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Prometheus and Open-Source Observability with Eric Schabell

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Manage episode 477162390 series 1418208
المحتوى المقدم من Podcast Archives - Software Engineering Daily. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Podcast Archives - Software Engineering Daily أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.

Modern cloud-native systems are highly dynamic and distributed, which makes it difficult to monitor cloud infrastructure using traditional tools designed for static environments. This has motivated the development and widespread adoption of dedicated observability platforms.

Prometheus is an open-source observability tool designed for cloud-native environments. Its strong integration with Kubernetes and pull-based data collection model have driven its popularization in DevOps. However, a common challenge with Prometheus is that it struggles with large data volumes and has limited cost-optimization capabilities. This raises the question of how best to handle Prometheus deployments at large scale.

Eric Schabell works in DevRel at Chronosphere where he’s the Director of Community and Developer. He is also a CNCF Ambassador. Eric joins the show with Kevin Ball to talk about metrics collection, time series data, managing Prometheus at scale, tradeoffs between self-hosted vs. managed observability, and more.

Full Disclosure: This episode is sponsored by Chronosphere.

Kevin Ball or KBall, is the vice president of engineering at Mento and an independent coach for engineers and engineering leaders. He co-founded and served as CTO for two companies, founded the San Diego JavaScript meetup, and organizes the AI inaction discussion group through Latent Space.

Please click here to see the transcript of this episode.

Sponsorship inquiries: [email protected]

The post Prometheus and Open-Source Observability with Eric Schabell appeared first on Software Engineering Daily.

  continue reading

871 حلقات

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iconمشاركة
 
Manage episode 477162390 series 1418208
المحتوى المقدم من Podcast Archives - Software Engineering Daily. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Podcast Archives - Software Engineering Daily أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.

Modern cloud-native systems are highly dynamic and distributed, which makes it difficult to monitor cloud infrastructure using traditional tools designed for static environments. This has motivated the development and widespread adoption of dedicated observability platforms.

Prometheus is an open-source observability tool designed for cloud-native environments. Its strong integration with Kubernetes and pull-based data collection model have driven its popularization in DevOps. However, a common challenge with Prometheus is that it struggles with large data volumes and has limited cost-optimization capabilities. This raises the question of how best to handle Prometheus deployments at large scale.

Eric Schabell works in DevRel at Chronosphere where he’s the Director of Community and Developer. He is also a CNCF Ambassador. Eric joins the show with Kevin Ball to talk about metrics collection, time series data, managing Prometheus at scale, tradeoffs between self-hosted vs. managed observability, and more.

Full Disclosure: This episode is sponsored by Chronosphere.

Kevin Ball or KBall, is the vice president of engineering at Mento and an independent coach for engineers and engineering leaders. He co-founded and served as CTO for two companies, founded the San Diego JavaScript meetup, and organizes the AI inaction discussion group through Latent Space.

Please click here to see the transcript of this episode.

Sponsorship inquiries: [email protected]

The post Prometheus and Open-Source Observability with Eric Schabell appeared first on Software Engineering Daily.

  continue reading

871 حلقات

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