Scaling Application Instances
Handle app and service scaling by automating the deployment and scaling of applications in Kubernetes clusters.
Accelerate scale
Automate deployments in Kubernetes clusters to accelerate scaling, ensuring quick response and consistent performance during peak times.
Reduce error
Ensure efficient resource allocation by automating app scaling and HITL approvals, reducing errors and minimizing downtime risks.
Speed up resolution
Streamline ticket creation and resolution to enhance operational effectiveness, ensuring accurate tracking and faster response times.
See what you can automate today.
Problem
Scaling applications to efficiently handle increased load is crucial. Operations teams face challenges when dynamically scaling instances, particularly during peak usage, while ensuring Human-in-the-Loop (HITL) checks for specific thresholds. Manually monitoring and approving scaling can be time-consuming and error-prone, risking downtime or degraded performance. Automating the approval process and scaling operations can accelerate response to demand changes, ensure consistent performance, and enhance user experience and operational efficiency.
Solution
PagerDuty Automation handles app and service scaling by automating the deployment and scaling of applications in Kubernetes clusters, ensuring efficient resource allocation. It streamlines HITL approvals by managing approval tasks for specific services or thresholds, adding oversight where necessary. PagerDuty integrates with systems of record to automate ticket creation and resolution related to changes, ensuring accurate tracking and faster response times.
Technical Job Steps
App/Service Scaling:
Scale an app/service deployed to Kubernetes cluster.
Business Steps
HITL Approvals:
Coordinate approval tasks for specific services or based on specific thresholds.
ITSM Management:
Coordinate ticket creation and resolution in systems of record for changes to specific services.
Report Generation:
Generate custom reports on requests/usage.
