What is Resource Scheduling?
TotalCloud Resource Scheduler Vs AWS Instance Scheduler
Case 1: EC2 Instances
Case 2: Instances in ASG
Case 3: Instances in ASG (Without Termination)
Case 4: RDS DB Instances
Case 5: Redshift Clusters
Trigger Actions Externally
Advanced Filters in the Resource Node
Add-ons in the Resource Node
Usage Examples of Resource Node
Sample JSON Output
Sample JSON Output II
Types of Filter Node
Security Group Filter
Usage Examples of Filter Node
User Approval Node
Workflow Trigger Node
Getting Started with Nodes
Spot EC2 Instances
Schedule Start AWS EC2 Instances
Schedule Stop AWS EC2 Instances
Delete Unattached AWS EBS Volumes
Periodic Snapshot of EBS Volumes
Terminate Inactive Workspaces
Notify Publicly Open AWS RDS Instances
Notify About Inactive Users
Notify All Public Amazon S3 Buckets
Create a Rule for EC2 Security Group
Revoke Rule From EC2 Security Group
Monitor Amazon EC2 Instances' State
Create Workflows Using Templates
Create Workflows From Scratch
Stopping EC2 Instances Every Evening
Workflow Policy Validation
Use Jira Tickets to Alter EC2 Instances
Use Jira Ticket to Reboot Instance
Use Jira Ticket to Reboot Instance Process
Use Jira Ticket to Upgrade Instance
TotalCloud vs Terraform vs CloudFormation
Listing Workspace Errors In Terraform
Creating Terraform Infrastructure
What sets TotalCloud ahead of stone-age scripting processes
One platform covers all AWS resources and use cases, whether it is scheduling, insights, auto-remediation, or custom actions.
Again, scripts can be created for actions on all AWS resources, but it consumes time and effort, and the lack of speed
Every node is pre-defined, eliminating the need to code. All you need to do is combine the nodes to create a workflow.
Once deployed, the workflow automates the use case, without any manual intervention.
The single biggest hiccup with scripting is the fact that it is manual.
TotalCloud scales as your needs increase.
Creating workflows takes minutes, and the platform allows you to create solutions to any evolving problems.
Additionally, if your needs are repetitive, workflows can simply be cloned or duplicated.
One of the biggest drawbacks of scripts remains the fact that it can not be scaled quickly enough, especially when your needs are complex.
Use Case Complexity
TotalCloud’s range of use cases are limited only by your needs.
From basic scheduling, to complete auto-remediation (For eg, rebalancing an instance fleet across AZs), everything can be solved using simple workflows.
As the complexity of your use case increases, the scripting effort and time shoots up.
It’ll involve innumerable lines of code - consuming tons of DevOps effort.
Flexibility & Customization
Workflows - combine nodes to create any kind of workflow
Triggers - Trigger workflows based on time, alarms (SNS), events (CloudTrail) or anywhere (HTTP)
Data - pull in monitoring data from CloudWatch or any external source that you want to track
Custom filters and code - Use function filters and custom logic whenever required
Notification - link notification system it to Slack or SNS
Although scripting allows every element of customization and flexibility, it’s a tedious process.
If you have a 100 actions and need to customize every one of them, it becomes resource-intensive and complex.
Multiple integrations like Jira, Jenkins, Zendesk, Freshdesk, Telegram, etc - so our platform fits into your tech stack seamlessly
Creating integrations manually requires your DevOps engineers to learn a new set of APIs for the new tool and write repetitive code.
TotalCloud can be used by multiple users, to provide a single, unified view of all workflows
Scripting for each workflow or use case makes it difficult to maintain consistency and standardization for DevOps teams.
Every additional script created adds to the chaos of not being able to track them when needed.
Eliminate the possibility of human error by completely automating cloud management.
Any errors made in code can negatively impact actions taken on your cloud.
DevOps’ Time and Opportunity Cost
With TotalCloud, DevOps’ time is freed to be spent on the customer.
DevOps time concentrated in doing repetitive tasks results in the opportunity cost of lack of attention to your customers and more value-driven innovative activities.