Prometheus - Intro, CNCF, TSDB,PromQL,GrafanaSridhar Kumar N
https://www.youtube.com/playlist?list=PLAiEy9H6ItrKC5PbH7KiELiSEIKv3tuov
-What is Prometheus?
-Difference Between Nagios vs Prometheus
-Architecture
-Alertmanager
-Time series DB
-PromQL (Prometheus Query Language)
-Live Demo
-Grafana
talked by CI/CD Conference 2021 by CloudNative Days https://event.cloudnativedays.jp/cicd2021
re-upload: https://speakerdeck.com/whywaita/cyberagent-oss-cicd-myshoes-cicd2021
Prometheus - Intro, CNCF, TSDB,PromQL,GrafanaSridhar Kumar N
https://www.youtube.com/playlist?list=PLAiEy9H6ItrKC5PbH7KiELiSEIKv3tuov
-What is Prometheus?
-Difference Between Nagios vs Prometheus
-Architecture
-Alertmanager
-Time series DB
-PromQL (Prometheus Query Language)
-Live Demo
-Grafana
talked by CI/CD Conference 2021 by CloudNative Days https://event.cloudnativedays.jp/cicd2021
re-upload: https://speakerdeck.com/whywaita/cyberagent-oss-cicd-myshoes-cicd2021
OSMC 2022 | Ignite: Observability with Grafana & Prometheus for Kafka on Kube...NETWAYS
Self-managing a highly scalable distributed system with Apache Kafka® at its core is not an easy feat. That’s why operators prefer tooling such as Confluent Control Center for administering and monitoring their deployments. However, sometimes, you might also like to import monitoring data into a third-party metrics aggregation platform for service correlations, consolidated dashboards, root cause analysis, or more fine-grained alerts. If you’ve ever asked a question along these lines: Can I export JMX data from Confluent clusters to my monitoring system with minimal configuration? What if I could correlate this service’s data spike with metrics from Confluent clusters in a single UI pane? Can I configure some Grafana dashboards for Confluent clusters?
This talk will enable you on achieving the below:
Monitoring Your Event Streams: Integrating Confluent with Prometheus and Grafana (this article)
Monitoring Your Event Streams: Tutorial for Observability Into Apache Kafka Clients
The monolith to cloud-native, microservices evolution has driven a shift from monitoring to observability. OpenTelemetry, a merger of the OpenTracing and OpenCensus projects, is enabling Observability 2.0. This talk gives an overview of the OpenTelemetry project and then outlines some production-proven architectures for improving the observability of your applications and systems.
MeetUp Monitoring with Prometheus and Grafana (September 2018)Lucas Jellema
This presentation introduces the concept of monitoring - focusing on why and how and finally on the tools to use. It introduces Prometheus (metrics gathering, processing, alerting), application instrumentation and Prometheus exporters and finally it introduces Grafana as a common companion for dashboarding, alerting and notifications. This presentations also introduces the handson workshop - for which materials are available from https://github.com/lucasjellema/monitoring-workshop-prometheus-grafana
Here is the PPT of our recently happened workshop. You can also watch on our youtube channel. here is the link -https://www.youtube.com/channel/UCeLma6SpNYH7jjYKSBNSexw
OSMC 2022 | The Power of Metrics, Logs & Traces with Open Source by Emil-Andr...NETWAYS
The talk will show how organisations can drastically reduce their MTTR (Mean Time To Repair) by using, integrating & correlating the open source tools Mimir, Loki & Tempo. We will then take the next step into open source reliability testing to even avoid problems in the first place. And yes, we will use Grafana 🙂
Cloudera Data Science WorkbenchとPySparkで 好きなPythonライブラリを 分散で使う #cadedaCloudera Japan
Data Engineering and Data Analysis Workshop #1 での有賀 (@chezou)の発表です。
https://cyberagent.connpass.com/event/58808/
Cloudera Data Science WorkbenchとPySparkを使い、Pythonで好きなライブラリを分散実行する方法についてです。日本語の形態素解析ライブラリMeCabをPySparkから実行します。
OSMC 2023 | What’s new with Grafana Labs’s Open Source Observability stack by...NETWAYS
Open source is at the heart of what we do at Grafana Labs and there is so much happening! The intent of this talk to update everyone on the latest development when it comes to Grafana, Pyroscope, Faro, Loki, Mimir, Tempo and more. Everyone has had at least heard about Grafana but maybe some of the other projects mentioned above are new to you? Welcome to this talk 😉 Beside the update what is new we will also quickly introduce them during this talk.
The monolith to cloud-native, microservices evolution has driven a shift from monitoring to observability. OpenTelemetry, a merger of the OpenTracing and OpenCensus projects, is enabling Observability 2.0. This talk covers the fundamental concepts of observability and then demonstrates how to instrument your applications using the OpenTelemetry libraries.
OSMC 2022 | OpenTelemetry 101 by Dotan Horovit s.pdfNETWAYS
Everyone wants observability into their system, but find themselves with too many vendors and tools, each with its own API, SDK, agent, and collectors. In this talk I will present OpenTelemetry, an ambitious open source project with the promise of a unified framework for collecting observability data. With OpenTelemetry you could instrument your application in a vendor-agnostic way, and then analyse the telemetry data in your backend tool of choice, whether Prometheus, Jaeger, Zipkin, or others. I will cover the current state of the various projects of OpenTelemetry (across programming languages, exporters, receivers, protocols), some of which not even GA yet, and provide useful guidance on how to get started with it.
Prometheus: Monitoring by "Pravin Magdum" from "Crevise". The presentation was done at #doppa17 DevOps++ Global Summit 2017. All the copyrights are reserved with the author
In this session, we will start with the importance of monitoring of services and infrastructure. We will discuss about Prometheus an opensource monitoring tool. We will discuss the architecture of Prometheus. We will also discuss some visualization tools which can be used over Prometheus. Then we will have a quick demo for Prometheus and Grafana.
OSMC 2022 | Ignite: Observability with Grafana & Prometheus for Kafka on Kube...NETWAYS
Self-managing a highly scalable distributed system with Apache Kafka® at its core is not an easy feat. That’s why operators prefer tooling such as Confluent Control Center for administering and monitoring their deployments. However, sometimes, you might also like to import monitoring data into a third-party metrics aggregation platform for service correlations, consolidated dashboards, root cause analysis, or more fine-grained alerts. If you’ve ever asked a question along these lines: Can I export JMX data from Confluent clusters to my monitoring system with minimal configuration? What if I could correlate this service’s data spike with metrics from Confluent clusters in a single UI pane? Can I configure some Grafana dashboards for Confluent clusters?
This talk will enable you on achieving the below:
Monitoring Your Event Streams: Integrating Confluent with Prometheus and Grafana (this article)
Monitoring Your Event Streams: Tutorial for Observability Into Apache Kafka Clients
The monolith to cloud-native, microservices evolution has driven a shift from monitoring to observability. OpenTelemetry, a merger of the OpenTracing and OpenCensus projects, is enabling Observability 2.0. This talk gives an overview of the OpenTelemetry project and then outlines some production-proven architectures for improving the observability of your applications and systems.
MeetUp Monitoring with Prometheus and Grafana (September 2018)Lucas Jellema
This presentation introduces the concept of monitoring - focusing on why and how and finally on the tools to use. It introduces Prometheus (metrics gathering, processing, alerting), application instrumentation and Prometheus exporters and finally it introduces Grafana as a common companion for dashboarding, alerting and notifications. This presentations also introduces the handson workshop - for which materials are available from https://github.com/lucasjellema/monitoring-workshop-prometheus-grafana
Here is the PPT of our recently happened workshop. You can also watch on our youtube channel. here is the link -https://www.youtube.com/channel/UCeLma6SpNYH7jjYKSBNSexw
OSMC 2022 | The Power of Metrics, Logs & Traces with Open Source by Emil-Andr...NETWAYS
The talk will show how organisations can drastically reduce their MTTR (Mean Time To Repair) by using, integrating & correlating the open source tools Mimir, Loki & Tempo. We will then take the next step into open source reliability testing to even avoid problems in the first place. And yes, we will use Grafana 🙂
Cloudera Data Science WorkbenchとPySparkで 好きなPythonライブラリを 分散で使う #cadedaCloudera Japan
Data Engineering and Data Analysis Workshop #1 での有賀 (@chezou)の発表です。
https://cyberagent.connpass.com/event/58808/
Cloudera Data Science WorkbenchとPySparkを使い、Pythonで好きなライブラリを分散実行する方法についてです。日本語の形態素解析ライブラリMeCabをPySparkから実行します。
OSMC 2023 | What’s new with Grafana Labs’s Open Source Observability stack by...NETWAYS
Open source is at the heart of what we do at Grafana Labs and there is so much happening! The intent of this talk to update everyone on the latest development when it comes to Grafana, Pyroscope, Faro, Loki, Mimir, Tempo and more. Everyone has had at least heard about Grafana but maybe some of the other projects mentioned above are new to you? Welcome to this talk 😉 Beside the update what is new we will also quickly introduce them during this talk.
The monolith to cloud-native, microservices evolution has driven a shift from monitoring to observability. OpenTelemetry, a merger of the OpenTracing and OpenCensus projects, is enabling Observability 2.0. This talk covers the fundamental concepts of observability and then demonstrates how to instrument your applications using the OpenTelemetry libraries.
OSMC 2022 | OpenTelemetry 101 by Dotan Horovit s.pdfNETWAYS
Everyone wants observability into their system, but find themselves with too many vendors and tools, each with its own API, SDK, agent, and collectors. In this talk I will present OpenTelemetry, an ambitious open source project with the promise of a unified framework for collecting observability data. With OpenTelemetry you could instrument your application in a vendor-agnostic way, and then analyse the telemetry data in your backend tool of choice, whether Prometheus, Jaeger, Zipkin, or others. I will cover the current state of the various projects of OpenTelemetry (across programming languages, exporters, receivers, protocols), some of which not even GA yet, and provide useful guidance on how to get started with it.
Prometheus: Monitoring by "Pravin Magdum" from "Crevise". The presentation was done at #doppa17 DevOps++ Global Summit 2017. All the copyrights are reserved with the author
In this session, we will start with the importance of monitoring of services and infrastructure. We will discuss about Prometheus an opensource monitoring tool. We will discuss the architecture of Prometheus. We will also discuss some visualization tools which can be used over Prometheus. Then we will have a quick demo for Prometheus and Grafana.
【DLゼミ】XFeat: Accelerated Features for Lightweight Image Matchingharmonylab
公開URL：https://arxiv.org/pdf/2404.19174
出典：Guilherme Potje, Felipe Cadar, Andre Araujo, Renato Martins, Erickson R. ascimento: XFeat: Accelerated Features for Lightweight Image Matching, Proceedings of the 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023)
概要：リソース効率に優れた特徴点マッチングのための軽量なアーキテクチャ「XFeat（Accelerated Features）」を提案します。手法は、局所的な特徴点の検出、抽出、マッチングのための畳み込みニューラルネットワークの基本的な設計を再検討します。特に、リソースが限られたデバイス向けに迅速かつ堅牢なアルゴリズムが必要とされるため、解像度を可能な限り高く保ちながら、ネットワークのチャネル数を制限します。さらに、スパース下でのマッチングを選択できる設計となっており、ナビゲーションやARなどのアプリケーションに適しています。XFeatは、高速かつ同等以上の精度を実現し、一般的なラップトップのCPU上でリアルタイムで動作します。
セル生産方式におけるロボットの活用には様々な問題があるが，その一つとして 3 体以上の物体の組み立てが挙げられる．一般に，複数物体を同時に組み立てる際は，対象の部品をそれぞれロボットアームまたは治具でそれぞれ独立に保持することで組み立てを遂行すると考えられる．ただし，この方法ではロボットアームや治具を部品数と同じ数だけ必要とし，部品数が多いほどコスト面や設置スペースの関係で無駄が多くなる．この課題に対して音𣷓らは組み立て対象物に働く接触力等の解析により，治具等で固定されていない対象物が組み立て作業中に運動しにくい状態となる条件を求めた．すなわち，環境中の非把持対象物のロバスト性を考慮して，組み立て作業条件を検討している．本研究ではこの方策に基づいて，複数物体の組み立て作業を単腕マニピュレータで実行することを目的とする．このとき，対象物のロバスト性を考慮することで，仮組状態の複数物体を同時に扱う手法を提案する．作業対象としてパイプジョイントの組み立てを挙げ，簡易な道具を用いることで単腕マニピュレータで複数物体を同時に把持できることを示す．さらに，作業成功率の向上のために RGB-D カメラを用いた物体の位置検出に基づくロボット制御及び動作計画を実装する．
This paper discusses assembly operations using a single manipulator and a parallel gripper to simultaneously
grasp multiple objects and hold the group of temporarily assembled objects. Multiple robots and jigs generally operate
assembly tasks by constraining the target objects mechanically or geometrically to prevent them from moving. It is
necessary to analyze the physical interaction between the objects for such constraints to achieve the tasks with a single
gripper. In this paper, we focus on assembling pipe joints as an example and discuss constraining the motion of the
objects. Our demonstration shows that a simple tool can facilitate holding multiple objects with a single gripper.
