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Berwout De Vries Robles
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My presentation for the Kubernetes meets Google Cloud meetup on 29-08-2019
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Your Journey to Cloud-Native Begins with DevOps, Microservices, and Containers
Atlassian
GitOps is a paradigm or a set of practices that empowers developers to perform tasks which typically (only) fall under the purview of operations. It’s a way to do Kubernetes cluster management and application delivery by using Git as a single source of truth for declarative infrastructure and applications. Being Git at the center of delivery pipelines, engineers use familiar tools to make pull requests to accelerate and simplify both application deployments and operations tasks to Kubernetes. GitOps software agents (e.g. ArgoCD, Flux and Jenkins X) can alert on any divergence between Git with what’s running in a cluster, and if there’s a difference, Kubernetes reconcilers automatically update or rollback the cluster depending on the case. This talk will include a demo of ArgoCD/Flux/Jenkins X on how to configure and use it to accelerate and simplify application deployments.
stackconf 2021 | GitOps: yea or nay?
stackconf 2021 | GitOps: yea or nay?
NETWAYS
A speaker session hosted by Samrat Priyadarshi as a part of GDSC WoW Punjab 2023 held on 16 April 2023 at Lovely Professional University.
GitOps - Argo CD - GDSC WoW Punjab
GitOps - Argo CD - GDSC WoW Punjab
TusharVilekar1
Slides from the GDG Santa Clara Meetup presenting on ways to get started with GCP ( Google Cloud Platform) and Qwiklabs
Getting started with GCP ( Google Cloud Platform)
Getting started with GCP ( Google Cloud Platform)
bigdata trunk
All the slides from 'Round Three' the Battle of the Clouds which took place in Manchester on Wednesday 10th October
AWS vs Azure vs Google (GCP) - Slides
AWS vs Azure vs Google (GCP) - Slides
TobyWilman
Similar to Observability on kubernetes
(20)
Introduction to Google Cloud Platform
Introduction to Google Cloud Platform
Google Cloud Study Jams Session -1 .pptx
Google Cloud Study Jams Session -1 .pptx
GWAB2014 Italy Microsoft Azure Web Sites
GWAB2014 Italy Microsoft Azure Web Sites
SEC302 Twitter's GCP Architecture for its petabyte scale data storage in gcs...
SEC302 Twitter's GCP Architecture for its petabyte scale data storage in gcs...
A Hitchhiker's Guide to Enterprise Microservices with Go
A Hitchhiker's Guide to Enterprise Microservices with Go
Provision GCP resources using Terraform @ GDG Craiova
Provision GCP resources using Terraform @ GDG Craiova
Session 4 GCCP.pptx
Session 4 GCCP.pptx
WebXR, if X = 5G
WebXR, if X = 5G
Digital Forensics and Incident Response in The Cloud
Digital Forensics and Incident Response in The Cloud
What is the cloud - First steps to understanding cloud computing
What is the cloud - First steps to understanding cloud computing
Introduction to GCP
Introduction to GCP
Essentials of cloud dsc skct
Essentials of cloud dsc skct
GO and GCP: Introduction
GO and GCP: Introduction
Metaverse - The 'Killer App' for 5G, 6G and Beyond
Metaverse - The 'Killer App' for 5G, 6G and Beyond
Welcome and State of Apache CloudStack Community
Welcome and State of Apache CloudStack Community
Your Journey to Cloud-Native Begins with DevOps, Microservices, and Containers
Your Journey to Cloud-Native Begins with DevOps, Microservices, and Containers
stackconf 2021 | GitOps: yea or nay?
stackconf 2021 | GitOps: yea or nay?
GitOps - Argo CD - GDSC WoW Punjab
GitOps - Argo CD - GDSC WoW Punjab
Getting started with GCP ( Google Cloud Platform)
Getting started with GCP ( Google Cloud Platform)
AWS vs Azure vs Google (GCP) - Slides
AWS vs Azure vs Google (GCP) - Slides
Recently uploaded
This presentation covers the following topics: What is logging? The purpose of logging: Debugging The purpose of logging: Security The purpose of logging: Stats & analytics Traditional logging Traditional logging: Advantages Traditional logging: Disadvantages The solution: Large-scale logging Large-scale logging: Core principles Large-scale logging: Solution types Large-scale logging: Cloud vs on-prem Large-scale logging: Operational complexity Large-scale logging: Security Large-scale logging: Costs Large-scale logging: On-prem comparison - Elasticsearch - Grafana Loki - VictoriaLogs On-prem comparison: Setup and operation On-prem comparison: Costs On-prem comparison: Full-text search support On-prem comparison: How to efficiently query 100TB of logs? On-prem comparison: Integration with CLI tools VictoriaLogs for large-scale logging VictoriaLogs demo instance - Ingestion rate: 3600 messages / minute - The number of log messages: 1.1 billion - Uncompressed log messages’ size: 1.5TB - Compressed log messages’ size: 23GB - Compression ratio: 47x - Memory usage: 150MB VictoriaLogs CLI integration demo - Which errors have occurred in all the apps during the last hour? - How many errors have occurred during the last hour? - Which apps generated the most of errors during the last hour? - The number of per-minute errors for the last 10 minutes - Status codes for the last hour - Non-200 status codes for the last week - Top client IPs for the last 4 weeks with 404 and 500 response status codes - Per-month stats for the given IP across all the logs Large-scale logging solution MUST provide excellent CLI integration VictoriaLogs: (temporary) drawbacks VictoriaLogs: Recap - Easy to setup and operate - The lowest RAM usage and disk space usage (up to 30x less than Elasticsearch and Grafana Loki) - Fast full-text search - Excellent integration with traditional command-line tools for log analysis - Accepts logs from popular log shippers (Filebeat, Fluentbit, Logstash, Vector, Promtail, Grafana Agent) - Open source and free to use!
Large-scale Logging Made Easy: Meetup at Deutsche Bank 2024
Large-scale Logging Made Easy: Meetup at Deutsche Bank 2024
VictoriaMetrics
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WSO2Con2024 - WSO2's IAM Vision: Identity-Led Digital Transformation
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WSO2Con2024 - WSO2's IAM Vision: Identity-Led Digital Transformation
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WSO2CON 2024 - Does Open Source Still Matter?
WSO2CON 2024 - Does Open Source Still Matter?
WSO2CON 2024 - Does Open Source Still Matter?
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Observability on kubernetes
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Organizers Rokesh Matt Constantijn Tea Clara
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Microservice observability Or how
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Berwout de Vries
Robles
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What do we
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Logs Structured Unstructered Centralized
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Metrics
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Traces
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Human
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Why do we
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Networking complexity
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Support
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Our demo case
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