Identity and Access Management Access Analyzer helps you to set, verify, and refine your IAM policies by providing a suite of capabilities. Its features include findings for external and unused access, basic and custom policy checks for validating policies, and policy generation to generate fine-grained policies. To start using IAM Access Analyzer to identify external or unused access, you first need to create an analyzer.
External access analyzers help identify potential risks of accessing resources by enabling you to identify any resource policies that grant access to an external principal. It does this by using logic-based reasoning to analyze resource-based policies in your Amazon Web Services environment. An external principal can be another Amazon Web Services account, a root user, an IAM user or role, a federated user, an Amazon Web Services service, or an anonymous user. You can also use IAM Access Analyzer to preview public and cross-account access to your resources before deploying permissions changes.
Unused access analyzers help identify potential identity access risks by enabling you to identify unused IAM roles, unused access keys, unused console passwords, and IAM principals with unused service and action-level permissions.
Beyond findings, IAM Access Analyzer provides basic and custom policy checks to validate IAM policies before deploying permissions changes. You can use policy generation to refine permissions by attaching a policy generated using access activity logged in CloudTrail logs.
This guide describes the IAM Access Analyzer operations that you can call programmatically. For general information about IAM Access Analyzer, see Identity and Access Management Access Analyzer in the IAM User Guide.
tags: - name: Amazon Web Services Timestream Write paths: /: POST: summary: Amazon Web Services Writerecords description: 'Enables you to write your time-series data into Timestream. You can specify a single data point or a batch of data points to be inserted into the system. Timestream offers you a flexible schema that auto detects the column names and data types for your Timestream tables based on the dimension names and data types of the data points you specify when invoking writes into the database. Timestream supports eventual consistency read semantics. This means that when you query data immediately after writing a batch of data into Timestream, the query results might not reflect the results of a recently completed write operation. The results may also include some stale data. If you repeat the query request after a short time, the results should return the latest data. Service quotas apply. See code sample for details. Upserts You can use the Version parameter in a WriteRecords request to update data points. Timestream tracks a version number with each record. Version defaults to 1 when it''s not specified for the record in the request. Timestream updates an existing record’s measure value along with its Version when it receives a write request with a higher Version number for that record. When it receives an update request where the measure value is the same as that of the existing record, Timestream still updates Version, if it is greater than the existing value of Version. You can update a data point as many times as desired, as long as the value of Version continuously increases. For example, suppose you write a new record without indicating Version in the request. Timestream stores this record, and set Version to 1. Now, suppose you try to update this record with a WriteRecords request of the same record with a different measure value but, like before, do not provide Version. In this case, Timestream will reject this update with a RejectedRecordsException since the updated record’s version is not greater than the existing value of Version. However, if you were to resend the update request with Version set to 2, Timestream would then succeed in updating the record’s value, and the Version would be set to 2. Next, suppose you sent a WriteRecords request with this same record and an identical measure value, but with Version set to 3. In this case, Timestream would only update Version to 3. Any further updates would need to send a version number greater than 3, or the update requests would receive a RejectedRecordsException. ' operationId: amazonWebServicesWriteRecords tags: - Amazon Web Services Timestream Write