Duration: 2 days / 16 hours

Delivery Method: Classroom-based, Virtual Instructor Led Training

COURSE DESCRIPTION

This course addresses the growing complexity of microservices and cloud-native architectures, which make systems harder to observe and troubleshoot. The course introduces practices for building resilience and architecting end-to-end observability for cloud-native applications. It is tailored for those focused on understanding basic and advanced concepts, implementations, use cases, and benefits.

COURSE OVERVIEW

Microservices and cloud-native architectures have been adopted by many organizations to increase speed and agility, but as complexity grows, systems become increasingly challenging to observe. When issues occur, these issues are often difficult to triage and identify the root causes. This course introduces a range of practices to advance resilience and explains how to architect end-to-end observability for cloud-native applications. The course covers the advantages of building full-stack metrics, events, logs, and distributed tracing, augmented by AI, along with the impact of DevSecOps on observability and how AIOps enhances observability capabilities. This course also explains how network and security observability play a key role in building reliability and covers key aspects of security operations and automated responses.

The course aims to equip participants with the practices, methods, and tools needed to engage people across the organization in observability, using real-life scenarios and case studies. Upon completion of the course, participants will have tangible takeaways to effectively leverage solutions such as MELT models that fit their organizational context, build distributed tracing and resiliency by design, and enhance these capabilities with AI.

The course was developed by leveraging key experts in the fields of telemetry, up-to-date sources of knowledge, and by engaging with thought leaders in the observability space, as well as working with organizations that have advanced modern observability to extract real-life best practices.

This course prepares learners to successfully complete the Observability Foundation certification exam.

COURSE OBJECTIVES

The learning objectives for the Observability FoundationSM course include a practical understanding of:

·      How to successfully implement a flourishing observability culture in your organization.

·      Τhe underlying principles of observability and an understanding why monitoring on its own will not provide the required results in microservices based containerized environments

·      The underlying principles of observability and why monitoring alone does not provide the required results in microservices-based, containerized environments.

·      The three pillars of observability.

·      How adopting OpenTelemetry standards helps achieve innovation and enables seamless distributed tracing.

·      The observability maturity model and methods for measuring practical observability.

·      How implementing full-stack observability and distributed tracing, together with AI, enables a modern DevSecOps culture and solutions.

·      How to leverage observability using AI to move from reactive to proactive and predictive incident management, and how to use DataOps to build a clean data lineage of observable data.

·      How to implement network- and container-level observability, and why security is a first-class citizen in building an observability culture.

·      The concept of time-based topology and its value in observability for distributed environments.

·      The data paradox, and how to address data issues using a systematic approach (DataOps) to build a clean observability pipeline.

·      How to incorporate DevSecOps wisdom into observability practices.

·      Observability practices for DevSecOps and SRE.