Cloud Native Observability: Fighting Rising Costs, Incidents

Cloud Native Observability: Fighting Rising Costs, Incidents

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

Tämä jakso on lisätty Podme-palveluun avoimen RSS-syötteen kautta eikä se ole Podmen omaa tuotantoa. Siksi jakso saattaa sisältää mainontaa.

Jaksot(300)

Dynatrace's $915M Arize deal bets AI agents are just another app to monitor

Dynatrace's $915M Arize deal bets AI agents are just another app to monitor

Dynatrace completed its $915 million acquisition of Arize on Oct. 1, combining Dynatrace’s application and infrastructure monitoring with Arize’s AI agent tracing and evaluation capabilities. The deal...

5 Loka 20min

Bit Cloud’s next chapter starts after the AI builds your app

Bit Cloud’s next chapter starts after the AI builds your app

For many developers, turning an AI-generated prototype into maintainable software requires more than generating code—it requires infrastructure, collaboration, testing and review. In this episode of T...

1 Loka 31min

CloudBees just committed to an AI-first pivot. Here's why it matters for enterprise DevOps teams

CloudBees just committed to an AI-first pivot. Here's why it matters for enterprise DevOps teams

CloudBees CEO Mo Plassnig is leading the CI/CD company through a major transformation as generative AI reshapes software development. Returning to CloudBees eight years after joining through its acqui...

30 Syys 23min

A third option is emerging in the fight over AI and your data

A third option is emerging in the fight over AI and your data

The AI industry has faced a growing enterprise dilemma: companies want access to powerful proprietary AI models without risking sensitive data or intellectual property, while AI labs want to protect t...

23 Syys 30min

Drowning in AI pull requests: Harness's field CTO on code review and a Git repo built for agents

Drowning in AI pull requests: Harness's field CTO on code review and a Git repo built for agents

Harness Field CTO Martin Reynolds joins The New Stack to talk about what happens after coding agents start opening pull requests faster than anyone can review them. He explains how he first saw the bo...

7 Syys 26min

How to find failures without drowning in tracing data

How to find failures without drowning in tracing data

Traces provide a detailed view of a request’s journey through data, microservices and applications, helping SREs pinpoint where failures occur and resolve issues faster. But while tracing can reduce d...

3 Syys 31min

Why CPUs still matter in the age of AI agents

Why CPUs still matter in the age of AI agents

As AI evolves from conversational chatbots to autonomous agents, CPUs are becoming an increasingly important part of the infrastructure equation. In this episode, The New Stack speaks with Bhumik Pate...

11 Elo 26min

Why Doist Says Less AI Can Deliver More

Why Doist Says Less AI Can Deliver More

Doist CTO Gonçalo Silva says AI is reshaping software development, but success depends on restraint rather than rapid feature expansion. Instead of chasing every AI capability, Doist prioritizes “subt...

31 Heinä 35min

Suosittua kategoriassa Politiikka ja uutiset

uutiscast
vallattomat
aikalisa
politiikan-puskaradio
rss-viihde-media
rss-ootsa-kuullut-tasta
rss-vaalirankkurit-podcast
ootsa-kuullut-tasta-2
otetaan-yhdet
tervo-halme
rss-voi-venaja
the-ulkopolitist
rss-kaikki-uusiksi
rss-asiastudio
rss-seksicast
rss-raha-talous-ja-politiikka
rss-girls-finish-f1rst
rss-podme-livebox
rss-hyvaa-huomenta-bryssel
rikosmyytit