Dt Obs Aws logo

Dt Obs Aws

Organization
Dynatrace
dt-obs-aws

AWS cloud resource monitoring including EC2, RDS, Lambda, ECS/EKS, VPC networking, load balancers, S3, DynamoDB, SQS/SNS, and cost optimization. Use when analyzing AWS infrastructure, resource inventory, security compliance, capacity planning, or cost savings. Trigger: "show EC2 instances", "find RDS databases", "VPC resources", "AWS cost optimization", "Lambda functions", "ECS services", "security groups", "unattached EBS volumes", "AWS load balancer topology", "publicly accessible databases", "AWS dashboards". Do NOT use for explaining existing queries, product documentation questions, generic host CPU/memory metrics (use dt-obs-hosts), application-level tracing (use dt-obs-tracing), or log analysis (use dt-obs-logs).

Overview

PublisherDynatrace
Repositorydynatrace-for-ai
Skill namedt-obs-aws
Stars
156
Forks
30
Bundled files
13
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 13 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Dynatrace on GitHub. Read the source before you install it.

Installation

Install the Dt Obs Aws AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Dynatrace/dynatrace-for-ai.git /tmp/dynatrace-for-ai
mkdir -p .claude/skills
cp -r /tmp/dynatrace-for-ai/skills/dt-obs-aws .claude/skills/dt-obs-aws
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dt Obs Aws in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Dt Obs Aws on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Dt Obs Aws is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

AWS Cloud Infrastructure

Monitor and analyze AWS resources using Dynatrace Smartscape and DQL. Query AWS services, optimize costs, manage security, and plan capacity across your AWS infrastructure.

When to Use This Skill

Use this skill when the user needs to work with AWS resources in Dynatrace. Load the reference file for the task type:

  • Inventory: "Show me all EC2 instances in us-east-1"
  • Network: "Find all resources in VPC vpc-abc123"
  • Database: "List all RDS instances with Multi-AZ enabled"
  • Serverless: "Show Lambda functions with VPC access"
  • Cost: "Find unattached EBS volumes for cost savings"
  • Security: "Identify publicly accessible databases"
  • Compliance: "Find resources missing Environment tags"
  • Capacity: "Analyze subnet IP utilization"
  • Troubleshoot: "Map load balancer to instances through target groups"
  • Problem Analysis: "What changed before this AWS problem?" / "What events affected this resource?"
  • Workload Context: "Is this instance behind a load balancer, in an EKS cluster, or managed by ECS?"
  • Events: "Have there been any recent events in AWS affecting this resource?"

Core Concepts

Entity Types

AWS resources use the AWS_* prefix and can be queried using the smartscapeNodes function. All AWS entities are automatically discovered and modeled in Dynatrace Smartscape.

Compute: AWS_EC2_INSTANCE, AWS_LAMBDA_FUNCTION, AWS_ECS_CLUSTER, AWS_ECS_SERVICE, AWS_EKS_CLUSTER Networking: AWS_EC2_VPC, AWS_EC2_SUBNET, AWS_EC2_SECURITYGROUP, AWS_EC2_NATGATEWAY, AWS_EC2_VPCENDPOINT Database: AWS_RDS_DBINSTANCE, AWS_RDS_DBCLUSTER, AWS_DYNAMODB_TABLE, AWS_ELASTICACHE_CACHECLUSTER Storage: AWS_S3_BUCKET, AWS_EC2_VOLUME, AWS_EFS_FILESYSTEM Load Balancing: AWS_ELASTICLOADBALANCINGV2_LOADBALANCER, AWS_ELASTICLOADBALANCINGV2_TARGETGROUP Messaging: AWS_SQS_QUEUE, AWS_SNS_TOPIC, AWS_EVENTS_EVENTBUS, AWS_MSK_CLUSTER

Common AWS Fields

All AWS entities include:

  • aws.account.id - AWS account identifier
  • aws.region - AWS region (e.g., us-east-1)
  • aws.resource.id - Unique resource identifier
  • aws.resource.name - Resource name
  • aws.arn - Amazon Resource Name
  • aws.vpc.id - VPC identifier (for VPC-attached resources)
  • aws.subnet.id - Subnet identifier
  • aws.availability_zone - Availability zone
  • aws.security_group.id - Security group IDs (array)
  • tags - Resource tags (use tags[TagName])

AWS Fields on Logs and Bizevents

AWS-originated logs (fetch logs) carry these fields — no exploration needed:

  • aws.region, aws.account.id, aws.service, aws.log_group, aws.log_stream
  • Plus standard log fields: content, loglevel, timestamp, k8s.*, dt.smartscape.*

AWS-originated bizevents (fetch bizevents) carry:

  • aws.region, aws.account.id, event.type, event.provider

Use filter isNotNull(aws.region) to scope to AWS-originated records.

Relationship Types

AWS entities use these relationship types:

  • is_attached_to - Exclusive attachment (e.g., volume to instance)
  • uses - Dependency relationship (e.g., instance uses security group)
  • runs_on - Vertical relationship (e.g., instance runs on AZ)
  • is_part_of - Composition (e.g., instance in cluster)
  • belongs_to - Aggregation (e.g., service belongs to cluster)
  • balances - Load balancing (e.g., target group balances instances)
  • balanced_by - Inverse load-balancing relationship (e.g., load balancer balanced by target group)

AWS Metric Key Naming Convention

Dynatrace ingests AWS CloudWatch metrics using this pattern:

cloud.aws.<service>.<MetricName>.By.<DimensionName>

The <service> is the lowercase AWS service name, <MetricName> is the CloudWatch metric name (case-preserved), and <DimensionName> is the CloudWatch dimension.

Examples: cloud.aws.ec2.CPUUtilization.By.InstanceId, cloud.aws.lambda.Invocations.By.FunctionName, cloud.aws.rds.CPUUtilization.By.DBInstanceIdentifier

Use timeseries, not fetch, for these metrics. Group by dt.smartscape_source.id to split by entity.

→ See references/metrics-performance.md for the complete metric catalog by service with DQL query templates.


Key Workflows

1. AWS Resource Discovery

Get all AWS resources by type:

dql
smartscapeNodes "AWS_*"
| summarize count = count(), by: {type}
| sort count desc

Filter by account and region:

dql
smartscapeNodes "AWS_*"
| filter aws.account.id == "123456789012" and aws.region == "us-east-1"
| fields type, name, aws.resource.id

Using tags for filtering:

dql
smartscapeNodes "AWS_*"
| filter tags[Environment] == "production"
| summarize count = count(), by: {type, aws.region}

→ For complete resource inventory patterns, see references/resource-management.md

2. VPC Networking Analysis

List all VPCs:

dql
smartscapeNodes "AWS_EC2_VPC"
| fields name, aws.account.id, aws.region, aws.vpc.id

Find resources in a VPC:

dql
smartscapeNodes "AWS_*"
| filter aws.vpc.id == "vpc-0be61db7c5d2d1bd1"
| summarize resource_count = count(), by: {type, aws.subnet.id}
| sort resource_count desc

Analyze security group usage:

dql
smartscapeNodes "AWS_EC2_INSTANCE"
| filter contains(aws.security_group.id, "sg-abc123")
| fields name, aws.resource.id, aws.vpc.id, aws.subnet.id

→ For VPC networking, see references/vpc-networking-security.md
→ For security group patterns, see references/security-compliance.md

3. Database Monitoring

List all RDS instances:

dql
smartscapeNodes "AWS_RDS_DBINSTANCE"
| fields name, aws.account.id, aws.region, aws.vpc.id, aws.availability_zone

Find Multi-AZ databases:

dql
smartscapeNodes "AWS_RDS_DBINSTANCE"
| parse aws.object, "JSON:awsjson"
| fieldsAdd multiAZ = awsjson[configuration][multiAZ]
| filter multiAZ == true
| fields name, aws.resource.id, aws.region

Group by engine type:

dql
smartscapeNodes "AWS_RDS_DBINSTANCE"
| parse aws.object, "JSON:awsjson"
| fieldsAdd engine = awsjson[configuration][engine]
| summarize db_count = count(), by: {engine, aws.region}
| sort db_count desc

→ For database monitoring, see references/database-monitoring.md

4. Serverless and Container Workloads

List Lambda functions:

dql
smartscapeNodes "AWS_LAMBDA_FUNCTION"
| fields name, aws.account.id, aws.region, aws.vpc.id

Find ECS services in a cluster:

dql
smartscapeNodes "AWS_ECS_SERVICE"
| traverse "belongs_to", "AWS_ECS_CLUSTER"
| fields name, aws.resource.id, aws.region

List EKS clusters:

dql
smartscapeNodes "AWS_EKS_CLUSTER"
| fields name, aws.account.id, aws.region, aws.vpc.id

→ For serverless, see references/serverless-containers.md
→ For containers, see references/serverless-containers.md

5. Load Balancer Topology

Complete load balancer to instance mapping:

dql
smartscapeNodes "AWS_ELASTICLOADBALANCINGV2_LOADBALANCER"
| parse aws.object, "JSON:awsjson"
| fieldsAdd dnsName = awsjson[configuration][dnsName], scheme = awsjson[configuration][scheme]
| filter scheme == "internet-facing"
| traverse "balanced_by", "AWS_ELASTICLOADBALANCINGV2_TARGETGROUP", direction:backward, fieldsKeep:{dnsName, id}
| fieldsAdd targetGroupName = aws.resource.name
| traverse "balances", "AWS_EC2_INSTANCE", fieldsKeep: {targetGroupName, id}
| fieldsAdd loadBalancerDnsName = dt.traverse.history[-2][dnsName],
            loadBalancerId = dt.traverse.history[-2][id],
            targetGroupId = dt.traverse.history[-1][id]

→ For load balancing, see references/load-balancing-api.md

6. Cost Optimization

Find unattached EBS volumes:

dql
smartscapeNodes "AWS_EC2_VOLUME"
| parse aws.object, "JSON:awsjson"
| fieldsAdd state = awsjson[configuration][state]
| filter state == "available"
| fields name, aws.resource.id, aws.availability_zone, aws.account.id

Analyze EBS costs by type:

dql
smartscapeNodes "AWS_EC2_VOLUME"
| parse aws.object, "JSON:awsjson"
| fieldsAdd volumeType = awsjson[configuration][volumeType],
            size = awsjson[configuration][size],
            state = awsjson[configuration][state]
| summarize total_volumes = count(), total_size_gb = sum(size), by: {volumeType, state}
| sort total_size_gb desc

→ For cost optimization, see references/cost-optimization.md

7. Security and Compliance

Find publicly accessible databases:

dql
smartscapeNodes "AWS_RDS_DBINSTANCE"
| parse aws.object, "JSON:awsjson"
| fieldsAdd publiclyAccessible = awsjson[configuration][publiclyAccessible]
| filter publiclyAccessible == true
| fields name, aws.resource.id, aws.vpc.id, aws.account.id

Security group blast radius:

dql
smartscapeNodes "AWS_EC2_INSTANCE"
| traverse "uses", "AWS_EC2_SECURITYGROUP"
| summarize instance_count = count(), by: {aws.resource.name, aws.vpc.id}
| sort instance_count desc
| limit 20

→ For security, see references/security-compliance.md

8. Resource Ownership and Tagging

Find untagged resources:

dql
smartscapeNodes "AWS_*"
| filter isNull(tags)
| fields type, name, aws.resource.id, aws.account.id, aws.region

Cost allocation by cost center:

dql
smartscapeNodes "AWS_*"
| filter isNotNull(tags[CostCenter])
| summarize resource_count = count(), by: {tags[CostCenter], type}
| sort resource_count desc

→ For resource ownership, see references/resource-ownership.md


Common Query Patterns

PatternTemplate
DiscoverysmartscapeNodes "AWS_*" | fieldsAdd <attrs> | filter <cond> | summarize <agg>
Config parsingsmartscapeNodes "AWS_<T>" | parse aws.object, "JSON:awsjson" | fieldsAdd f = awsjson[configuration][field]
TraversalsmartscapeNodes "AWS_<SRC>" | traverse "<rel>", "AWS_<TGT>"
Multi-typesmartscapeNodes "AWS_T1", "AWS_T2" | filter <cond> | summarize count(), by: {type}

Best Practices

Query Optimization

  1. Filter early by account and region
  2. Use specific entity types (avoid "AWS_*" wildcards when possible)
  3. Limit results with | limit N for exploration
  4. Use isNotNull() checks before accessing nested fields

Configuration Parsing

  1. Always parse aws.object with JSON parser: parse aws.object, "JSON:awsjson"
  2. Use consistent field naming: fieldsAdd configField = awsjson[configuration][field]
  3. Check for null values after parsing
  4. Use toString() for complex nested objects

Security Fields

  1. Security group IDs are arrays - use contains() or expand
  2. Parse aws.object for detailed security context
  3. Check publiclyAccessible, storageEncrypted, and similar flags
  4. Validate IAM role assumptions

Tagging Strategy

  1. Use tags[TagName] for filtering by specific tag value
  2. tags is a JSON object, not an array — use isNull(tags) for untagged resources, never arraySize(tags)
  3. Use isNull(tags[TagName]) to find resources missing a specific tag
  4. Implement consistent tag naming conventions
  5. Track tag coverage with summarize operations

Limitations and Notes

Smartscape Limitations

  • AWS object configuration requires parsing with parse aws.object, "JSON:awsjson"
  • AWS metrics are available as Dynatrace metrics using the cloud.aws.* naming convention (see AWS Metric Naming Convention)
  • Resource discovery depends on AWS integration configuration
  • Tag synchronization may have slight delays

Relationship Traversal

  • Use direction:backward for reverse relationships (e.g., target group → load balancer)
  • Use fieldsKeep to maintain important fields through traversal
  • Access traversal history with dt.traverse.history[-N]
  • Complex topologies may require multiple traverse operations

General Tips

  • Use getNodeName() for human-readable resource names
  • Handle null values gracefully with isNotNull() and isNull()
  • Combine region and account filters for large environments
  • Use countDistinct() for unique resource counts

When to Load References

This skill uses progressive disclosure. Start here for 80% of use cases. Load reference files for detailed specifications when needed.

Load vpc-networking-security.md when:

  • Analyzing VPC topology and connectivity
  • Investigating security group configurations
  • Finding resources by security group
  • Troubleshooting network interface issues

Load database-monitoring.md when:

  • Managing RDS instances and clusters
  • Analyzing database engine distributions
  • Checking Multi-AZ configurations
  • Monitoring cache clusters

Load serverless-containers.md when:

  • Working with Lambda functions
  • Analyzing ECS/EKS deployments
  • Investigating container networking
  • Planning serverless migrations

Load load-balancing-api.md when:

  • Mapping load balancer topologies
  • Analyzing target group health
  • Working with API Gateway
  • Configuring CloudFront

Load messaging-event-streaming.md when:

  • Managing SQS queues and SNS topics
  • Analyzing EventBridge event buses
  • Working with Kinesis or MSK
  • Monitoring Step Functions

Load resource-management.md when:

  • Conducting resource audits
  • Analyzing tag compliance
  • Finding unattached resources
  • Planning regional distribution

Load cost-optimization.md when:

  • Identifying cost savings opportunities
  • Analyzing storage costs
  • Finding unused resources
  • Optimizing instance types

Load capacity-planning.md when:

  • Planning capacity expansions
  • Analyzing resource utilization
  • Monitoring subnet IP usage
  • Sizing auto-scaling groups

Load security-compliance.md when:

  • Conducting security audits
  • Checking encryption status
  • Analyzing IAM roles
  • Finding public resources

Load resource-ownership.md when:

  • Implementing chargeback
  • Tracking resource ownership
  • Allocating costs by team
  • Managing multi-account environments

Load events.md when:

  • Investigating what changed before or during a problem
  • Checking for recent CloudFormation stack deployments
  • Reviewing AWS Auto Scaling activity (scale-in/scale-out)
  • Checking AWS Health service events affecting a resource

Load workload-detection.md when:

  • Determining how an EC2 instance is orchestrated (ECS, EKS, Batch, ASG, standalone)
  • Following a resolution path that depends on the workload pattern
  • Understanding the blast radius of an instance failure

References


Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Dt Obs Aws AI skill do?

AWS cloud resource monitoring including EC2, RDS, Lambda, ECS/EKS, VPC networking, load balancers, S3, DynamoDB, SQS/SNS, and cost optimization. Use when analyzing AWS infrastructure, resource inventory, security compliance, capacity planning, or cost savings. Trigger: "show EC2 instances", "find RDS databases", "VPC resources", "AWS cost optimization", "Lambda functions", "ECS services", "security groups", "unattached EBS volumes", "AWS load balancer topology", "publicly accessible databases", "AWS dashboards". Do NOT use for explaining existing queries, product documentation questions, ge...

Why use Dt Obs Aws on TypingMind?

Because you install it once and use it with any model. Dt Obs Aws is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Dt Obs Aws in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Dynatrace/dynatrace-for-ai/tree/main/skills/dt-obs-aws. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Dt Obs Aws?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Dt Obs Aws?

As many as you like. As long as a model supports skills, you can use Dt Obs Aws with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Dt Obs Aws AI skill free?

Yes. It is published on GitHub by Dynatrace under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇