Chat with your AWS CloudWatch Metrics data

AI to analyze AWS CloudWatch Metrics data with Claude and ChatGPT

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No credit card required | 14 days | 10 million records | 30 pipelines

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AWS CloudWatch Metrics
You
What was our peak EC2 CPU utilization during yesterday's traffic surge?
EC2 Performance
Your EC2 instances peaked at 87% CPU utilization at 14:30 UTC, triggering auto-scaling 12 minutes later.
Via Kondado MCP
You
How many 5xx errors did our load balancer report this week?
API Health
Your Application Load Balancer logged 1,247 5xx errors this week, representing 0.04% of total requests.
Via Kondado MCP
You
Which RDS instance showed the highest read latency today?
Database Ops
The production RDS cluster recorded peak read latency of 18ms at 09:15 AM, 3x higher than average.
Via Kondado MCP
You
What is the current memory utilization across our Lambda functions?
Serverless Metrics
Your Lambda functions are averaging 64% memory utilization, with 12% of invocations nearing the 512MB limit.
Via Kondado MCP
Works in Claude, ChatGPT and any MCP client

AI to analyze AWS CloudWatch Metrics data with Claude and ChatGPT

Connect Claude, ChatGPT, or any MCP client to your AWS CloudWatch Metrics data and ask questions in natural language about your infrastructure performance and application health. Business teams can query operational KPIs, investigate latency spikes, or compare resource utilization across periods without writing SQL or navigating complex monitoring consoles. Simply chat with your AI assistant to uncover insights about EC2 performance, database load, or API traffic patterns.

Kondado replicates AWS CloudWatch Metrics data and exposes it via an MCP server, enabling direct analysis through Claude, ChatGPT, and other compatible clients. The platform provides 2 distinct pipelines covering incremental metric collection and moving window analytics, making time-series operational data accessible through conversational AI. The same replicated data also powers ready dashboards in Power BI and Looker Studio for visual monitoring.

Operations managers use this to spot performance bottlenecks before they impact customers, while finance teams analyze resource consumption patterns to optimize cloud spending. E-commerce managers track application availability during high-traffic events, and engineering leads validate infrastructure scaling decisions by asking about CPU trends, memory utilization, or request volume comparisons directly in chat.

I prefer ready dashboards

Dashboard templates in Power BI and Looker Studio, connected to your AWS CloudWatch Metrics data by Kondado in minutes.

View AWS CloudWatch Metrics dashboards →

I want to ask the AI

Claude, ChatGPT and other MCP clients query your AWS CloudWatch Metrics data in natural language.

View MCP setup →

The pipelines below deliver comprehensive AWS monitoring data structured for AI analysis. Query the Métricas (Incremental) pipeline to examine metrics collected incrementally from your last execution, ideal for tracking daily API request volumes, EC2 CPU utilization trends, or Lambda invocation counts as they accumulate. The Métricas (Janela Móvel) pipeline provides configurable moving time-window analytics, enabling you to ask about rolling average response times, compare error rates across specific business hours versus peak periods, or analyze database connection patterns over sliding intervals. Cross-analyzing both pipelines allows you to correlate recent incremental spikes with historical moving averages, identifying whether current latency represents a true anomaly or expected seasonal variation for your infrastructure. With automated updates on a configurable schedule, your AI assistant always references current operational data when answering questions about application health and resource performance.

How to connect AWS CloudWatch Metrics to Claude, ChatGPT and other AI clients

MCP is an open standard. Add the Kondado server to the connections of Claude (Web or Desktop), ChatGPT, or any other MCP client you use, and authorize via OAuth at app.kondado.com.br. Setup through the UI, no code.

Kondado MCP server: https://mcp.kondado.io/mcp
Detailed guide: Claude Detailed guide: ChatGPT
AI vocabulary

AWS CloudWatch Metrics tables and metrics available via Kondado

Each item below is something Claude, ChatGPT or another MCP client already knows how to query — no schema setup, no manual mapping.

2
Tables
∞
Ad-hoc questions
Métricas (Incremental)
Metrics collected incrementally from the last execution
Métricas (Janela Móvel)
Metrics with a configurable moving time window
Full docs on the wiki → Connect AWS CloudWatch Metrics now →

How to connect and use AI with your data

In 3 steps: connect on Kondado, pick dashboard or chat, analyze.

1
Connect AWS CloudWatch Metrics at app.kondado.com.br

Log into Kondado at app.kondado.com.br, add AWS CloudWatch Metrics as a data source, and select a Via Kondado destination. Your operational data lands ready for immediate AI access and for powering the dashboard templates.

2
Add Kondado MCP server in Claude or ChatGPT

Open the connection settings in Claude Web or Desktop, or in ChatGPT, and add the Kondado MCP server. Authorize once via OAuth at app.kondado.com.br to enable natural language querying of your metrics.

3
Ask about metrics or open ready dashboards

Start chatting with Claude or ChatGPT using natural language to investigate AWS CloudWatch Metrics data. For recurring visual monitoring, open the ready Power BI or Looker Studio dashboard templates using the same replicated data.

Other connectors with AI via MCP

Same Kondado data, in chat through Claude, ChatGPT and other MCP clients.

CRM and Sales

ActiveCampaign ActiveCampaign
Bitrix24 CRM Bitrix24 CRM
Exact Sales Exact Sales
Hubspot Hubspot
Infusionsoft (Keap) Infusionsoft (Keap)
Meetime Meetime
NectarCRM NectarCRM
Pipedrive Pipedrive
PipeRun PipeRun
Ploomes Ploomes
RDStation CRM RDStation CRM
Salesforce Salesforce

Marketing and Automation

Google Ads Google Ads
E-goi E-goi
Google Search Console Google Search Console
Hi Platform Hi Platform
Huggy Huggy
Linkedin Linkedin
MailChimp MailChimp
Mandrill Mandrill
Mautic Mautic
Pushwoosh Pushwoosh
RDStation RDStation
Salesforce Marketing Cloud (Exact Target) Salesforce Marketing Cloud (Exact Target)
SenseData SenseData
Taboola Taboola
Twilio Twilio
WordPress WordPress

Advertising and Media

Apple App Store Apple App Store
Bing Bing
Criteo Criteo
Facebook Facebook
Facebook Ads Facebook Ads
Google Play Store Google Play Store
Instagram Ads Instagram Ads
Meta Ads Meta Ads
Microsoft Ads Microsoft Ads
Microsoft Advertising Microsoft Advertising
Pinterest Ads Pinterest Ads
TikTok Ads TikTok Ads
X Ads X Ads
YouTube YouTube

E-commerce and Marketplaces

Bling! Bling!
Hotmart Hotmart
Loja Integrada Loja Integrada
Mercado Libre Mercado Libre
Nuvemshop (Tiendanube) Nuvemshop (Tiendanube)
Olist Tiny Olist Tiny
Omie Omie
Pagar.me Pagar.me
Shopify Shopify
Tiny ERP Tiny ERP
Tray Tray
VNDA VNDA
VTEX VTEX
Wake Commerce Wake Commerce

Financial and Payments

ASAAS ASAAS
ContaAzul ContaAzul
Fatura Simples Fatura Simples
Granatum Granatum
Superlogica Superlogica
Sympla Sympla

Support and Customer Service

55pbx 55pbx
api4com api4com
Blip (take) Blip (take)
Clockify Clockify
EADBOX EADBOX
Freshdesk Freshdesk
Movidesk Movidesk
Recruiterbox Recruiterbox
Stilingue Stilingue
Wootric Wootric
Zendesk Zendesk
Zendesk Chat (Zopim) Zendesk Chat (Zopim)

Databases

Azure Table Storage Azure Table Storage
BigQuery BigQuery
InfluxDB v1 InfluxDB v1
MongoDB MongoDB
MySQL (& MariaDB) MySQL (& MariaDB)
Oracle Oracle
PostgreSQL PostgreSQL
SQLServer SQLServer
Webhook Webhook

Productivity and Collaboration

ClickUp ClickUp
Google Sheets Google Sheets
Jira Jira
monday.com monday.com
Notion Notion
Pipefy Pipefy
Tangerino Tangerino
Toggl Toggl
Trello Trello

Social Media

Instagram Instagram
TikTok Organic TikTok Organic

User Analytics

Google Analytics GA4 Google Analytics GA4
Mixpanel Mixpanel
Zeeng Zeeng

Storage and Transfer

Amazon S3 Amazon S3
FTP FTP
Google Cloud Storage Google Cloud Storage
See all AI connectors →

Related on Kondado

Frequently asked questions about AI

How ready dashboards and chat via Claude / ChatGPT work together with your data via Kondado.

What kind of infrastructure questions can I ask Claude or ChatGPT about my AWS CloudWatch Metrics data? ▼
You can ask about EC2 instance performance trends, RDS database latency patterns, application load balancer request volumes, or Lambda function error rates. The AI analyzes your replicated time-series data to answer specific questions like peak CPU utilization periods or comparative resource usage across different AWS services.
How do I configure Claude or ChatGPT to access my AWS CloudWatch Metrics data through Kondado? ▼
In Claude Web or Desktop, or directly in the ChatGPT interface, navigate to the connection settings and add the Kondado MCP server. You will authorize access once via OAuth at app.kondado.com.br, granting the AI read-only access to your replicated metrics without any command line setup.
Can the AI execute actions on my AWS infrastructure or modify CloudWatch alarms? ▼
No, the AI provides read-only analytical chat. It can analyze your historical and current metrics data to answer questions about trends and performance, but it cannot start instances, modify thresholds, or trigger any actions within your AWS environment.
How frequently does the AWS CloudWatch Metrics data update in the AI chat? ▼
Data replicates on a configurable schedule you set in Kondado, ensuring your AI assistant references fresh metrics when answering questions. You can adjust the frequency based on your monitoring needs, from frequent updates for critical systems to periodic refreshes for standard reporting.
What dashboard templates are available for visualizing AWS CloudWatch Metrics besides the AI chat? ▼
Kondado offers ready report templates in Power BI and Looker Studio that use the same replicated AWS CloudWatch Metrics data. These provide visual monitoring capabilities for recurring operational reviews, while the AI chat handles ad-hoc investigative questions.
What is the difference between asking the AI about my metrics and opening a ready dashboard? ▼
The AI chat in Claude or ChatGPT allows flexible, ad-hoc questioning about specific operational scenarios using natural language, such as investigating sudden latency spikes. Ready dashboards in Power BI or Looker Studio provide structured visual monitoring for recurring KPI tracking and standardized operational reports.
Do other MCP clients besides Claude and ChatGPT work with Kondado? ▼
Yes, while Claude and ChatGPT are the primary supported interfaces, any MCP-compatible client can connect to Kondado's server. This includes other AI assistants and tools that implement the open Model Context Protocol standard.
Which specific AWS services can I analyze through the AI chat using CloudWatch Metrics? ▼
You can analyze metrics from EC2 instances, RDS databases, Lambda functions, Application Load Balancers, and any other AWS service publishing to CloudWatch. The two available pipelines capture both point-in-time incremental data and rolling window analytics for comprehensive operational visibility.

Try out all the features for free for 14 days