AWS Amazon Data Lifecycle Manager
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AI ReadinessFoundational (C+)59/100
Agent-ready OpenAPI document · curated by JenticStorageBackup Recoveryhmac8 EndpointsREST
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For Agents
Define and manage Amazon Data Lifecycle Manager policies that automate EBS snapshot and AMI backup schedules with retention rules.
Use for: Create a daily snapshot policy for production EBS volumes, List all lifecycle policies in this account, Update the retention period on an existing snapshot policy, Disable a lifecycle policy during a maintenance window
Not supported: Does not handle snapshot data movement, cross-region copy outside policy actions, or non-EBS resource types - use for declarative EBS and AMI lifecycle policies only.
Jentic publishes the only available OpenAPI specification for Amazon Data Lifecycle Manager, keeping it validated and agent-ready. Amazon Data Lifecycle Manager (DLM) automates the creation, retention, and deletion of Amazon EBS snapshots and AMI backups through declarative lifecycle policies. The API exposes a small surface - create, get, update, and delete policies, plus tag operations - that is purpose-built for treating backup schedules as code. Use it when an agent needs to enforce backup posture across many accounts or to programmatically rotate retention windows as compliance requirements change.
Install Jentic One Beta
Connect the Amazon Data Lifecycle Manager to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Amazon Data Lifecycle Manager, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Famazonaws.com%2Faws-dlm" | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Famazonaws.com%2Faws-dlm" | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with Amazon Data Lifecycle Manager API.
Define declarative backup schedules for EBS volumes via CreateLifecyclePolicy with target tag selectors
Update retention windows, schedules, and resource targets on an existing policy with PATCH /policies/{policyId}
Disable or re-enable policies during maintenance windows by toggling state on UpdateLifecyclePolicy
Inspect existing policies with GetLifecyclePolicy and GetLifecyclePolicies for inventory and compliance
Apply tags to lifecycle policies for cost allocation and team ownership tracking
Decommission policies that target retired workloads with DeleteLifecyclePolicy
Use Cases
Patterns agents use Amazon Data Lifecycle Manager API for, with concrete tasks.
★ Codify EBS Backup Schedules
Replace ad-hoc snapshot scripts with DLM lifecycle policies that target EBS volumes by tag and run on a fixed schedule. CreateLifecyclePolicy defines the cadence, retention, and target resource tags; the policy then runs without further intervention until updated or deleted, ensuring backups are consistent across accounts.
Call CreateLifecyclePolicy with PolicyDetails.ResourceTypes set to VOLUME, a TargetTags filter of Environment=prod, and a schedule of daily snapshots retained for 14 days.
Rotate Retention to Meet Compliance
When auditors increase retention requirements from 14 to 90 days, DLM can update every affected policy in seconds via PATCH /policies/{policyId}. The new retention applies to subsequent snapshots without recreating the policy or losing the existing schedule history.
Call UpdateLifecyclePolicy on policy-0123456789abcdef with PolicyDetails.Schedules[0].RetainRule.Count set to 90 and verify with GetLifecyclePolicy.
Inventory Lifecycle Posture Across Accounts
Run GetLifecyclePolicies in each account and region to build a backup inventory: which workloads are protected, which schedule applies, and which policies are currently disabled. The flat list lets compliance and FinOps teams quickly spot unprotected volumes or over-retained snapshots driving up storage cost.
Call GetLifecyclePolicies, then GetLifecyclePolicy for any policy in DISABLED state to surface gaps.
Agent-Driven Backup Policy Management
An AI agent connected via Jentic can read a compliance change ticket, locate every DLM policy that needs adjusting, and update retention or schedules accordingly. Jentic returns the matching DLM operation and schema so the agent can execute the change with the right PolicyDetails payload and verify it after the update.
Search Jentic for 'update a DLM lifecycle policy', load UpdateLifecyclePolicy, execute it with the new retention, then GetLifecyclePolicy to confirm.
Key Endpoints
8 endpoints — jentic publishes the only available openapi specification for amazon data lifecycle manager, keeping it validated and agent-ready.
METHOD
PATH
DESCRIPTION
POST
/policies
Create a new lifecycle policy
GET
/policies
List lifecycle policies
GET
/policies/{policyId}/
Get a specific policy
PATCH
/policies/{policyId}
Update an existing policy
DELETE
/policies/{policyId}/
Delete a lifecycle policy
POST
/tags/{resourceArn}
Tag a lifecycle policy
GET
/tags/{resourceArn}
List tags on a policy
POST
/policies
Create a new lifecycle policy
GET
/policies
List lifecycle policies
GET
/policies/{policyId}/
Get a specific policy
PATCH
/policies/{policyId}
Update an existing policy
DELETE
/policies/{policyId}/
Delete a lifecycle policy
POST
/tags/{resourceArn}
Tag a lifecycle policy
GET
/tags/{resourceArn}
List tags on a policy
Jentic AI Readiness Score
This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.
A
Amazon Data Lifecycle Manager
- Foundational (C+)59/100
74
Foundational Compliance63
Developer Experience & Jentic Compatibility37
AI-Readiness & Agent Experience94
Agent Usability50
Security100
AI DiscoverabilityPowered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.0
Show dimension breakdown
74
Foundational Compliance
Base layer of spec validity and structural soundness.
Grade: A-Signals: 4
96%
Lint Results
Aggregated quality score from linter diagnostics, weighted by severity.
100%
Resolution Completeness
Percentage of `$ref` references that resolve successfully.
0%
Specification Validity
Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).
100%
Structural Integrity
Structural correctness score based on schema issues using logarithmic dampening.
63
Developer Experience & Jentic Compatibility
Clarity, completeness, and ingestion readiness for developers and tooling.
Grade: B-Signals: 4
0%
Example Density
How richly the API is illustrated with examples.
100%
Example Validity
Percentage of examples that conform to their schemas.
50%
Response Coverage
Percentage of operations with complete response definitions (success, client error, server error).
100%
Tooling Readiness
Health of API ingestion, bundling, and resolution within Jentic pipelines.
37
AI-Readiness & Agent Experience
Semantic breadth, depth, and agent comprehension for AI systems.
Grade: FSignals: 4
48%
Description Coverage
Coverage of descriptions across API elements.
0%
Error Standardization
Coverage of RFC 9457 Problem Details for error responses.
100%
OperationId Quality
Coverage, uniqueness, and casing consistency of operationIds for AI inference.
0%
Summary Coverage
Coverage of summaries across operations/tags/info.
94
Agent Usability
Functional utility, complexity comfort, and AI orchestration readiness.
Grade: A+Signals: 1
94%
Complexity Comfort
Agent comfort level based on API operational and structural complexity.
50
Security
Trust, risk posture, and security compliance.
Grade: C-Signals: 1
50%
Authentication Strength
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
100
AI Discoverability
Findability, semantic richness, and reasoning readiness.
Grade: A+Signals: 1
100%
Descriptive Richness
Clarity and depth of descriptions across API elements.
Score it yourself
Every API in the directory is allowlisted, so you can re-score it with no key required.
npx @jentic/api-scorecard-cli score <openapi-url>Why Jentic?
What agents get from Jentic-routed access to this vendor.
Setup
Wiring Amazon Data Lifecycle Manager by hand means building SigV4 request signing, resolving the regional dlm.{region}.amazonaws.com host, and handling AWS throttling and retries yourself. Through Jentic you install once, import Data Lifecycle Manager from the API Directory, store the AWS access keys once, and your agent calls it.
Permission scoping
DLM puts the policy id in the URL path (/policies/{policyId}), so a rule can pin your agent to one lifecycle policy: it can read and update that policy and nothing else. You choose the operations it may call, so policy deletion is not included unless you add it.
Credential isolation
Your AWS access keys for DLM are stored once, encrypted, by your own Jentic One instance and injected at execution time when the request is signed. They never enter the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'create a DLM lifecycle policy' or 'change snapshot retention', and Jentic returns the matching DLM operation with its input schema so the agent calls the right endpoint without browsing the reference docs.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Amazon Data Lifecycle Manager API through Jentic.
Why is there no official OpenAPI spec for Amazon Data Lifecycle Manager?
AWS does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Amazon Data Lifecycle Manager via structured tooling. It is validated against the live API and kept up to date. Get started with Jentic One, the self-hosted execution layer.
What authentication does the Amazon DLM API use?
DLM uses AWS Signature Version 4 (HMAC) signing with an AWS access key ID and secret access key. Through Jentic, those credentials live encrypted in your Jentic One instance and are injected into signed requests at execution time, so the agent never sees the raw secret access key.
Can I update an existing lifecycle policy without deleting it?
Yes. Call PATCH /policies/{policyId} with the modified PolicyDetails - including schedules and retention rules - and the existing policy is updated in place. The schedule continues without losing history of past runs.
What are the rate limits for the Amazon DLM API?
DLM shares standard AWS service quotas, which are managed per account and region rather than published as fixed per-second limits in the spec. Bulk policy listing should rely on pagination, and ThrottlingException responses should trigger backoff.
How do I create an EBS snapshot policy through Jentic?
Search Jentic for 'create a DLM lifecycle policy', load CreateLifecyclePolicy, then execute it with PolicyDetails.ResourceTypes, TargetTags, and a Schedules array. Run pip install jentic to use the async search and execute pattern.
Does this API actually take snapshots, or only schedule them?
The API only schedules and configures policies. Snapshot creation happens automatically inside AWS based on the policy schedule, and the resulting snapshots appear in the EC2 EBS API rather than in DLM responses.
Can I limit what my agent is allowed to do with the Amazon Data Lifecycle Manager API?
Yes. Because you run Jentic One yourself, your own rules decide which DLM operations and credentials the agent may use. Since DLM puts the policy id in the URL path (/policies/{policyId}), you can pin the agent to a single lifecycle policy so it reads and updates that one policy and nothing else. You choose the operations it may call, so DeleteLifecyclePolicy stays out of reach unless you explicitly allow it.
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