Amazon CloudWatch Alternatives: Top 8 Competitors in 2025

Amazon CloudWatch is tightly integrated with the AWS ecosystem, offering a unified monitoring experience across services like EC2, Lambda, and EKS. It delivers built-in dashboards, alarm-based automation, and seamless metric collection — making it an essential tool for teams operating entirely within AWS. Its convenience and centralized nature have made it the default choice for many cloud-native workloads. Major issues such as metric latency, sluggish UI performance, and cost concerns are pushing individuals to seek solutions with more predictable costs, and with great user experience.  In fact, the global APM and observability market is projected to grow to 16.45 Bn. by 2030, driven largely by demand for cost-efficient, OpenTelemetry-native platforms with better user experiences.

CubeAPM  is an excellent alternative to SolarWinds, offering over 800+ integrations and no egress fees. Designed for OpenTelemetry-native observability, it covers full MELT (Metrics, Events, Logs, Traces), with smart sampling and seamless integration for distributed systems, RUM, synthetics, and infrastructure monitoring. CubeAPM supports self-hosting for full compliance and data localization, offering pricing that’s 60-80% more affordable than traditional vendors.

In this article, we’ll explore the top 7 Amazon CloudWatch alternatives in 2025 — including CubeAPM, Datadog and others. We’ll compare them across key criteria like OpenTelemetry support, smart sampling, deployment flexibility, pricing transparency, and full MELT observability — so you can find the best fit for your team’s scale, budget, and compliance needs.

Top 8 Amazon CloudWatch Alternatives

1. CubeAPM
2. Datadog
3. Dynatrace
4. Coralogix
5. Splunk Appdynamics
6. New Relic
7. Better Stack
8. Sumo Logic

Why Look for Amazon CloudWatch Alternatives?

1. High and Unpredictable Costs at Scale

CloudWatch charges separately for ingestion, custom metrics, dashboards, API usage, and data storage. Costs grow rapidly as telemetry volumes increase — especially for high-frequency metrics or logs. Pricing complexity often results in unpredictable bills that are hard to optimize.

For a mid-sized team ingesting 10 TB (10,240 GB) of logs and traces per month and generating around 1 million RUM events, Amazon CloudWatch’s costs still add up quickly. Log ingestion alone would cost $5,120/month (10,240 GB × $0.50), while storage adds another $307/month (10,240 GB × $0.03). RUM is billed per 100,000 events, typically around $1 per 100K, so 1 million events adds approximately $10/month. This brings the total CloudWatch bill to roughly $5,437/month — and that’s without including metrics, synthetics, or user license fees. In comparison, CubeAPM offers all-inclusive pricing at $0.15/GB, resulting in a flat $1,536/month (10,240 GB × $0.15) — with no extra charges for RUM, metrics, or users. That’s a ~72% cost reduction, with simpler billing, full MELT observability, and built-in compliance features.

As one user notes:

“AWS charges $0.30/month (pro-rated hourly) per custom metric, where each metric is defined by the unique combination of dimensions. When you multiply the number of metric types we’d like to emit (successes, errors, latency, etc) by the number of endpoints we host and call, and the number of customers we host, that number blows up pretty fast and gets quite expensive.”(Reddit 2025)

2. Complex and Unintuitive User Interface

CloudWatch’s UI often feels sluggish and unresponsive, especially when loading dashboards with high-cardinality metrics or large log groups. Engineers report long render times, failed queries, and general friction during debugging workflows. These slowdowns not only hurt productivity but also force many teams to adopt third-party tools like Grafana for visualization. As a user notes:

“The graph feature … is very slow. It takes immense time to load basically due to the large data size.” — Verified G2 reviewer (G2)

3. Metric Latency & Troubleshooting Delays

CloudWatch doesn’t deliver metrics in real time, especially under high ingestion volumes. This delay can stretch incident detection by minutes and complicate autoscaling decisions. For fast-moving systems, these lags translate directly to longer MTTR and reduced reliability.

“Metric latency is the biggest pain point for me, for both scaling and troubleshooting.” — Reddit user pottaargh (reddit)

4. Steep Learning Curve for Configuration

Configuring CloudWatch, especially for alarms, dashboards, and custom metrics, is often cited as complex, requiring a deep understanding of AWS infrastructure and query languages, which can be daunting for new users or non-technical teams. CloudWatch’s setup process, including defining alarms, sampling rules, or custom metrics, involves a steep learning curve. Users must master IAM roles, Logs Insights queries, and X-Ray sampling rules, which can be time-consuming and error-prone. As a user notes:

“The CloudWatch console is the second best thing that I’ve used. It allows to monitor and alert about AWS services… The least helpful thing I came across is that it requires some learning to understand the data and interpret the logs, and other parameters.”(G2)

5. Limited Log Search and Debugging Capabilities

Users find CloudWatch Logs cumbersome for debugging due to difficulties in searching across multiple log groups, lack of shareable links, Searching logs in CloudWatch is a frequent pain point, as users must navigate numerous log groups and streams manually or use Logs Insights, which requires SQL-like queries. The absence of shareable log query links and limited real-time log tailing (outside CLI) frustrates users, especially during one-off debugging. Many prefer third-party tools like ElasticSearch or Datadog for faster, more flexible.

6. Not Built for OpenTelemetry Ecosystem

While AWS offers OpenTelemetry agents, CloudWatch lacks native OTEL semantics, such as semantic conventions, correlation across MELT data types, and vendor-neutral dashboards. OTEL data often requires transformation and context is lost in ingestion.

Criteria for Suggesting Amazon CloudWatch Alternatives

When evaluating CloudWatch alternatives, we considered tools that offer:

1. Native OpenTelemetry Support

Alternatives must support ingestion of OTEL-native telemetry across traces, metrics, and logs without needing translation or vendor-specific agents. This allows teams to avoid lock-in and ensure interoperability.

2. Full MELT Observability

The best alternatives offer Metrics, Events, Logs, and Traces (MELT) under one platform. Bonus if they also include RUM, synthetic monitoring, and error tracking for full visibility from infra to frontend.

3. Transparent and Predictable Pricing

CloudWatch’s pricing is fragmented and opaque. We prioritized platforms with clear per-GB or per-host pricing models that are easy to budget and scale. Real-world benchmarks showed savings of 60–80% for similar telemetry volumes when switching.

4. Smart Sampling

Tools with smart sampling retain only high-value telemetry based on latency, errors, or custom signals, reducing storage costs and improving visibility. CloudWatch’s lack of this feature results in noisy datasets.

5. On-Prem or Private Cloud Deployment

Self-hostable observability platforms are gaining popularity due to compliance, security, and data sovereignty concerns. Teams handling sensitive workloads need deployment flexibility, which CloudWatch doesn’t provide.

6. Fast, Developer-Friendly UI and Alerting

We focused on platforms with faster performance, intuitive interfaces, and modern alerting (e.g., Slack-based, anomaly detection, or service maps) to reduce MTTR and improve engineering experience.

Amazon CloudWatch Overview

Known for:

Amazon CloudWatch is primarily known as Amazon’s native monitoring and observability service for AWS infrastructure. It is widely used for tracking metrics, logs, alarms, and custom events across AWS services like EC2, Lambda, ECS, and RDS. CloudWatch is deeply integrated with the AWS ecosystem and serves as the default monitoring tool for most workloads deployed within it.

Standout Features:

• Tight AWS Integration: Automatic telemetry collection from over 70 AWS services, with no additional configuration required.
• CloudWatch Alarms: Customizable thresholds and alarm-based automation tied to AWS services (e.g., auto-scaling).
• CloudWatch Logs Insights: SQL-like querying for log data with aggregation and filtering options.
• CloudWatch Contributor Insights: Detects high-impact contributors to performance issues (e.g., specific API calls, IPs).
• CloudWatch Application Signals (APM-lite): Lightweight APM with automatic span collection for some AWS-native services.

Key Features:

1. Metrics Collection

Collects standard and custom metrics across AWS services and applications.

2. Log Aggregation & Analysis

Centralized log ingestion, with search and analysis capabilities via Log Insights.

3. Dashboarding

Visual dashboards with custom graphs and widgets, linked to AWS data streams.

4. Alarm System

Allows real-time alerting based on thresholds, anomaly detection, or composite conditions.

5. EventBridge Integration

Seamlessly routes events and triggers automated workflows across AWS services.

6. RUM & Synthetics (Optional)

Real User Monitoring and synthetic canary testing available as separate paid features.

Pros:

• Native to AWS, no setup required for most services
• Highly reliable and horizontally scalable
• Granular access control using IAM
• Deep integration with AWS Lambda, EC2, EKS, RDS, and more
• Flexible alarm configuration and automation with EventBridge

Cons

• Complex User Interface
• High Costs at Scale: Custom metrics ($0.30/metric/month) and log ingestion ($0.50/GB)
• Limited Log Search Capabilities compared to tools like Prometheus.
• Steep Learning Curve: Configuring alarms, custom metrics, and OTEL integrations requires familiarity with AWS
• Fragmented and unpredictable pricing across services (metrics, logs, API, dashboards)
• UI is slow, especially with large datasets
• No self-hosted/on-premise deployment option

Best for:

Cloud-native teams that are 100% committed to AWS and need basic monitoring and alerting without requiring deep APM, smart sampling, or cross-cloud observability. Best suited for DevOps teams already leveraging other AWS-native services.

Pricing & Customer Reviews:

• Pricing:
  • Logs ingestion: $0.50/GB
  • Logs storage: $0.03/GB/month
  • Metrics: $0.30/metric/month (first 10,000 metrics)
  • RUM: ~$1 per 100,000 events (varies by region)
  • Synthetics: $0.0012/run
  • Application Signals (APM): Starts at $0.35/GB for first 10TB
• Customer Reviews:
  • G2 Score: 4.5/5
  • Common praise: Tight AWS integration, reliability, scalability
  • Common complaints: UI slowness, complex billing, limited visualization tools, poor log UX
  • Source: G2 CloudWatch Reviews

Top 8 Amazon CloudWatch Alternatives

1. CubeAPM

Known for

Comprehensive OpenTelemetry-native observability with cost savings and intelligent sampling.

CubeAPM is a robust observability platform designed for enterprises, offering complete MELT coverage (Metrics, Events, Logs, Traces) with rapid data ingestion, compliance-friendly self-hosting, and a 60–80% reduction in total cost of ownership compared to traditional APM tools.

Unlike conventional platforms that depend on cloud-only setups and inflexible pricing, CubeAPM caters to modern teams needing performance, flexibility, and data control. Built with OpenTelemetry as its foundation, it enables real-time ingestion, analysis, and action on telemetry data without proprietary agent lock-in or rising per-user costs.

Its standout strength lies in managing high-throughput observability workloads while maintaining low costs and latency. By processing data on-premises, CubeAPM achieves 2–4x faster response times, quicker dashboards, and stronger compliance, making it ideal for SRE and platform teams handling large-scale, latency-critical environments.

Key Features:

• Intelligent Sampling: Context-driven sampling prioritizes high-value data (e.g., latency spikes, 5xx errors) while reducing noise, lowering ingestion volume and costs.
• Real-Time Tracing & Metrics: Full distributed tracing paired with infrastructure and application metrics.
• Infrastructure Monitoring: Native support for AWS, Kubernetes, and Linux-based infrastructure metrics.
• Synthetic Monitoring & RUM: Emulates user interactions and tracks real-world frontend performance.
• Full OTEL and Prometheus Support: Ingests any telemetry data, avoiding vendor lock-in.

Standout Features:

• Intelligent sampling ensures high signal-to-noise ratio and efficient storage.
• On-premises hosting complies with data residency regulations and eliminates cloud egress fees.
• Unlimited user seats with flat, usage-based pricing—no per-user fees like New Relic or Datadog.
• Seamless migration from Datadog, New Relic, or Uptrace in under an hour.
• High-resolution dashboards with customizable MELT views and anomaly alerts.
• We have 800+ integrations. Lets mention it
• Zero cloud egress costs

Pros:

• Up to 80% cost savings compared to Datadog, New Relic, and others.
• Intelligent sampling optimizes data retention and storage efficiency.
• Comprehensive MELT coverage, including logs, metrics, RUM, synthetics, and error tracking.
• Direct Slack/WhatsApp support from core engineers with rapid response times.
• Built for scalable, self-hosted observability.

Cons:

• Not ideal for teams seeking cloud-only solutions.
• Focused solely on observability, lacking cloud security management features.

Best for:

• Engineering teams prioritizing cost efficiency and telemetry control.
• Startups and mid-sized companies scaling quickly while managing budgets.

Pricing & Customer Reviews:

• Pricing: Ingestion-based pricing at $0.15/GB. Zero cloud egress costs
• Rating: 4.7/5 (based on pilot programs, Slack feedback, and demos).

CubeAPM vs. Amazon CloudWatch

CubeAPM delivers full-stack, OpenTelemetry-native observability — including logs, metrics, traces, infrastructure, RUM, and synthetics — in a single, streamlined platform. Unlike Amazon CloudWatch, which charges separately for ingestion, storage, dashboards, and RUM, CubeAPM offers predictable pricing with no hidden fees. Its smart sampling reduces noise and cost, while support for on-premise or private cloud deployment ensures data localization compliance — something CloudWatch doesn’t support. For teams seeking deep visibility, real-time performance, and transparent billing beyond the AWS ecosystem, CubeAPM is the clear choice.

2. Datadog

Known for:

Cloud-native, all-in-one observability platform with extensive integrations across the DevOps ecosystem. Datadog is a leading SaaS observability solution, offering infrastructure monitoring, APM, log analytics, and security monitoring within a unified control plane, widely adopted for its robust feature set.

Key Features:

• Infrastructure Monitoring: Agent-based metrics for hosts and containers with pre-built dashboards.
• Application Performance Monitoring (APM): Distributed tracing across services, databases, and APIs.
• Log Management: Centralized log collection with Live Tail and search functionality.
• Security Monitoring: Real-time detection of vulnerabilities and compliance issues.
• Synthetic Monitoring & RUM: Simulates user journeys and monitors real frontend performance.
• Custom Dashboards & Alerting: Advanced visualization with threshold, anomaly, and composite alerts.

Standout Features:

• Over 900 integrations with tools like AWS, Kubernetes, Jenkins, and GitHub.
• Watchdog AI engine automatically detects anomalies and trends.
• Unified platform for logs, infrastructure, APM, RUM, and security in one interface.
• High scalability for large, multi-region deployments with real-time metrics.

Pros:

• Feature-rich and mature across all observability domains.
• Strong support for multi-cloud and containerized environments.
• User-friendly dashboards, AI-driven alerts, and comprehensive documentation.
• Seamless integration with modern CI/CD pipelines.

Cons:

• Costly at scale due to fragmented pricing for ingestion, hosts, events, and features.
• Lacks intelligent sampling, relying on fixed-rate probabilistic sampling (1%, 5%), which may miss anomalies.
• Unpredictable billing leads to surprise costs for many users.
• Limited self-hosting options, as it’s SaaS-only, potentially conflicting with data localization needs.
• Charges per user, host, and GB, escalating costs in distributed setups.

Best for:

• Enterprises needing a comprehensive DevOps observability solution, particularly in cloud-native ecosystems.
• Teams with substantial budgets prioritizing ready-to-use integrations and dashboards.

Pricing & Customer Reviews:

• Pricing: APM starts at $31/host/month; logs at $0.1/GB + $1.7/M events (15d); synthetics billed separately; infrastructure starts at $15/host/month.
• G2 Review Rating: 4.4/5.
• Users commend Datadog’s extensive features and integrations but criticize its complex pricing, overages, and vendor lock-in. Performance slowdowns at high volumes are also noted.

Datadog vs. Amazon CloudWatch

Datadog offers a more polished user experience, better cross-stack correlation, and deeper APM capabilities compared to CloudWatch. It supports real user monitoring, synthetics, and service maps out of the box — areas where CloudWatch is either limited or requires piecemeal setup. While Datadog is more expensive due to its per-host and feature-based pricing, it outperforms CloudWatch in terms of usability, real-time analytics, and OpenTelemetry-native workflows.

3. Dynatrace

Known for:

AI-powered, full-stack observability and automation for large-scale enterprise environments. Dynatrace is a premium observability platform renowned for its AI-driven insights (Davis engine), automatic discovery, and deep code-level diagnostics, popular among enterprises with complex hybrid cloud setups.

Key Features:

• Davis AI Engine: Automatically correlates metrics, traces, and logs to identify and predict anomalies.
• Full-Stack Monitoring: Unified visibility from infrastructure to user experience, including synthetics, RUM, and logs.
• Automatic Dependency Mapping: Discovers services, APIs, databases, and their relationships automatically.
• Log Management & Indexing: Context-aware log ingestion with dynamic sampling and indexing.
• Cloud-Native Support: Robust support for Kubernetes, serverless, and multi-cloud environments.
• Code-Level Tracing & Insights: Detailed execution path and bottleneck analysis for JVM, .NET, Node.js, and more.

Standout Features:

• Zero manual configuration with fully automated instrumentation and discovery.
• AI-driven root cause analysis, reducing mean time to resolution (MTTR).
• Business KPI monitoring integrated into observability workflows.
• Application Security Module for vulnerability detection.

Pros:

• Scalable for enterprise-grade environments with strong automation.
• Highly detailed tracing and performance diagnostics.
• Real-time anomaly detection with minimal tuning.
• Seamless support for hybrid cloud and distributed tracing.

Cons:

• High costs and unclear billing for AI, logs, and cloud modules.
• Proprietary agents with limited OpenTelemetry compatibility.
• Less flexible custom dashboards compared to Grafana or CubeAPM.
• Self-hosting is possible but complex compared to OTEL-native platforms.

Best for:

• Large enterprises and Fortune 500 companies needing automated observability at scale.
• Teams seeking predictive diagnostics beyond basic monitoring.

Pricing & Customer Reviews:

• Pricing: $0.08/hour per 8 GiB host (~$57.60/host/month).
• G2 Review Rating: 4.4/5.
• Users praise the automation and Davis AI but highlight pricing opacity, a steep learning curve, and rigid agent-based instrumentation as drawbacks.
• Dynatrace vs. Uptrace: Dynatrace offers deeper observability with automated service maps and predictive AI, unlike Uptrace’s focus on tracing. However, its high cost and lack of OpenTelemetry nativeness make it less accessible. CubeAPM provides a cost-effective, OTEL-native alternative with similar enterprise capabilities.

Dynatrace vs. Amazon CloudWatch

Dynatrace goes far beyond Amazon CloudWatch with its AI-powered root cause detection, automatic dependency mapping, and full MELT observability across hybrid environments. It offers advanced features like code-level diagnostics, real-time topology views, and proactive anomaly detection that CloudWatch lacks entirely. While CloudWatch is limited to AWS-native data and relies on manual setup for deep visibility, Dynatrace provides automatic instrumentation and richer analytics across clouds. That said, Dynatrace’s pricing can be complex and premium-tiered, whereas CloudWatch appears cheaper upfront — though often unpredictable at scale.

4. Coralogix

Known for

Log-focused observability with real-time stream processing and customizable data routing. Coralogix is a contemporary observability platform emphasizing log analytics and cost optimization. Its proprietary Streama™ architecture enables real-time parsing and routing of logs, metrics, and traces before storage, making it a top choice for teams prioritizing control over data ingestion.

Known for:

Splunk AppDynamics is an enterprise-grade APM with in-depth application diagnostics and business transaction monitoring. Integrated into Splunk’s observability suite after Cisco’s AppDynamics acquisition, Splunk AppDynamics targets large organizations needing detailed performance insights tied to business KPIs.

Key Features:

• Business Transaction Monitoring: Tracks complete transaction flows across services and infrastructure.
• Application Performance Management (APM): Provides detailed performance metrics and root-cause diagnostics for application components.
• Infrastructure Visibility: Links application performance to underlying server, container, and cloud metrics.
• Custom Dashboards & Health Rules: Alerts based on business outcomes, user experience, and SLAs.
• Synthetic Monitoring: Proactively identifies performance bottlenecks by simulating user interactions.
• Code-Level Diagnostics: Visualizes code traces and method-level insights for Java, .NET, PHP, and Node.js.

Standout Features:

• Strong application-to-business KPI mapping, aligning IT and business goals.
• Tag-based smart alerting and SLA tracking integrated into the UI.
• Deep diagnostics for monoliths and legacy architectures.
• Enhanced by Splunk’s observability stack for broader log and infrastructure visibility.

Pros:

• Ideal for transaction-heavy applications like e-commerce or financial platforms.
• Highly granular performance insights at method, class, and tier levels.
• Business-focused alerting with SLA and KPI correlation.
• Leverages Splunk’s ecosystem for advanced logging and SIEM.

Cons:

• Complex setup and configuration, especially for custom instrumentation.
• High costs for full-stack deployment, including APM, infrastructure, and synthetics.
• Limited native OpenTelemetry support, relying on agent-driven instrumentation.
• UI feels outdated compared to modern tools like CubeAPM or Grafana.

Best for:

• Large enterprises with Java/.NET applications needing business-centric APM.
• Teams using Splunk for logs or SIEM, seeking a unified ecosystem.

Pricing & Customer Reviews:

• Pricing: $75/host/month, billed annually.
• G2 Review Rating: 4.3/5.
• Splunk AppDynamics vs. Uptrace: AppDynamics offers deeper diagnostics and business KPI tracking than Uptrace but is hindered by agent lock-in, high costs, and setup complexity. Uptrace is simpler and open-source but lacks enterprise-grade features. CubeAPM provides an OTEL-native, business-aware alternative with self-hosting and no per-user fees.

Splunk AppDynamics vs. Amazon CloudWatch

Splunk AppDynamics provides robust application performance monitoring, business transaction tracing, and real-time user insights that go well beyond the basic metrics and logs offered by Amazon CloudWatch. It excels in deep code-level visibility, dynamic baselining, and multi-cloud observability, making it better suited for complex, distributed applications. While CloudWatch is tightly coupled to AWS services and lacks advanced APM or user behavior tracking, AppDynamics offers end-to-end visibility from frontend to backend. However, AppDynamics can be costly and is better suited for enterprises with dedicated ops teams, while CloudWatch offers a simpler, AWS-native baseline.

6. New Relic

Known for:

A usage-based, comprehensive observability platform covering APM, infrastructure monitoring, logs, RUM, synthetics, and mobile telemetry. New Relic is recognized for its unified Telemetry Data Platform (TDP) and NRQL-powered dashboards, offering end-to-end observability.

Key Features:

• Full MELT Observability: Supports metrics, events, logs, traces, RUM, synthetics, and error tracking in a single UI.
• Telemetry Data Platform (TDP): Centralized ingestion and query engine for OTEL, Prometheus, and custom agents.
• Dashboards & NRQL Analytics: Real-time querying and flexible dashboards using New Relic Query Language (NRQL).
• RUM, Synthetics, and Mobile Monitoring: Detailed browser, mobile performance, and uptime monitoring.
• Integrations & Auto-Instrumentation: Auto-instrumentation for multiple languages and platforms, with AWS, Azure, and Kubernetes support.

Standout Features:

• Telemetry Data Lake for unified storage and querying of logs, metrics, and traces.
• Rich NRQL-powered dashboards for deep telemetry analytics.
• Comprehensive MELT support in a single suite, though some features require New Relic agents.

Pros:

• End-to-end observability with a unified interface.
• Flexible ingestion of OpenTelemetry and Prometheus data.
• Strong frontend (RUM) and mobile observability.
• Easy onboarding with auto-instrumentation for many languages.
• Mature alerting, SLOs, and anomaly detection.

Cons:

• Complex pricing with charges for ingestion and per-user licenses, starting at $400/user/month.
• Data residency concerns due to storage in New Relic’s global cloud.
• Limited OTEL support, with reduced feature depth without New Relic agents.
• No intelligent sampling, relying on head-based sampling that may miss key traces.

Best for:

• Mid-to-large DevOps teams seeking quick setup, rich dashboards, and all-in-one observability, comfortable with cloud-only, usage-based pricing.

Pricing & Customer Reviews:

• Free Tier: Perpetual free tier with 100 GB/month of data ingest included.
• Paid: Ingestion-based pricing at $0.35/GB + $400/user/month for full access.
• G2 Rating: 4.4/5.

New Relic vs. Amazon CloudWatch

New Relic delivers full-stack observability with integrated metrics, logs, traces, dashboards, RUM, and synthetics — all accessible through a unified, real-time UI. Unlike Amazon CloudWatch, which separates monitoring components and charges individually for ingestion, storage, and custom metrics, New Relic offers a more cohesive experience with better data correlation and visualization. It also supports OpenTelemetry out of the box and provides faster, more intuitive dashboards. However, New Relic’s pricing can escalate with high ingest volumes, while CloudWatch may appear cheaper at first but becomes costly as workloads scale.

7. Better Stack

Known for:

Log and uptime monitoring with intuitive dashboards and developer-friendly UX. BetterStack (formerly Better Uptime) integrates log monitoring, incident alerting, and uptime checks with sleek, modern dashboards, ideal for developers needing lightweight observability with minimal setup.

Key Features:

• Uptime Monitoring: HTTP, ping, port, and SSL checks with on-call schedules and status pages.
• Log Management: Logging platform with SQL-like search, alerting, and retention controls.
• Incident Management: On-call scheduling, incident tracking, and escalation workflows.
• Team Collaboration: Integrations with Slack, MS Teams, and email for rapid alert routing.
• Custom Dashboards: Modern UI with Markdown support and status reporting.
• Developer Experience: Quick onboarding with YAML config and Git-based alert workflows.

Standout Features:

• Exceptionally clean UI, perfect for startups and indie teams.
• Combines uptime monitoring and log management in one product.
• Free plan with generous limits for basic monitoring.
• Status pages, incident logs, and alerts for public communication.

Pros:

• User-friendly with no steep learning curve.
• Ideal for frontend, APIs, and external service uptime monitoring.
• Fast log search with real-time alerting.
• Simple, elegant dashboards for public or internal status pages.

Cons:

• Lacks distributed tracing or APM, limiting full MELT observability.
• Unsuitable for complex microservices or backend-heavy architectures.
• Limited scalability for logs beyond a few GB/day without premium pricing.
• No support for OpenTelemetry, synthetic monitoring, or intelligent sampling.

Best for:

• Solo developers, startups, and small teams needing basic monitoring and logs.
• Teams seeking a better alternative to Pingdom or basic uptime checkers.

Pricing & Customer Reviews:

• Pricing: Free plan includes 10 monitors, 500MB logs/day, basic alerting; paid plans start at $25 based on traces, logs, and metrics, up to $850.
• G2 Review Rating: 4.6/5.
• Developers praise the UX and simplicity but note the lack of deep APM or observability features.
• BetterStack vs. Uptrace: BetterStack focuses on logs and uptime, while Uptrace emphasizes traces and metrics. Neither offers full-stack observability. For backend or infrastructure monitoring, CubeAPM provides comprehensive MELT coverage with OpenTelemetry and intelligent sampling.

Better Stack vs. Amazon CloudWatch

Better Stack offers a modern, developer-friendly observability experience with real-time log streaming, incident management, and beautiful, customizable dashboards. Unlike Amazon CloudWatch, which suffers from sluggish UI and fragmented services, Better Stack prioritizes speed and usability — especially in log querying and alerting. It also integrates directly with incident response workflows like on-call scheduling and uptime monitoring. However, Better Stack is log-first and lacks native support for traces or deep APM, while CloudWatch at least provides lightweight application signals and native AWS integration. Still, for teams focused on faster logs and alerting, Better Stack is a compelling alternative.

8. Sumo Logic

Known for:

Cloud-native log analytics with integrated security, metrics, and monitoring for enterprise DevSecOps. Sumo Logic is a SaaS-based observability and SIEM platform providing unified visibility across logs, metrics, and security analytics, widely used by enterprises needing compliance-ready cloud observability for AWS, GCP, and Azure.

Key Features:

• Log Management & Analytics: Robust search and correlation engine for real-time log ingestion and visualization.
• Metrics Monitoring: Tracks system and application-level metrics with custom dashboards and alerts.
• Cloud-Native Integrations: Deep support for Kubernetes, AWS, Azure, GCP, and serverless environments.
• Security Analytics (SIEM): Includes threat detection, compliance audits, and incident response.
• Dashboards & Alerting: Pre-built content packs, alerts, and customizable dashboards.
• Machine Learning Insights: Identifies anomalies, outliers, and trends using predictive models.

Standout Features:

• Comprehensive platform for observability and security, ideal for DevSecOps.
• SOC 2, GDPR, HIPAA compliance readiness.
• Query-based log search and visualization, comparable to Splunk and ELK.
• Real-time correlation across telemetry and security events.

Pros:

• Strong log analysis and compliance tools.
• Scalable for large, multi-cloud environments.
• Integrated security and observability workflows.
• Extensive pre-built dashboards for common services.

Cons:

• Expensive, tiered pricing, especially for long-term retention and high ingestion.
• No native OpenTelemetry pipeline, limiting OTEL flexibility.
• Limited tracing support, requiring significant setup for full APM.
• SaaS-only, raising data residency concerns with no self-hosting option.

Best for:

• Enterprises with strong security and compliance needs.
• Teams committed to SaaS infrastructure and log-centric workflows.

Pricing & Customer Reviews:

• Pricing: Starts around $3.30–$4.50 per TB scanned.
• G2 Review Rating: 4.2/5.
• Customers appreciate the security integrations and scalable log management but cite high costs, rigid plans, and limited tracing as reasons to explore alternatives.
• Sumo Logic vs. Uptrace: Sumo Logic offers stronger security analytics and log compliance than Uptrace’s tracing focus. However, neither provides unified MELT observability. CubeAPM combines logs, traces, RUM, and synthetics with predictable pricing and OTEL-native ingestion.

Sumo Logic vs. Amazon CloudWatch

Sumo Logic delivers powerful log analytics, real-time dashboards, and cloud-native monitoring across hybrid and multi-cloud environments — offering greater flexibility than Amazon CloudWatch. It provides more advanced querying, richer visualizations, and faster root cause analysis for high-volume log data. While CloudWatch is tightly tied to AWS with basic log querying and limited customization, Sumo Logic supports OpenTelemetry pipelines and cross-cloud observability. That said, Sumo Logic’s pricing can become unpredictable at scale, similar to CloudWatch, especially when ingestion volumes spike or retention requirements grow.

Conclusion: Choosing the Right Amazon CloudWatch Alternative

As engineering teams scale and adopt modern DevOps practices, many are finding that Amazon CloudWatch’s fragmented pricing, limited UX, and AWS-only architecture no longer meet their evolving observability needs. From delayed metric visibility to the lack of real user monitoring and smart sampling, CloudWatch’s constraints are driving teams to seek platforms that offer real-time performance, cross-cloud flexibility, and predictable cost models.

Why CubeAPM Leads the Pack

Among all CloudWatch alternatives, CubeAPM stands out with its OpenTelemetry-native architecture, full MELT stack coverage (metrics, logs, traces, synthetics, RUM), and intelligent sampling that significantly reduces cost and noise. With transparent, per-GB pricing, no per-user or retention fees, and support for on-premise deployments, CubeAPM is purpose-built for teams that demand speed, compliance, and complete observability without vendor lock-in.

Whether you’re outgrowing CloudWatch’s limitations or looking to consolidate your toolchain under a modern observability platform, CubeAPM delivers the performance, clarity, and savings your team needs — all in one place.