Arrow Education reçoit la certification QUALIOPI
La certification QUALIOPI permet à nos clients de faire financer les formations de leurs collaborateurs par les organismes financeurs.
CODE: SPL_USFSOC
DURÉE: 14 Hours (2 Jours)
PRIX H.T.: Prix sur demande
This 2-day (virtual days) course is targeted towards SREs, ITOps, and DevOps Engineers who are responsible for implementing and maintaining an observability solution for infrastructure and application monitoring. In this advanced technical course, you will learn to use SignalFlow – the analytics language used in Splunk Observability Cloud. SignalFlow is a programming language used to define Charts, Navigators and Detectors, and for more complicated data manipulation.
Use SignalFlow to develop visualizations and detectors that are more specific and reusable than what is possible using the user interface alone. You will create functions to analyze data and to incorporate elements from the Observability Cloud code library. The content covered in this course is essential to managing Observability Cloud resources as code using the REST API, Terraform or another contentas-code solution.
Learn the concepts and apply the knowledge through demonstrations, discussions and hands-on activities.
Note: Much of the content in this course was previously covered in the retired course "Automation and the REST and SignalFlow APIs"
Module 1 – Writing Your First SignalFlow Program
Module 2 – Working with Data Streams in Splunk Observability Cloud
Module 3 – Stream aggregations, transformations, and calculations
Module 4 – Detecting and Alerting in SignalFlow
Module 5 – Advanced Detecting and Stream Manipulation
Module 6 – The SignalFlow REST API
Splunk classes are designed for specific roles such as Splunk Administrator, Developer, User, Knowledge Manager, or Architect.
Note: If you have not worked extensively with Splunk Observability Cloud you should take another course first before continuing with this one.
Our certification tracks provide comprehensive education for Splunk customer and partner personnel according to their areas of responsibility.
Course Format
Instructor-led lecture with labs, delivered via live virtual classroom.