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

Det här avsnittet är hämtat från ett öppet RSS-flöde och publiceras inte av Podme. Det kan innehålla reklam.

Avsnitt(300)

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 Aug 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 Juli 35min

Why your company should (try to) build its own AI SRE

Why your company should (try to) build its own AI SRE

As AI coding agents accelerate software development, they also create new challenges for site reliability engineers (SREs), who are increasingly responsible for debugging systems that no single human ...

30 Juli 30min

Nvidia

Nvidia

In this episode with The New Stack Agents, Frederic Lardinois, NVIDIA’s Joey Conway says advances in AI over the past year have dramatically improved the capabilities of local models, making them prac...

23 Juli 32min

Meet Brain, the AI that decides when Azure is officially down

Meet Brain, the AI that decides when Azure is officially down

In this episode, Mark Russinovich, CTO of Microsoft Azure revealed Brain, the AI-powered AIOps system that continuously monitors Azure’s health, detects incidents, identifies root causes, and increasi...

14 Juli 19min

What comes after attention? This startup says it already knows.

What comes after attention? This startup says it already knows.

Subquadratic is beginning to back up its ambitious claims with benchmarks and third-party validation for its SubQ 1.1 Small model, which uses its proprietary Sparse Attention (SSA) architecture to dra...

7 Juli 20min

“The harness is where the hard work is”: Harness bets on agents that enterprises can trust in production

“The harness is where the hard work is”: Harness bets on agents that enterprises can trust in production

Harness has introduced Autonomous Worker Agents, a new capability that allows enterprises to replace rigid CI/CD pipeline scripts with AI agents that can deploy applications, run tests, and perform se...

2 Juli 19min

Public cloud vs. on-prem: Summit on where each workload belongs

Public cloud vs. on-prem: Summit on where each workload belongs

More than two decades after AWS helped usher in the public cloud era, many organizations are reassessing whether a cloud-first strategy still delivers the cost and operational benefits it once promise...

25 Juni 36min

Populärt inom Politik & nyheter

p3-krim
rss-krimstad
aftonbladet-daily
svenska-fall
aftonbladet-krim
flashback-forever
tv4-nyheterna-story
motiv
svd-ledarredaktionen
politiken
rss-vad-fan-hande
mannen-utan-spar
de-fyras-gang
rss-sanning-konsekvens
rss-krimreportrarna
spar
fordomspodden
rss-aftonbladet-krim
rss-flodet
olyckan-inifran