These slides from Enterprise Management Associates (EMA) present a wealth of research data from EMA’s recent study of real-world adoption patterns, challenges, trends, and enterprise-priorities related to infrastructure and application observability.

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With over 15 years of enterprise IT
experience, Torsten helps end users and
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software-defined infrastructure
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advanced machine learning. He specializes
in topics that lead the way from hybrid
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EMA

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5. Observability: Challenges, Priorities,
Adoption Patterns, and Solutions
● The Exploding Importance Of
Observability
● Observability And Business Success
● The Observability Cost Trap
● Context Is King
● The Data Pipeline
● Open Source Priorities
● Developer Challenges
● Operator Challenges
● Security Challenges
● Collaboration Is Key
● Last Words

6. The Exploding Importance Of Observability

7. Investor’s
Perspective
Observability data, platforms,
and tools are top of mind.
Strong interest in open
source, especially
Kubernetes.
AI is a rising topic in
observability.

8. Web Searches for
Observability
1. The Basics
2. Significance for Software
3. Importance for DevOps
4. Use Cases
5. Tools and Platforms
6. Comparative Analysis

9. Observability Is
Business
Critical
The long missing link between
business success and
technology investments.

10. Business KPIs,
Technology KPIs,
and Telemetry Data
The Observability
Platform Monitors and
Optimizes.

11. Why
Observability Is
Difficult
Many independent
sources of telemetry
data.

12. Context Is King

13. Processing Observability Data

15. For Example: We Have 3x More Tools

16. The Role of
Open Source
Kubernetes-related
monitoring topics are at the
top.
Data visualization through
Grafana and distributed
tracing come next.

17. OpenTelemetry Growth and Priorities

18. Developer
Challenges
Logging is at the top
of the list of priorities.
Framework specific
challenges.
Cloud native
observability.

19. Spotlight On
Cloud Native
Observability
Prometheus for collecting
Kubernetes metrics is at
the top of the list.
Fluent Bit data pipeline is
at #4.

20. Security
Challenges
Integration between
observability software
is challenging.
Code instrumentation,
lack of skills,
complexity, and data
silos go hand in hand.

21. Operator
Challenges
Log Management &
Monitoring are at the
top of the list.
Then come
infrastructure-specific
topics.

22. Observability Is A Team Sport