What credentials do I need to connect AWS CloudWatch Metrics to Kondado?

You will need your AWS Access Key ID, Secret Access Key, Region, and the specific Namespace you want to replicate. These credentials enable the cloud-to-cloud connection that allows Kondado to access your cloudwatch statistics and custom metrics without installing local agents.

Does Kondado require IP whitelisting for AWS CloudWatch Metrics connections?

Since this is a cloud-to-cloud connection using AWS API endpoints, you typically do not need to whitelist specific IP addresses in your security groups. The connection authenticates through standard AWS IAM credentials rather than fixed IP ranges, simplifying your network configuration.

How do I select which metric namespaces or data sets to replicate from AWS CloudWatch Metrics?

During setup, Kondado's dynamic mapping interface displays available namespaces and metric categories from your AWS account. You simply select the specific cloudwatch statistics, custom application metrics, or operational data you want to replicate, giving you granular control over which time-series data flows to your destination.

Can I combine AWS CloudWatch Metrics data with other data sources in Kondado?

Yes, you can create cross-platform analyses by blending your cloudwatch statistics with pipelines from databases like PostgreSQL , marketing platforms, or CRM systems. This enables you to correlate infrastructure performance with business outcomes in a single dashboard or warehouse.

Which destinations support AWS CloudWatch Metrics data from Kondado?

You can send your metrics to BigQuery , PostgreSQL , Power BI , Looker Studio , Google Sheets , MySQL, Excel, Redshift, SQL Server, or Amazon S3. This flexibility lets you choose between database storage for historical analysis or BI tools for immediate visualization.

Does Kondado support incremental sync for AWS CloudWatch Metrics?

Yes, Kondado captures new metric data points and updates since your last scheduled run, ensuring you only replicate fresh cloudwatch statistics without reprocessing historical time-series data you already have. This keeps sync times efficient while maintaining complete metric history in your destination.

How often can I schedule updates for my AWS CloudWatch Metrics pipelines?

You can configure automated updates to run as frequently as every 5 minutes or as infrequently as daily, depending on your monitoring needs. This configurable schedule ensures your aws cloudwatch cpu utilization metric trends and operational dashboards stay current without manual intervention.

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Connect AWS CloudWatch Metrics to Any Destination

Centralize your AWS CloudWatch Metrics data to unlock deeper visibility into application performance, infrastructure health, and resource utilization patterns. With Kondado, you can replicate time-series monitoring statistics, custom application metrics, and operational telemetry from your cloud environment to any destination. Typical use cases include tracking cloudwatch statistics over time, analyzing aws cloudwatch cpu utilization metric trends across EC2 instances, and monitoring custom business KPIs built through cloudwatch put_metric_data calls.

Kondado connects to AWS CloudWatch Metrics through a direct, cloud-to-cloud connection via the AWS CloudWatch Metrics API using your AWS Access Key ID, Secret Access Key, Region, and Namespace credentials. Our dynamic mapping system lets you select exactly which metric namespaces, schemas, or data categories to replicate to your chosen destination on a configurable schedule ranging from every 5 minutes to daily. This means you maintain complete control over which cloudwatch statistics flow into your data warehouse, spreadsheet, or BI tool without writing any code.

DevOps engineers and site reliability teams use these pipelines to build proactive monitoring dashboards that correlate infrastructure metrics with application logs. Cloud architects leverage this AWS CloudWatch Metrics analytics capability to optimize resource allocation by analyzing historical performance patterns and predicting capacity needs. Business analysts also benefit by combining operational metrics with revenue data to calculate the true cost of system downtime and infrastructure scaling decisions.

The Kondado platform takes care of refreshing AWS CloudWatch Metrics data, allowing you to stop wasting time with manual work and complex workflows, and focus on analyzing AWS CloudWatch Metrics data in your report, spreadsheet, data warehouse, data lake, or database

Once you configure your AWS CloudWatch Metrics data source below, your monitoring statistics begin flowing to your chosen destination automatically.

Transform raw cloudwatch statistics into actionable intelligence by building executive dashboards that track system availability, latency percentiles, and error rates alongside business metrics. Create detailed reports analyzing aws cloudwatch cpu utilization metric patterns to right-size your compute resources, or build automated alerts in Google Sheets that trigger when custom thresholds breach normal operational baselines. Data teams can calculate aggregate performance scores across distributed microservices and visualize infrastructure health trends in Power BI or Looker Studio.

Enhance your AWS CloudWatch Metrics analytics by blending monitoring data with Salesforce customer records, Google Analytics traffic patterns, or PostgreSQL application databases to identify how infrastructure performance directly impacts user experience and conversion rates.

Scheduled updates keep these analyses current by refreshing your cloudwatch statistics on a configurable schedule, ensuring your operational reports always reflect the latest system state.

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Dynamic data

Kondado automatically reads the schema of your AWS CloudWatch Metrics. All tables, views, and fields available in your account are extracted without manual configuration.

available pipelines

What Kondado extracts

Métricas (Incremental)

Metrics collected incrementally from the last execution

Métricas (Janela Móvel)

Metrics with a configurable moving time window

Integration	Description
Métricas (Incremental)	Metrics collected incrementally from the last execution
Métricas (Janela Móvel)	Metrics with a configurable moving time window

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How to visualize AWS CloudWatch Metrics data in 3 steps

Connect AWS CloudWatch Metrics to dashboards, spreadsheets, or databases — no code required.

Set up AWS CloudWatch Metrics connection

Enter your AWS Access Key ID, Secret Access Key, Region, and Namespace in Kondado to establish the cloud-to-cloud data source. This authenticates your account and enables dynamic mapping of your available cloudwatch statistics.

Select metrics and choose destination

Browse your metric namespaces and select which cloudwatch statistics or custom application data to replicate, then choose where to send your data such as BigQuery, PostgreSQL, Power BI, or Google Sheets.

Visualize in dashboards, sheets, or databases

Build custom reports in Looker Studio or Power BI, analyze raw numbers in Google Sheets or Excel, or query historical metrics directly in PostgreSQL, Redshift, or SQL Server databases for advanced AWS CloudWatch Metrics analytics.

Try out all the features for free for 14 days