This presentation was used for Japan Container Days 2018.
I explained the important point to use the k8s on Production environment for Japanese Audience.
This is the presentation which was showed at Microsoft Tier1 event de:code 2019. In this presentation, I showed that there is a lot of option for Java Developer to use the Microsoft Azure.
This is the presentation which was showed at Microsoft Tier1 event de:code 2019. In this presentation, I showed that there is a lot of option for Java Developer to use the Microsoft Azure.
CloudNative Days Tokyo 2021
Track C 2021/11/05 15:20-15:40
中級者 Operation / Monitoring / Logging
CyberAgentではプライベートクラウド上で多数のKubernetesクラスタが稼働しており、ノードの自動修復機能を実装することで運用コストを削減しました。本発表では、似たような自動修復を実現したいオンプレミスKubernetesの運用者にむけて、KubernetesにおけるノードのNotReadyの定義から、OverlayFSで実現した再起動でディスクの変更が揮発する仕組みまで紹介します。
CloudNative Days Tokyo 2021
Track C 2021/11/05 15:20-15:40
中級者 Operation / Monitoring / Logging
CyberAgentではプライベートクラウド上で多数のKubernetesクラスタが稼働しており、ノードの自動修復機能を実装することで運用コストを削減しました。本発表では、似たような自動修復を実現したいオンプレミスKubernetesの運用者にむけて、KubernetesにおけるノードのNotReadyの定義から、OverlayFSで実現した再起動でディスクの変更が揮発する仕組みまで紹介します。
Jakarta EE Microproile Update JJUG 2020 MayYoshio Terada
This is an explanation of Jakarta EE & MicroProfile update for Japanese Java Users Group at Java 25th Anniversary event.
In this session, I explained about the history of J2EE/Java EE/Jakarta EE as well as MicroProfile.
In order to understand the current situation of Jakarta EE and MicroProfile, this explanation may be useful.
Azure RedHat OpenShift - Red Hat Forum 2019Yoshio Terada
This is an explanation at RedHat Forum 2019 in Japan.
The actual demonstration of "Azure RedHat OpenShift" is existing on the following URL.
https://youtu.be/oz7I_BQuttU
This is the explanation of Azure Spring Cloud.
In the explanation, I showed the demo of Azure Spring Cloud.
You can see my demo on following URL.
https://youtu.be/lxvTPMkqeo4
Payara Scale (Hazelcast Enterprise) on AzureYoshio Terada
This is the HoL to create the Paraya Scale on Azure.
In fact, if use got the license from Payara or Hazelcast, you can create multi region cluster or On premiss and public Hybrid cluster. For mission critical environment, the solution is very useful.
Cloud Native Application on DEIS by using 12 factorYoshio Terada
This presentation explain how to create the cloud native scalable application by using 12 factor app of Heroku. In the presentation, I use the DEIS Workflow for kubernetes on Azure Container Services on Azure.
If you are interested in this, I created Hands on Lab as follows. Please try following?
https://github.com/yoshioterada/DEIS-k8s-ACS
Engineer can change the world with DrewYoshio Terada
Based on our experience of technology evangelists and Java Champion, we shared the information of global company's working style and communication with foreign engineers to grow up their motivation. Finally we said that "Engineer can change the world".
Microsoft LUIS meet Java (NAVITIME also used LUIS on production)Yoshio Terada
Language Understanding Intelligent Service (LUIS) offers a fast and effective way of adding language understanding to applications. It is not only C# but also Java can available. In this article, I explained the basic of LUIS and the adoption story by NAVITIME. NAVITIME already use the LUIS on their production environment. And he explained the best practice to use the LUIS.
Preparation to Start the Microservice for Java EE developersYoshio Terada
This presentation explain how to start the Microservices for Java EE developers. From monolithic application to micro services, not only separate the services but also must consider some point in this article.
【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.
26. リソース使用量の制限
$ kubectl top pod
NAME CPU(cores) MEMORY(bytes)
account-service-74b64648b7-2bqgs 3m 842Mi
account-service-74b64648b7-48kf8 3m 826Mi
For CPU entry:
The above 0.5(500m) is guaranteed to use the half CPU in
1 CPU. The expression 0.1 is equivalent to the expression
100m, which can be read as “one hundred millicpu”. CPU is
always requested as an absolute quantity, never as a
relative quantity.
For Memory entry:
You can express memory as a plain integer or as a fixed-
point integer using one of these suffixes: E, P, T, G, M, K.
You can also use the power-of-two equivalents: Ei, Pi, Ti,
Gi, Mi, Ki. For example, the following represent roughly
the same value:
66. Azure Kubernetes Service (AKS)
Fully managed Kubernetes orchestration service
Auto patching, auto scaling, auto updates
Use the full Kubernetes ecosystem