Prometheus Multi Tenancy

Kubernetes is an open-source system for managing containerized applications across multiple hosts. It includes key components like Pods, Services, ReplicationControllers, and a master node for managing the cluster. The master maintains state using etcd and schedules containers on worker nodes, while nodes run the kubelet daemon to manage Pods and their containers. Kubernetes handles tasks like replication, rollouts, and health checking through its API objects.

Presentation on managing artifacts with JFrog Artifactory given by Yoav Landman and Fred Simon at the March SvJugFx meeting.

Kubernetes has the concept of resource requests and limits. Pods get scheduled on the nodes based on their requests and optionally limited in how much of the resource they can consume. Understanding and optimizing resource requests/limits is crucial both for reducing resource "slack" and ensuring application performance/low-latency. This talk shows our approach to monitoring and optimizing Kubernetes resources for 80+ clusters to achieve cost-efficiency and reducing impact for latency-critical applications. All shown tools are Open Source and can be applied to most Kubernetes deployments.

Red Hat Insights is a service that analyzes customer environments running Red Hat Enterprise Linux to identify and resolve configuration issues before they impact operations. It uses a lightweight agent that collects minimal data and sends it to Red Hat's rules engine for analysis against their knowledge base of over 30,000 solutions. The service provides a web interface where customers can view prioritized risks and get guidance on remediation. Using Insights with Technical Account Managers allows them to proactively help customers uncover vulnerabilities. Customers can acquire Insights through various Red Hat products or as standalone offerings.

Building on top of his talk at DockerCon 2015, Jana Radhakrishnan, Lead Software Engineer at Docker, does a deep dive into Docker Networking with additional demos and insights on the product roadmap.

* Quick Intro to Bigtop * Trend Micro Big Data Platform * Mission-specific Platform * Big Data Landscape (3p) * Bigtop 1.1 Release (6p)

This document introduces Quarkus, an open source Java framework for building container-native microservices. Quarkus uses GraalVM to compile Java code ahead-of-time, resulting in applications that are up to 10x smaller and 100x faster to start than traditional Java applications. It is optimized for Kubernetes and serverless workloads. Quarkus achieves these benefits through ahead-of-time compilation using GraalVM, which analyzes code statically and removes unused classes and code to generate efficient native executables.

Presented at GDG Devfest Ukraine 2018. Prometheus has become the defacto monitoring system for cloud native applications, with systems like Kubernetes and Etcd natively exposing Prometheus metrics. In this talk Tom will explore all the moving part for a working Prometheus-on-Kubernetes monitoring system, including kube-state-metrics, node-exporter, cAdvisor and Grafana. You will learn about the various methods for getting to a working setup: the manual approach, using CoreOS’s Prometheus Operator, or using Prometheus Ksonnet Mixin. Tom will also share some little tips and tricks for getting the most out of your Prometheus monitoring, including the common pitfalls and what you should be alerting on.

This document discusses LINE's private cloud platform Verda and two new services: Verda Kubernetes as a Service (KaaS) and Verda Event Handler. Verda KaaS provides managed Kubernetes clusters to developers. It is built using Rancher and aims to simplify Kubernetes usage. Verda Event Handler aims to improve automation by defining operations as functions that are triggered by events. It will utilize Knative to provide a functions-as-a-service platform and improve visibility, operability, and maintenance of automation scripts. The status and future plans of these new services are also outlined.

** Kubernetes Certification Training: https://www.edureka.co/kubernetes-certification ** This Edureka tutorial on "Kubernetes Architecture" will give you an introduction to popular DevOps tool - Kubernetes, and will deep dive into Kubernetes Architecture and its working. The following topics are covered in this training session: 1. What is Kubernetes 2. Features of Kubernetes 3. Kubernetes Architecture and Its Components 4. Components of Master Node and Worker Node 5. ETCD 6. Network Setup Requirements ​DevOps Tutorial Blog Series: https://goo.gl/P0zAfF

Like many other messaging systems, Kafka has put limit on the maximum message size. User will fail to produce a message if it is too large. This limit makes a lot of sense and people usually send to Kafka a reference link which refers to a large message stored somewhere else. However, in some scenarios, it would be good to be able to send messages through Kafka without external storage. At LinkedIn, we have a few use cases that can benefit from such feature. This talk covers our solution to send large message through Kafka without additional storage.

This talk shares experiences from deploying and tuning Flink steam processing applications for very large scale. We share lessons learned from users, contributors, and our own experiments about running demanding streaming jobs at scale. The talk will explain what aspects currently render a job as particularly demanding, show how to configure and tune a large scale Flink job, and outline what the Flink community is working on to make the out-of-the-box for experience as smooth as possible. We will, for example, dive into - analyzing and tuning checkpointing - selecting and configuring state backends - understanding common bottlenecks - understanding and configuring network parameters

Kubernetes is an open-source system for managing containerized applications and services. It includes a master node that runs control plane components like the API server, scheduler, and controller manager. Worker nodes run the kubelet service and pods. Pods are the basic building blocks that can contain one or more containers. Labels are used to identify and select pods. Replication controllers ensure a specified number of pod replicas are running. Services define a logical set of pods and associated policy for access. They are exposed via cluster IP addresses or externally using load balancers.

Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery called Pods. ReplicaSets ensure that a specified number of pod replicas are running at any given time. Key components include Pods, Services for enabling network access to applications, and Deployments to update Pods and manage releases.

Grafana Loki is a newly developed logs aggregation system that integrated very nicely with Grafana dashboard to link metrics with logs or just use logs as a separate panel. It is open-source and has a growing community.

This document discusses the basics of CI/CD and the different pieces involved in a CI/CD setup such as wiring projects with build servers, setting up pipelines, and pipeline as code. It explains connecting the dots between a developer's machine, repository, CI server, end users, and connecting these pieces together in the final CI/CD pipeline picture.

This is a talk on how you can monitor your microservices architecture using Prometheus and Grafana. This has easy to execute steps to get a local monitoring stack running on your local machine using docker.

This document discusses strategies for applying test-driven development (TDD) to Apache Cassandra projects. It notes that Cassandra's distributed and resource-intensive nature can make it difficult to integrate with TDD. Initially, the author embedded Cassandra in tests, but this led to slow test runs. Alternative tools like Cassandra Unit and the Cassandra Maven plugin were explored. The author ultimately recommends separating unit and integration tests, using the Cassandra Maven plugin without fixtures, and running tests in parallel to better apply TDD principles to Cassandra.