Observability & Datadog

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Is your company built on software? How do you know if your customer's experience is slow and sucks? How do you debug slowness or troubleshoot an incident? Observability! David Mitchell, VP of Engineering at Datadog will talk to use about Observability, why it's important, what it is and how Datadog helps reduce toil in your environment. GDG Cloud Southlake #13

David Mitchell
VP of Engineering
June, 2022
Observability &
Datadog

Observability is a measure of how well internal states of a
system can be inferred from knowledge of its external
outputs

Monitoring
Traditional Deployment
4
Logging
CPU / Memory / Disk
Application Performance
Monitoring
Service B Service C
Distributed Tracing

Increasingly complex software deployments systems
Virtualized Deployment
Traditional Deployment Container Deployment Serverless Architecture
5

Our deﬁnition of a system
continues to change

Security
Compliance
Availability
Performance
Cost
Observability culture is the ability to answer questions about:
Is my business vulnerable or under attack?
Is my business legal?
Do system limitations or code issues prevent accessibility?
Are my users having a good experience?
Is my business efficient?
Proactive
Monitoring

Datadog is a uniﬁed
SaaS platform for
observability,
monitoring and
security.
Built speciﬁcally for
the cloud
environments (public
or private)

All teams lack a single source of
truth and are often blindsided at
critical moments:
- Metrics indicate something is
wrong, but lack details
- Traces can point to the general
area, but aren’t speciﬁc
- Logs have high volume and
varying value, with cost and
visibility tradeoffs
Everything must be manually
queried and correlated
Traditional siloed monitoring tools
aren’t designed to detect problems
at cloud-scale

Datadog — Uniﬁed observability SaaS platform
500+

This document discusses concepts related to observability including Prometheus, ELK stack, OpenTracing, and Victoria Metrics. It provides examples of setting up Prometheus and Grafana to monitor metrics from applications instrumented with exporters. It also demonstrates setting up Filebeat, Logstash and Elasticsearch (ELK stack) to monitor logs and send them to Elasticsearch. Additionally, it shows how to implement OpenTracing in a Java application and visualize traces using Jaeger. Finally, it outlines an exercise to build a microservices ecommerce application incorporating logging, metrics and tracing using the discussed tools.

Observability

Ebru Cucen Çüçen

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Observability

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Martin Gross

Observability refers to the ability to infer the internal state of a system from its external outputs. It is a property of the system, not an action like monitoring. For a system to be observable, it must externalize its state through logs, metrics, and events. Improving observability involves monitoring all components of an application from the front-end to backend services to infrastructure. Common metrics include requests processed, errors encountered, and response times for applications as well as CPU usage, disk I/O, and network traffic for infrastructure. Observability extends monitoring by helping understand why a system is not working in addition to whether it is working.

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With the acceleration of customer and business demands, site reliability engineers and IT Ops analysts now require operational visibility into their entire architecture, something that traditional APM tools, dev logging tools, and SRE tools aren’t equipped to provide. Observability enables you to inspect and understand your IT stack on premises and in the cloud(s); It’s no longer about whether your system works (monitoring), but being able to task why it is not working? (Observability). This presentation will outline key steps to take to move from monitoring to observability.

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For senior executives, successfully managing a major cyber attack relies on your ability to minimise operational downtime, revenue loss and reputational damage. Indeed, the approach you take to recovery is the ultimate test for your Resilience, Business Continuity, Cyber Security and IT teams. Our Cyber Recovery Wargame prepares your organisation to deliver an exceptional crisis response. Event date: 19th June 2024, Tate Modern

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Observability & Datadog

1. David Mitchell VP of Engineering June, 2022 Observability & Datadog

2. What is Observability?

3. Observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs

4. Monitoring Traditional Deployment 4 Logging CPU / Memory / Disk Application Performance Monitoring Service B Service C Distributed Tracing

5. Increasingly complex software deployments systems Virtualized Deployment Traditional Deployment Container Deployment Serverless Architecture 5

6. Our deﬁnition of a system continues to change

7. Complex systems create complex answers

8. Security Compliance Availability Performance Cost Observability culture is the ability to answer questions about: Is my business vulnerable or under attack? Is my business legal? Do system limitations or code issues prevent accessibility? Are my users having a good experience? Is my business efficient? Proactive Monitoring

9. Datadog & Observability

10. Datadog is a uniﬁed SaaS platform for observability, monitoring and security. Built speciﬁcally for the cloud environments (public or private)

11. All teams lack a single source of truth and are often blindsided at critical moments: - Metrics indicate something is wrong, but lack details - Traces can point to the general area, but aren’t speciﬁc - Logs have high volume and varying value, with cost and visibility tradeoffs Everything must be manually queried and correlated Traditional siloed monitoring tools aren’t designed to detect problems at cloud-scale

12. Datadog — Uniﬁed observability SaaS platform 500+

13. Live Demo

14. Q & A

Observability & Datadog

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