kubernetes adoption grows, or a FinOps review surfaces costs no one was tracking. That's when the tool starts costing you more time (and money) during incidents.

The best CloudWatch alternatives deliver three things: multi-cloud visibility, predictable economics, and correlated telemetry that turns incident response into root-cause analysis instead of tool-switching.

Key takeaways: CloudWatch alternatives

• CloudWatch works well for AWS-only environments but creates visibility gaps in multi-cloud or hybrid architectures.
• The best alternatives consolidate metrics, logs, traces, and events into a single platform, reducing context switching during incidents.
• Pricing models vary significantly. Evaluate the total cost of ownership, not just per-unit rates.
• New Relic correlates telemetry across applications, infrastructure, and cloud services with AI-powered insights, reducing the operational fragmentation that slows incident resolution in multi-cloud environments.

What is Amazon CloudWatch, and why look for alternatives?

CloudWatch is AWS's native monitoring service, built to collect, visualize, and analyze metrics, logs, and events from AWS resources. Within a single-cloud AWS environment, it does the basics well: tight service integration, no extra agents to install, and solid baseline coverage for resource health.

The limitations usually appear as environments become more distributed and operational requirements become more complex.

• Costs you can't see. CloudWatch billing is layered: detailed monitoring per resource, custom metrics per dimension, GetMetricData API calls per dashboard refresh, log ingestion per GB, and cross-account data transfer. Each one is small. Together, they often produce monthly bills that surprise even the platform leads who configured them.
• Work you can't share. CloudWatch metrics, logs, and traces (X-Ray) are three separate products with three separate query models. Engineers investigating a production incident don't get a single view — they get three console tabs and a stack of context switches. The cost shows up as longer MTTR.
• Data you can't reach. CloudWatch only natively sees AWS. If you've added Azure, GCP, on-premises, or even SaaS dependencies, you're either maintaining a second monitoring tool per environment or accepting that part of your stack is dark.
• Decisions you can't make. Because CloudWatch is fragmented and AWS-specific, it can't tell you what you most need to know during a multi-cloud incident: how latency in one region correlates with deploys in another, which customer segments are affected, and what the business impact is. The data exists—it's just locked in different rooms.

None of these is a reason to abandon CloudWatch entirely, but they should prompt you to evaluate whether it's still the right primary monitoring layer for the complexity you're actually managing.

Top CloudWatch alternatives for modern infrastructure monitoring

The platforms below were selected based on their ability to address CloudWatch's core limitations across multi-cloud environments, telemetry correlation, and operational complexity. Every tool featured has a 4-star rating or higher on G2, and all claims were sourced directly from verified user feedback to ensure recommendations are grounded in actual practitioner experience rather than marketing claims.

Every platform featured below has a 4-star rating or higher on G2. The descriptions and considerations are based on verified user feedback and publicly available product information rather than vendor positioning alone.

New Relic

New Relic is a unified observability platform that consolidates metrics, events, logs, and traces into a single interface. It ingests telemetry from AWS, Azure, GCP, and on-premises infrastructure, correlating telemetry across infrastructure, applications, and cloud services to help teams investigate root causes more efficiently. With native AWS CloudWatch Metric Streams integration, teams can maintain existing data flows while gaining cross-platform visibility.

• Metrics, events, logs, and traces in one queryable data model, with automatic correlation across signals
• 750+ integrations, including native AWS, Azure, GCP, and Kubernetes monitoring
• AI-powered anomaly detection and automated root cause analysis
• Consumption-based pricing tied to data ingested and users, not host count
• NRQL (New Relic query language) for custom queries and dashboards without predefined views

Why users like it: Users often highlight the unified telemetry model, flexible querying, and native AWS integrations in G2 reviews.

Considerations: Teams migrating from CloudWatch may need to adjust existing workflows, though the CloudWatch Metric Streams integration helps to ease the transition.

Best for: Organizations managing multi-cloud or hybrid infrastructure who need complete visibility across distributed systems without operational fragmentation.

Datadog

Datadog is a monitoring and analytics platform that provides visibility across infrastructure, applications, and logs. It originated as an infrastructure monitoring tool and has expanded into full-stack observability, supporting teams managing distributed cloud environments and microservices architectures.

• 600+ integrations covering cloud platforms, containers, databases, and SaaS tools
• Infrastructure monitoring with auto-discovery for cloud resources and containers
• APM with distributed tracing across microservices to identify latency bottlenecks
• Unified view of metrics, traces, and logs with Watchdog AI for anomaly detection and root cause suggestions
• Synthetic monitoring and real user monitoring (RUM) for frontend visibility

Why users like it: Users frequently mention Datadog's integrations, dashboards, and broad monitoring coverage.

Considerations: Pricing scales with host count and custom metrics, making cost forecasting difficult as infrastructure grows.

Best for: Engineering teams with complex, integration-heavy environments who need flexible visualization and broad third-party tool support.

Dynatrace

Dynatrace is an enterprise-grade observability platform built around automated discovery and AI-powered analytics. Its proprietary OneAgent technology automatically instruments applications and infrastructure, capturing full-stack traces without manual configuration.

• Automatic dependency mapping via OneAgent across hosts, containers, and cloud services
• Davis AI engine for deterministic root cause analysis across metrics, traces, and logs
• Full-stack observability covering APM, infrastructure, RUM, and synthetic monitoring
• Native integrations with AWS, Azure, Google Cloud, and Kubernetes
• Business analytics that connect application performance to customer experience metrics

Why users like it: Users often highlight automated discovery, dependency mapping, and AI-assisted troubleshooting workflows.

Considerations: The platform's depth and automation come with a steeper learning curve, particularly for teams accustomed to simpler monitoring tools.

Best for: Large enterprises with complex application architectures that want to minimize manual instrumentation and use AI-driven insights for faster troubleshooting.

Grafana Cloud

Grafana Cloud extends the open-source Grafana visualization platform with managed services for metrics, logs, and traces. It is commonly used by teams already running Prometheus or other open-source monitoring tools.

• Managed Prometheus, Loki (logs), and Tempo (traces) with cloud scalability
• Full compatibility with existing Grafana dashboards and plugins
• Usage-based pricing with a generous free tier for smaller deployments
• Multi-cloud support across AWS, Azure, GCP, and on-premises environments
• Large community-driven plugin library for custom integrations and data sources

Why users like it: Users often value the platform's open-source ecosystem, customization options, and flexible visualization capabilities.

Considerations: Teams may need to manage separate data sources for metrics, logs, and traces, which can require more manual correlation than fully unified platforms.

Best for: Teams with established Grafana workflows or strong preferences for open-source tooling who want managed scalability without switching visualization platforms.

Splunk Observability Cloud

Splunk Observability Cloud brings together metrics, traces, and logs for enterprise-scale monitoring across cloud-native and hybrid environments. Built on the SignalFx acquisition, it offers real-time streaming analytics with support for high-cardinality telemetry and large-scale distributed systems.

• Real-time streaming architecture with sub-second latency for immediate anomaly detection
• NoSample™ tracing captures 100% of traces for complete distributed transaction visibility
• Unified metrics and APM in a single interface 
• AI-driven analytics that baseline normal behavior and surface statistically significant deviations
• Multi-cloud support via pre-built integrations and OpenTelemetry compatibility

Why users like it: Users frequently cite real-time analytics, streaming telemetry, and detailed distributed tracing capabilities.

Considerations: Pricing can become complex at scale, and teams new to the Splunk ecosystem often report a steeper onboarding process compared to some alternatives.

Best for: Large enterprises with existing Splunk investments who want to unify observability and security analytics, or teams managing extremely high-volume telemetry data.

When is it time to look for a CloudWatch alternative?

Before benchmarking alternatives, work through four questions about your own situation. The right answer depends on whether CloudWatch is still doing the job you need it to do, or whether your infrastructure requirements have outgrown it.

1. How AWS-deep is your architecture? If 100% of your workloads are in AWS and likely to stay there, an AWS-native tool might still fit your scale. But verify what “AWS-native” buys you. Most modern alternatives ingest CloudWatch data directly via Metric Streams, so you don’t lose AWS visibility when you switch. You expand visibility across the rest of your infrastructure alongside it.
2. What's your real CloudWatch bill? Before comparing per-unit pricing across platforms, calculate what CloudWatch costs today: detailed monitoring per resource, custom metrics, GetMetricData API calls, log ingestion, and cross-account data transfer. Many teams underestimate these combined costs. A platform with a higher subscription price can still be cheaper in practice once all operational costs are accounted for.
3. Where does correlation live in your incident workflow? If your incident process involves switching between CloudWatch Metrics, CloudWatch Logs, and X-Ray — or pulling data into Athena to investigate after the fact — that usually points to fragmented telemetry workflows. Unified observability platforms are designed to correlate metrics, logs, traces, and infrastructure data in a single environment to support faster root cause analysis.
4. Who owns observability, and is that role explicit? Teams that inherited CloudWatch often don’t have a clearly defined observability strategy or owner. Evaluating alternatives is an opportunity to define how monitoring, troubleshooting, and telemetry management scale alongside the business. Some platforms are built for mature observability teams. Others support organizations that are still building those processes.

If two or more of these areas are creating operational friction, it may be time to evaluate whether CloudWatch should remain your primary monitoring layer, even if it continues running alongside a broader observability platform during migration.

What changes when you move from CloudWatch to unified observability?

Teams that adopt unified observability often improve both operational visibility and incident response speed. For example, Credit Sense, a financial services platform running on AWS, reduced its AWS bill by 26% and cut time-to-diagnose by 80% after adopting New Relic’s unified observability platform.

The team mapped AWS resources to the customer-facing services they supported, attached unit costs, and tracked spend continuously to identify inefficient infrastructure usage. The same instrumentation also improved incident investigations by giving engineers shared visibility across infrastructure, applications, and telemetry data.

Other examples include Infomedia, which reduced AWS costs by 40%, and Entrata, which reduced severe incidents to zero following its cloud migration.

The good news is that you don't have to abandon CloudWatch entirely to get there. Platforms like New Relic ingest CloudWatch data directly through Metric Streams, allowing teams to maintain AWS-native visibility during a phased migration. That approach lets teams validate workflows and telemetry coverage before retiring overlapping tooling.

Improve monitoring and visibility with New Relic

Whether you chose CloudWatch or inherited it, the real question is whether to keep it as your primary monitoring layer or move on.

If your stack still fits inside AWS and your engineering team isn't feeling friction during incidents or surprises on the AWS bill, CloudWatch may still be the right primary layer. For others, fragmented telemetry, rising operational overhead, and slower troubleshooting workflows can make unified observability a better fit.

New Relic was built for teams making that decision. It ingests CloudWatch data natively, so AWS visibility continues during a phased migration without requiring a full rip-and-replace approach. From there, it correlates AWS telemetry with application performance, multi-cloud infrastructure, logs, and traces in a single data model, helping engineers investigate incidents without switching between disconnected tools and dashboards. Pricing scales with data ingested and users, not host count or API calls, so costs remain more predictable as infrastructure grows.

Book a demo to see how unified observability changes the way your team monitors AWS—and the rest of your stack alongside it.

FAQs about CloudWatch alternatives

Can I use CloudWatch alongside other monitoring tools, or do I need to fully migrate?

Yes. Most teams run CloudWatch alongside another observability platform during migration, and some continue using both long term. CloudWatch Metric Streams can send AWS metrics directly into third-party platforms, allowing teams to expand visibility across infrastructure, applications, and logs without immediately replacing existing AWS-native monitoring workflows.

How do CloudWatch alternatives handle multi-cloud environments compared to native AWS monitoring?

Most CloudWatch alternatives support AWS, Azure, GCP, Kubernetes, on-premises infrastructure, and SaaS services within a single platform. Instead of monitoring each environment separately, unified observability tools correlate telemetry across distributed systems to support faster troubleshooting, shared dashboards, and more consistent visibility across multi-cloud environments.

What's the typical cost difference between CloudWatch and third-party monitoring solutions?

The cost difference depends on telemetry volume, retention requirements, and how extensively AWS-native services are used. CloudWatch pricing often scales across detailed monitoring, custom metrics, log ingestion, API requests, and data transfer. Some third-party platforms have higher subscription costs but provide more predictable pricing and broader visibility across complex infrastructure environments.