Cloud Native Observability: Fighting Rising Costs, Incidents

Oct 11, 2023

Cloud-native observability in multi-cloud environments is increasingly complex, creating challenges of rising incidents and costly tools. The podcast explores the need to prioritize alerts and shift security responsibility to developers. It also dives into the cultural shift towards DevOps and the gap in addressing developer needs with current observability tools. The guest suggests empowering developers to run and maintain their software in production with cloud-native observability tools, providing insights into complex environments. The podcast also covers the impact of multi-cloud and cloud-native architecture, open source updates, and trends in observability.

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Introduction

00:00 • 2min

Cloud-Native Observability Challenges: Rising Costs and Incidents

02:08 • 2min

Challenges and Impact of Multi-Cloud and Cloud-Native Architecture

03:44 • 11min

Open Source Updates and Innovations in Observability Data Visualization

14:32 • 3min

Observability Trends: Cost, Cloud Native, and Open Source Standards

17:56 • 4min

Observability in multi-cloud environments is becoming increasingly complex, as highlighted by Martin Mao, CEO and co-founder of Chronosphere. This challenge has two main components: a rise in customer-facing incidents, which demand significant engineering time for debugging, and the ineffectiveness and high cost of existing tools. These issues are creating a problematic return on investment for the industry.

Mao discussed these observability challenges on The New Stack Makers podcast with host Heather Joslyn, emphasizing the need to help teams prioritize alerts and encouraging a shift left approach for security responsibility among developers. With the adoption of distributed cloud architectures, organizations are not only dealing with a surge in data but also facing a cultural shift towards DevOps, where developers are expected to be more accountable for their software in production.

Historically, operations teams handled software in production, but in the cloud-native world, developers must take on these responsibilities themselves. Many current observability tools were designed for centralized operations teams, which creates a gap in addressing developer needs.

Mao suggests that cloud-native observability tools should empower developers to run and maintain their software in production, providing insights into the complex environments they work in. Moreover, observability tools can assist developers in understanding the intricacies of their software, such as its dependencies and operational aspects.

To streamline the data obtained from observability efforts and manage costs, Chronosphere introduced the "Observability Data Optimization Cycle." This framework starts with establishing centralized governance to set budgets for teams generating data. The goal is to optimize data usage to extract value without incurring unnecessary costs. This approach applies financial operations (FinOps) concepts to the observability space, helping organizations tackle the challenges of cloud-native observability.

Learn more from The New Stack about Observability and Chronosphere:

Observability Overview, News and Trends

4 Key Observability Best Practices

Top Ways to Reduce Your Observability Costs

Top 4 Factors for Cloud Native Observability Tool Selection