Top runbooks

Make sure you have installed the DagKnows CLI installed

The DagKnows app. This repo contains a minimal set of compose files for running a DagKnows app anywhere.

You will need a server with the following specs: * min 16GB RAM

* min 100GB disk

* min 2 CPUs * Ubuntu (20.04+)

You need to have the following packages on the VM. Most of the Linux distributions have it by default. In not, please install. * git * python (3.10+)

AWS Route53 is a scalable and highly available DNS service that connects user requests to infrastructure running in AWS and outside. One of its features is health checks, which monitor the health of your resources. Over time, as resources are added or removed, or configurations change, some health checks may no longer be associated with any active resources, leading to unnecessary costs and po...

This runbook is designed to identify unattached Elastic IPs within all AWS regions and release them. Elastic IPs that are not associated with any instances can accumulate over time and result in unnecessary costs. By using this runbook, you can efficiently release these unattached Elastic IPs, optimizing your resources and reducing expenses.

This runbook is designed to identify and remove secrets from the AWS Secrets Manager that haven't been accessed or utilized within a defined period (e.g., the past 90 days). Secrets Manager is a tool that helps manage sensitive information like API keys or database credentials. Over time, some secrets may become obsolete or unused, occupying unnecessary space and potentially incurring extra co...

This task involves enumerating and displaying all AWS RDS (Amazon Relational Database Service) instances within an AWS account. This task is essential for management and auditing purposes, providing a clear view of all RDS instances. During this process, the script communicates with AWS services to retrieve information about each RDS instance, including their identifiers, status, and any other...

This runbook involves identifying Amazon RDS instances that consistently exhibit low CPU usage over a specific time frame and then safely removing them. By leveraging Amazon CloudWatch metrics, organizations can pinpoint underutilized RDS instances, set a CPU utilization threshold, and analyze instances that fall below this mark. Before initiating deletion, it's crucial to disable any active '...

This process retrieves a list of all Amazon Redshift clusters within an AWS account. Amazon Redshift is a fully managed data warehouse service in the cloud that allows users to run complex analytic queries against petabytes of structured data. By fetching all Redshift clusters, users can gain insights into the number of active clusters, their configurations, statuses, and other related metadat...

This runbook identifies and removes inactive NAT gateways to optimize AWS costs. By eliminating unused resources, it streamlines infrastructure management and reduces unnecessary charges.

This runbook automates the process of identifying and deleting unused Amazon CloudWatch Log Streams. By scanning specified log groups across designated AWS regions, it efficiently detects log streams that have been inactive for a predetermined period. Once identified, these log streams are safely removed, helping organizations maintain a clutter-free logging environment and potentially reducin...

This runbook is designed to assist in the removal of unattached Amazon EBS Volumes within an AWS region. Once the EBS volume is deleted, the volume's data is permanently removed, and the volume cannot be attached to any instance. To preserve important data before deletion, you have the option to create a snapshot of the volume, allowing for potential volume recreation in the future.

This runbook involves identifying Amazon Redshift clusters that have consistently low CPU utilization over a specified period and then deleting them to optimize resource usage and reduce costs. By monitoring the CPU metrics of Redshift clusters using Amazon CloudWatch, organizations can determine which clusters are underutilized and might be candidates for deletion or resizing. Deleting or res...

This runbook identifies Amazon Elastic Block Storage (EBS) volumes that exhibit low usage, and subsequently removes them. The process involves searching for EBS volumes that have been minimally utilized over a specified threshold period, and then performing the deletion for those volumes. This automation helps optimize storage resources by removing underutilized volumes, freeing up space and p...

This runbook identifies and removes old Amazon Elastic Block Store (EBS) snapshots. By setting a specific age threshold it scans through designated AWS regions, pinpoints snapshots that surpass the age limit, and subsequently deletes them. This operation not only ensures efficient resource utilization but also aids in minimizing storage costs, promoting a cleaner and more cost-effective cloud ...

This runbook streamlines resource management by identifying and removing Elastic Block Store (EBS) volumes linked to stopped Amazon EC2 instances. Through a sequential process, this automation retrieves EBS volumes associated with stopped instances and subsequently detaches and deletes them. This procedure aids in resource optimization and cost efficiency within the AWS environment.

This runbook retrieves the list of resources, such as instances or targets, that are marked as 'unhealthy' or 'OutOfService', and are associated with AWS Elastic Load Balancers (ELB). This helps in identifying potential issues and ensuring the smooth operation and high availability of applications.

This runbook helps in identifying and removing Amazon Elastic Load Balancers (ELBs) that do not have any associated target groups or instances. ELBs play a crucial role in distributing traffic across instances, and if they are no longer serving a purpose due to the absence of targets or instances, it's recommended to remove them to optimize resources and reduce unnecessary costs. This process ...