| agent: | Auto Exec |
What is an "Expert"? How do we create our own expert?
Add credentials for various integrations
Managing workspaces and access control
DagKnows Architecture Overview
Setting up SSO via Azure AD for Dagknows
Enable "Auto Exec" and "Send Execution Result to LLM" in "Adjust Settings" if desired
(Optionally) Add ubuntu user to docker group and refresh group membership
Deployment of an EKS Cluster with Worker Nodes in AWS
Adding, Deleting, Listing DagKnows Proxy credentials or key-value pairs
Comprehensive AWS Security and Compliance Evaluation Workflow (SOC2 Super Runbook)
AWS EKS Version Update 1.29 to 1.30 via terraform
Instruction to allow WinRM connection
MSP Usecase: User Onboarding Azure + M365
Post a message to a Slack channel
How to debug a kafka cluster and kafka topics?
Open VPN Troubleshooting (Powershell)
Execute a simple task on the proxy
Assign the proxy role to a user
Create roles to access credentials in proxy
Install OpenVPN client on Windows laptop
Setup Kubernetes kubectl and Minikube on Ubuntu 22.04 LTS
Install Prometheus and Grafana on the minikube cluster on EC2 instance in the monitoring namespace
update the EKS versions in different clusters
AI agent session 2024-09-12T09:36:14-07:00 by Sarang Dharmapurikar
Parse EDN content and give a JSON out
Check whether a user is there on Azure AD and if the user account status is enabled
Get the input parameters of a Jenkins pipeline
Distribution Analysis of AWS Normalized Usage
This task showcases the distribution of normalized usage amounts across AWS services. The normalized usage amount is a standardized metric that provides a consistent unit of measure across different AWS services, allowing users to better understand and compare their consumption patterns. The histogram, offers insights into the commonality of various usage levels and highlights trends or anomalies in service consumption.
Normalized Usage in the context of AWS Cost and Usage Reports refers to a consistent metric that AWS provides across various services. With the myriad of AWS services available, each has its unit of measurement — for instance, EC2 might be measured in hours of instance usage, S3 in GB-months, and Lambda in GB-seconds. These disparate units make it challenging to compare the usage of one service against another directly. Hence, AWS offers a "normalized" metric, which standardizes these varied measurements into a consistent unit. This allows users to aggregate and compare the consumption of different AWS services more easily.
X-axis (Normalized Usage Amount): Represents different levels of normalized usage amounts, as specified in the lineItem/NormalizedUsageAmount column. Each bin or segment of the histogram corresponds to a range of normalized usage values.
Y-axis (Frequency): Indicates the number of times (or the frequency) a particular range of normalized usage values appears in the data. The height of the bars in the histogram represents this frequency.
The histogram provides a visual representation of how often different levels of normalized usage are observed. Peaks (or areas where the bars are taller) indicate commonly occurring usage amounts, while valleys (or areas with shorter or no bars) point to less frequent usage levels. By understanding this distribution, organizations can identify common usage patterns, outliers, or anomalies in their AWS consumption.