SigNoz vs AWS CloudWatch: In-Depth Comparison 2026

AWS CloudWatch is the default monitoring tool for AWS workloads, but its costs compound fast at scale and it lacks native distributed tracing. SigNoz is an open source observability platform that offers full stack visibility with OpenTelemetry native support, but requires self hosting unless you opt for SigNoz Cloud.

CloudWatch has no native OpenTelemetry receiver, while SigNoz is built entirely on OpenTelemetry from day one.

This guide compares SigNoz and AWS CloudWatch across pricing models, signal depth, deployment complexity, and real world operational trade offs. Each section includes sourced limitations and cost breakdowns for teams at three scales: small (10 hosts, 2TB/month), mid market (50 hosts, 10TB/month), and enterprise (200 hosts, 40TB/month).

Quick Comparison: SigNoz vs AWS CloudWatch

Feature	SigNoz	AWS CloudWatch
Pricing model	$0.30/GB SigNoz Cloud or self hosted OSS	Per metric, log bytes, trace spans, alarms, dashboards
Deployment	Self hosted or SigNoz Cloud SaaS	AWS managed service only
OpenTelemetry	Native OTel receiver and storage	No native OTel support, requires ADOT collector
Distributed tracing	Native full fidelity traces	Basic X-Ray integration, separate service
Log management	Unified with traces and metrics	Separate CloudWatch Logs, basic search
Dashboarding	Native Grafana style UI	CloudWatch dashboards or third party tools
Data residency	Full control when self hosted	Data stored in AWS region only
Best for	Teams wanting full stack OTel observability with data control	AWS native teams, basic monitoring, no tracing needs

SigNoz Overview

SigNoz is an open source observability platform that provides APM, distributed tracing, metrics, and logs in a single interface. It was built from the ground up on OpenTelemetry, making it the only major open source APM that natively ingests, stores, and queries OTel signals without translation layers.

Core capabilities

SigNoz collects traces, metrics, and logs through the OpenTelemetry Collector. Traces are stored in ClickHouse for fast querying, metrics use a time series database, and logs are indexed alongside trace context for unified debugging. The UI surfaces service maps, RED metrics (rate, errors, duration), and flame graphs for every distributed transaction.

Deployment model

SigNoz can run self hosted in your Kubernetes cluster, on VMs, or via SigNoz Cloud (managed SaaS). Self hosting gives full data control and avoids egress fees. SigNoz Cloud offers the same feature set without operational overhead, starting at $199/month for 100GB of ingested telemetry.

Pricing structure

SigNoz Cloud charges $0.30/GB for combined traces, metrics, and logs. Self hosted SigNoz is free OSS, but you pay for infrastructure (ClickHouse, Kafka if used, compute). A 50 node cluster generating 10TB/month typically costs $3,000/month on SigNoz Cloud or $1,200 to $1,800/month in AWS infrastructure costs when self hosted.

What SigNoz does well

Native OpenTelemetry means zero proprietary agents. If you already instrument with OTel, SigNoz ingests your data without modification. Trace and log correlation is automatic because both are indexed together. Service dependency graphs update in real time without manual configuration. The UI is fast, teams report dashboards loading 3 to 4 times faster than Grafana on large trace datasets.

Documented limitations

SigNoz lacks advanced anomaly detection and ML based alerting found in enterprise APM tools. Alert rules are manual threshold based definitions. The self hosted version requires operational expertise, users on GitHub report that upgrading SigNoz can break custom dashboards if ClickHouse schema changes. SigNoz Cloud mitigates this but removes data residency control.

Community users note that retention beyond 30 days requires additional ClickHouse storage tuning. A GitHub issue from early 2025 documents that querying traces older than 90 days slows significantly without partitioning optimization.

AWS CloudWatch Overview

AWS CloudWatch is Amazon’s managed monitoring and observability service for AWS resources and applications. It collects metrics, logs, events, and alarms natively from AWS services like EC2, Lambda, RDS, and ECS without installing agents.

Core capabilities

CloudWatch Metrics tracks resource utilization and service health. CloudWatch Logs ingests application and system logs with basic search and filtering. CloudWatch Alarms trigger notifications when metrics breach thresholds. AWS X-Ray provides basic distributed tracing for AWS services and Lambda functions. CloudWatch dashboards visualize metrics and logs, though users frequently export data to Grafana for richer analysis.

Deployment model

CloudWatch is a fully managed AWS service. No installation is required. Logs and metrics flow automatically from AWS services once enabled. For custom application metrics and logs, you install the CloudWatch Agent on EC2 instances or container tasks. All data is stored in AWS, retention is configurable per log group and metric namespace.

Pricing structure

CloudWatch pricing is granular and multi dimensional. Metrics cost $0.30 per custom metric per month. Logs cost $0.50/GB ingested and $0.03/GB per month stored. Alarms cost $0.10 per alarm per month for standard metrics, $0.30 for high resolution metrics. Dashboards cost $3 per month per dashboard. X-Ray tracing costs $5 per million traces recorded and $0.50 per million traces retrieved. Contributor Insights and anomaly detection are billed separately.

A common pain point documented on Reddit and AWS forums is that CloudWatch’s itemized pricing makes cost forecasting difficult. One r/aws thread from late 2025 describes a team’s bill increasing from $400 to $2,800/month after enabling detailed monitoring and custom metrics on 40 EC2 instances, with no prior warning or cost estimate from AWS.

What CloudWatch does well

CloudWatch integrates natively with every AWS service. EC2 instance metrics, Lambda invocation counts, RDS database connections, and ECS task CPU all flow automatically without configuration. For teams running entirely on AWS with basic monitoring needs, CloudWatch provides zero setup observability.

CloudWatch Logs Insights offers a query language for log analysis, though it lacks the full text search speed of Elasticsearch or ClickHouse. Alarms integrate directly with SNS, Lambda, and Auto Scaling, making it easy to trigger automated responses to threshold breaches.

Documented limitations

CloudWatch has no native support for OpenTelemetry. To send OTel data to CloudWatch, you must run the AWS Distro for OpenTelemetry (ADOT) collector, which translates OTel signals into CloudWatch’s proprietary formats. This adds operational complexity and latency.

Distributed tracing in CloudWatch requires AWS X-Ray, a separate service with its own SDK instrumentation. X-Ray does not correlate with CloudWatch Logs automatically, teams report having to manually link trace IDs to log entries. A GitHub discussion from early 2026 notes that X-Ray sampling is aggressive by default, often capturing less than 5% of traces, making rare errors hard to debug.

CloudWatch’s per metric pricing punishes high cardinality data. A Kubernetes cluster with pod level metrics across 50 nodes can generate 10,000+ unique metric series, costing $3,000/month in metric fees alone before log ingestion. One DevOps engineer on Hacker News documented that enabling detailed EC2 monitoring across 100 instances added $720/month in metric costs with no prior estimate provided by AWS.

CloudWatch dashboards are functional but limited. Users frequently export CloudWatch data to Grafana for richer visualization, which requires setting up a CloudWatch data source and managing API rate limits. Log search in CloudWatch Logs Insights is slower than Elasticsearch based tools for high volume queries, with some queries timing out after 15 minutes on large log groups.

Feature by Feature Comparison

OpenTelemetry Support

SigNoz is built natively on OpenTelemetry. It runs the OpenTelemetry Collector as its core ingestion pipeline, storing OTel traces, metrics, and logs without transformation. If your application is already instrumented with OTel SDKs, SigNoz receives that data directly over OTLP (OpenTelemetry Protocol).

AWS CloudWatch has no native OpenTelemetry receiver. To send OTel data to CloudWatch, you must deploy the AWS Distro for OpenTelemetry (ADOT) collector, which translates OTel signals into CloudWatch Metrics, CloudWatch Logs, and X-Ray trace formats. This adds an extra hop and operational complexity. The ADOT collector must be configured, scaled, and monitored separately.

ADOT exporter configuration also introduces vendor lock in. Once you translate OTel to CloudWatch’s proprietary formats, switching to another observability backend requires reconfiguring exporters and potentially re instrumenting applications.

Distributed Tracing

SigNoz provides full fidelity distributed tracing out of the box. Every trace span is stored in ClickHouse, making it queryable by service, endpoint, duration, status code, or any custom attribute. Trace flame graphs surface the exact microservice or database query causing latency. Logs emitted during a trace are automatically linked, so you can jump from a slow trace span directly to the relevant log lines.

AWS CloudWatch does not provide distributed tracing natively. You must use AWS X-Ray, a separate service that requires installing the X-Ray SDK or daemon in your application. X-Ray’s default sampling rate is 1 request per second plus 5% of additional requests, meaning most traces are never captured. For high traffic APIs handling 1,000 requests per second, only ~55 traces per second are recorded.

X-Ray traces do not automatically correlate with CloudWatch Logs. To link them, you must manually emit the X-Ray trace ID into your application logs and then query CloudWatch Logs Insights with that trace ID. SigNoz does this automatically because traces and logs share the same storage and indexing layer.

Log Management

SigNoz indexes logs alongside traces and metrics in ClickHouse. Log search is fast even at scale, queries return results in under a second for millions of log lines. Logs are automatically enriched with trace context, service names, and Kubernetes pod labels if running in a cluster. The UI lets you filter logs by log level, service, time range, or free text search.

AWS CloudWatch Logs stores logs in log groups and streams. Each application or service writes to its own log group. CloudWatch Logs Insights provides a query language for filtering and aggregating logs, but search speed degrades on large log groups. Some teams report that queries on log groups with 500GB+ of data time out after 15 minutes.

CloudWatch Logs pricing is per GB ingested and per GB stored per month. Retention can be set per log group (from 1 day to indefinite), but longer retention increases storage costs. There is no option to archive logs to cheaper storage tiers without exporting to S3 manually.

Metrics and Dashboarding

SigNoz collects metrics through the OpenTelemetry Collector using scrapers like Prometheus receiver, StatsD receiver, or native OTLP metric export from applications. Metrics are stored in a time series database (Prometheus or ClickHouse depending on deployment mode) and visualized in the SigNoz UI with Grafana style panels.

AWS CloudWatch Metrics automatically collects basic metrics from AWS services (CPU, network, disk, request counts). Custom application metrics require installing the CloudWatch Agent or using the PutMetricData API. Each custom metric costs $0.30 per month. High cardinality metrics (for example, per container metrics in a Kubernetes cluster) become expensive fast.

CloudWatch dashboards are functional but basic. Many teams export CloudWatch metrics to Grafana for richer visualization, which requires setting up a CloudWatch data source and managing API rate limits. SigNoz includes a Grafana style UI natively, so no additional tooling is needed.

Alerting

SigNoz alerting is threshold based. You define alert rules using PromQL style queries on metrics or trace attributes. When a rule breaches, SigNoz sends notifications to Slack, PagerDuty, email, or webhooks. Alert rules can include trace specific conditions, for example, “alert if any API endpoint has P95 latency above 500ms for 5 minutes.”

AWS CloudWatch Alarms trigger when a metric crosses a defined threshold for a specified number of evaluation periods. Alarms can invoke SNS topics, Lambda functions, or Auto Scaling actions. Standard resolution alarms evaluate every 1 minute, high resolution alarms every 10 seconds (at higher cost). CloudWatch supports anomaly detection alarms that use ML to detect deviations from historical baselines, but these cost extra.

CloudWatch does not support alerting directly on log events or trace spans. To alert on log patterns, you must create a metric filter that extracts a numeric value from log lines, then create an alarm on that derived metric. This adds operational complexity and introduces delay.

Data Residency and Compliance

SigNoz self hosted deployments give full data control. All traces, metrics, and logs stay inside your Kubernetes cluster or VPC. This is critical for teams with GDPR, HIPAA, or data localization requirements. SigNoz Cloud stores data in AWS or GCP regions you choose, but data leaves your infrastructure.

AWS CloudWatch stores all data in AWS. Data residency is limited to the AWS region you select when creating resources. For multi region applications, CloudWatch data is scattered across regions unless you centralize it manually using CloudWatch cross region data sharing or export logs to a central S3 bucket.

CloudWatch is SOC 2, ISO 27001, and HIPAA compliant, but some organizations (especially in healthcare, finance, or government) require that telemetry data never leave their own infrastructure. For these teams, CloudWatch is not an option.

Integration and Ecosystem

SigNoz integrates natively with any OpenTelemetry instrumented application or service. It also supports ingesting data from Prometheus exporters, Fluentd, and other observability tools via the OpenTelemetry Collector’s receiver ecosystem. If you already use OTel, SigNoz drops in without re instrumentation.

AWS CloudWatch integrates seamlessly with AWS services but requires agents or SDKs for external systems. CloudWatch Agent runs on EC2, ECS, or on premises servers to collect metrics and logs. For tracing, you must use X-Ray SDKs or the X-Ray daemon. Integrating CloudWatch with non AWS services (for example, on premises databases, third party APIs) requires custom scripting or third party tools.

Pricing Comparison

Pricing estimates below are based on a standardized usage profile. Actual costs vary by retention, data types, alarm count, dashboard count, and AWS region.

Small team scenario

• 10 hosts (EC2 instances or Kubernetes nodes)
• 2TB telemetry per month (1.2TB logs, 600GB traces, 200GB metrics)
• 30 day retention
• 20 alarms, 5 dashboards

SigNoz Cloud: $600/month ($0.30/GB × 2TB)

SigNoz self hosted: $300 to $450/month (AWS infrastructure: ClickHouse on 2× r6g.xlarge, Kafka optional, NAT gateway, EBS storage)

AWS CloudWatch:

• Logs: $600 ingestion ($0.50/GB × 1.2TB) + $36 storage ($0.03/GB × 1.2TB)
• Metrics: $60 (200 custom metrics × $0.30)
• Alarms: $2 (20 alarms × $0.10)
• Dashboards: $15 (5 dashboards × $3)
• X-Ray tracing: $180 (600GB trace data = ~36 million trace spans; $5 per million recorded)
• Total: $893/month

CloudWatch costs more at this scale, but the gap is smaller because metric and alarm counts are still low.

Mid market scenario

• 50 hosts
• 10TB telemetry per month (6TB logs, 3TB traces, 1TB metrics)
• 90 day retention
• 100 alarms, 20 dashboards

SigNoz Cloud: $3,000/month ($0.30/GB × 10TB)

SigNoz self hosted: $1,500 to $2,000/month (AWS infrastructure: ClickHouse on 3× r6g.2xlarge, Kafka, larger EBS volumes, longer retention storage)

AWS CloudWatch:

• Logs: $3,000 ingestion + $540 storage (90 days × 6TB × $0.03/GB)
• Metrics: $300 (1,000 custom metrics × $0.30)
• Alarms: $10 (100 alarms × $0.10)
• Dashboards: $60 (20 dashboards × $3)
• X-Ray tracing: $900 (3TB trace data = ~180 million spans)
• Total: $4,810/month

At mid market scale, CloudWatch costs 60% more than SigNoz Cloud and over 2× the infrastructure cost of self hosted SigNoz.

Enterprise scenario

• 200 hosts
• 40TB telemetry per month (24TB logs, 12TB traces, 4TB metrics)
• 90 day retention
• 500 alarms, 50 dashboards

SigNoz Cloud: $12,000/month ($0.30/GB × 40TB)

SigNoz self hosted: $6,000 to $8,000/month (AWS infrastructure: ClickHouse cluster on 6× r6g.4xlarge, Kafka cluster, distributed storage, longer retention)

AWS CloudWatch:

• Logs: $12,000 ingestion + $2,160 storage (90 days × 24TB × $0.03/GB)
• Metrics: $1,200 (4,000 custom metrics × $0.30)
• Alarms: $50 (500 alarms × $0.10)
• Dashboards: $150 (50 dashboards × $3)
• X-Ray tracing: $3,600 (12TB trace data = ~720 million spans)
• Total: $19,160/month

At enterprise scale, CloudWatch costs 60% more than SigNoz Cloud and 2.4× the infrastructure cost of self hosted SigNoz.

Pricing based on publicly available rate cards as of early 2026. AWS CloudWatch pricing varies by region and usage patterns. SigNoz self hosted costs depend on instance types, storage configuration, and retention policies. Verify current rates on each vendor’s official pricing page.

Hidden CloudWatch costs

The pricing above does not include AWS data transfer fees. CloudWatch charges data transfer out fees when you export logs to S3, send metrics to third party tools, or query data from outside AWS. Data transfer out costs $0.09/GB for the first 10TB per month, $0.085/GB for the next 40TB, and decreases at higher tiers.

For a team exporting 10TB of CloudWatch logs per month to an external SIEM or log analysis platform, data transfer adds $900/month to the bill. SigNoz self hosted has zero data transfer fees because data never leaves your VPC.

CloudWatch also charges for API requests. GetMetricStatistics, PutMetricData, and CloudWatch Logs API calls are billed per request. High frequency queries or dashboards that refresh every 10 seconds can generate millions of API calls per month. AWS charges $0.01 per 1,000 GetMetricStatistics requests, which can add $50 to $200/month for active monitoring dashboards.

Who Should Choose SigNoz

SigNoz is the better choice for:

Teams already using OpenTelemetry: If your applications are instrumented with OTel SDKs, SigNoz ingests that data natively without transformation layers or ADOT collectors. You avoid vendor lock in and retain the flexibility to switch observability backends later.

Organizations with data residency requirements: SigNoz self hosted keeps all telemetry data inside your infrastructure. This is critical for teams in healthcare, finance, or government sectors that cannot send monitoring data to external SaaS platforms.

Engineering teams that need distributed tracing: SigNoz provides full fidelity trace storage and automatic trace log correlation. CloudWatch’s X-Ray integration is a separate service with aggressive sampling and no automatic log linking.

Cost conscious teams at scale: Beyond 5TB/month of telemetry, SigNoz becomes significantly cheaper than CloudWatch. The flat per GB pricing model makes cost forecasting straightforward, while CloudWatch’s multi dimensional pricing (metrics, logs, alarms, dashboards, traces) creates billing surprises.

Teams willing to self host: SigNoz self hosted offers the lowest total cost of ownership but requires operational expertise. You must manage ClickHouse, Kafka (optional), and the SigNoz backend. SigNoz Cloud removes this burden but costs more than self hosted.

Who Should Choose AWS CloudWatch

AWS CloudWatch is the better choice for:

AWS native teams with basic monitoring needs: If your entire stack runs on AWS and you only need basic metrics, logs, and alarms, CloudWatch requires zero setup. EC2, Lambda, RDS, and ECS metrics flow automatically without installing agents.

Teams without distributed tracing requirements: If your application is a monolith or you don’t need trace level debugging, CloudWatch Metrics and Logs may be sufficient. Adding X-Ray for tracing increases complexity and cost.

Organizations already locked into AWS tooling: If your team uses AWS Systems Manager, AWS Config, and AWS Security Hub, CloudWatch integrates seamlessly. Switching to SigNoz would require exporting data or running parallel monitoring stacks.

Teams that prefer fully managed services: CloudWatch is fully managed by AWS. No infrastructure to provision, no upgrades to manage, no ClickHouse tuning required. SigNoz self hosted adds operational overhead, SigNoz Cloud reduces this but still requires monitoring backend health.

Small scale deployments: For teams with under 2TB/month of telemetry and fewer than 20 hosts, CloudWatch’s itemized pricing may be cheaper than SigNoz Cloud, especially if you only use basic metrics and logs without tracing.

Verdict

SigNoz and AWS CloudWatch serve different use cases. CloudWatch is the default choice for AWS native teams that need basic monitoring with zero setup. SigNoz is the better choice for teams that need full stack observability with OpenTelemetry, distributed tracing, and data control, especially at scale.

Choose SigNoz if: You want OpenTelemetry native observability, need distributed tracing with automatic log correlation, have data residency requirements, or monitor more than 5TB of telemetry per month.

Choose AWS CloudWatch if: Your entire stack runs on AWS, you only need basic metrics and logs without tracing, you prefer fully managed services, or your telemetry volume is under 2TB/month.

Consider CubeAPM if: You want the OpenTelemetry compatibility and full stack observability of SigNoz but prefer managed deployment inside your own VPC. CubeAPM offers $0.15/GB pricing with unlimited retention, self hosted architecture, and vendor managed operations. It runs in your cloud, giving data sovereignty without the operational burden of managing ClickHouse and Kafka yourself.

Disclaimer: The information in this article reflects the latest details available at the time of publication and may change as technologies and products evolve. Features, pricing, and plan limits can change over time. Always verify the latest information directly with the vendor before making purchasing or deployment decisions.

Frequently Asked Questions