Author:
Splunk
Language:
English

12 Immutable Rules for Observability

September 2021
Transformation

Speed defines success in today’s digital economy. With customers expecting flawless digital experiences and competition hovering just a click away, companies turn to cloud-native technologies like microservices, containers and Kubernetes to accelerate innovation, build applications faster and improve performance. However, moving to cloud native technologies and distributed architectures introduces new challenges around speed, scale and complexity of data — challenges that traditional monitoring solutions simply weren’t designed to handle.

This is where observability comes in.

Organizations must deliver high quality code and differentiated user experiences — fast. Observability lets DevOps and SRE teams understand and explain unexpected behavior, so they can effectively and proactively manage the performance of distributed microservices running on ephemeral infrastructure.

The right observability strategy and solution translates into more reliability, better customer experience and higher team productivity. Here, we provide 12 immutable rules for observability for ongoing success no matter the complexity of your environment.

The more observable a system is, the quicker we can understand why it’s acting up and fix it — which is critical when meeting service-level indicators (SLIs) and objectives (SLOs) and, ultimately, accelerating business results.

Contents:

  1. Introduction
  2. Observability Definition
  3. An observability solution uses all your data to avoid blind spots
  4. Operates at speed and resolution of your new software-defined (or cloud) infrastructure
  5. Leverages open, flexible instrumentation and makes it easy for developers to use
  6. Enables a seamless workflow across monitoring, troubleshooting and resolution with correlation, and data links between metrics, traces and logs
  7. Makes it easy to use, visualise and explore data out of the box
  8. Leverages in-stream AI for faster and more accurate alerting, directed troubleshooting and rapid insights
  9. Gives fast feedback about (code) changes, even in production
  10. Automates and enables you to do as much “as code”
  11. Is a core part of business performance measurement
  12. Provides observability as a service
  13. Seamlessly embeds collaboration, knowledge management and incident response
  14. Scales to support future growth and elasticity

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12 Immutable Rules for Observability

September 2021
Transformation

Speed defines success in today’s digital economy. With customers expecting flawless digital experiences and competition hovering just a click away, companies turn to cloud-native technologies like microservices, containers and Kubernetes to accelerate innovation, build applications faster and improve performance. However, moving to cloud native technologies and distributed architectures introduces new challenges around speed, scale and complexity of data — challenges that traditional monitoring solutions simply weren’t designed to handle.

This is where observability comes in.

Organizations must deliver high quality code and differentiated user experiences — fast. Observability lets DevOps and SRE teams understand and explain unexpected behavior, so they can effectively and proactively manage the performance of distributed microservices running on ephemeral infrastructure.

The right observability strategy and solution translates into more reliability, better customer experience and higher team productivity. Here, we provide 12 immutable rules for observability for ongoing success no matter the complexity of your environment.

The more observable a system is, the quicker we can understand why it’s acting up and fix it — which is critical when meeting service-level indicators (SLIs) and objectives (SLOs) and, ultimately, accelerating business results.

Contents:

  1. Introduction
  2. Observability Definition
  3. An observability solution uses all your data to avoid blind spots
  4. Operates at speed and resolution of your new software-defined (or cloud) infrastructure
  5. Leverages open, flexible instrumentation and makes it easy for developers to use
  6. Enables a seamless workflow across monitoring, troubleshooting and resolution with correlation, and data links between metrics, traces and logs
  7. Makes it easy to use, visualise and explore data out of the box
  8. Leverages in-stream AI for faster and more accurate alerting, directed troubleshooting and rapid insights
  9. Gives fast feedback about (code) changes, even in production
  10. Automates and enables you to do as much “as code”
  11. Is a core part of business performance measurement
  12. Provides observability as a service
  13. Seamlessly embeds collaboration, knowledge management and incident response
  14. Scales to support future growth and elasticity