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.
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.
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
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.
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
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
Installation of Grafana on linux ; connectivity with Prometheus database , installation of Prometheus ; Installation of node_exporter ,Tomcat-exporter ; installation and configuration of alert manager .. Detailed step by step installation and working
Explore your prometheus data in grafana - Promcon 2018Grafana Labs
- new Prometheus features in Grafana that were added over the last year
- instant query
- heatmap
- template variable expansion
- new Explore UI with split views and better tab completion for promQL queries
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
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 CoreOSs 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.
Prometheus Design and Philosophy by Julius Volz at Docker Distributed System Summit
Prometheus - https://github.com/Prometheus
Liveblogging: http://canopy.mirage.io/Liveblog/MonitoringDDS2016
This talk is about monitoring with Prometheus. A progression is shown from monitoring concept, to Micrometer, Prometheus and Grafana.
Presented at Alithya by Richard Langlois and Gervais Naoussi, on September 19th, 2018
Cloud Native Night August 2016, Munich: Talk by Julius Volz (@juliusvolz, Co-founder at Prometheus).
Join our Meetup: www.meetup.com/cloud-native-muc
Abstract: This talk is on monitoring dynamic cloud environments with Prometheus.
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.
An Introduction to Prometheus (GrafanaCon 2016)Brian Brazil
Often what you monitor and get alerted on is defined by your tools, rather than what makes the most sense to you and your organisation. Alerts on metrics such as CPU usage which are noisy and rarely spot real problems, while outages go undetected. Monitoring systems can also be challenging to maintain, and overall provide a poor return on investment.
In the past few years several new monitoring systems have appeared with more powerful semantics and which are easier to run, which offer a way to vastly improve how your organisation operates and prepare you for a Cloud Native environment. Prometheus is one such system. This talk will look at the monitoring ideal and how whitebox monitoring with a time series database, multi-dimensional labels and a powerful querying/alerting language can free you from midnight pages.
Monitoring Kubernetes with Prometheus (Kubernetes Ireland, 2016)Brian Brazil
Prometheus is a next-generation monitoring system. Since being publicly announced last year it has seen wide-spread interest and adoption. This talk will look at the concepts behind monitoring with Prometheus, and how to use it with Kubernetes which has direct support for Prometheus.
Installation of Grafana on linux ; connectivity with Prometheus database , installation of Prometheus ; Installation of node_exporter ,Tomcat-exporter ; installation and configuration of alert manager .. Detailed step by step installation and working
Explore your prometheus data in grafana - Promcon 2018Grafana Labs
- new Prometheus features in Grafana that were added over the last year
- instant query
- heatmap
- template variable expansion
- new Explore UI with split views and better tab completion for promQL queries
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
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 CoreOSs 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.
Prometheus Design and Philosophy by Julius Volz at Docker Distributed System Summit
Prometheus - https://github.com/Prometheus
Liveblogging: http://canopy.mirage.io/Liveblog/MonitoringDDS2016
This talk is about monitoring with Prometheus. A progression is shown from monitoring concept, to Micrometer, Prometheus and Grafana.
Presented at Alithya by Richard Langlois and Gervais Naoussi, on September 19th, 2018
Cloud Native Night August 2016, Munich: Talk by Julius Volz (@juliusvolz, Co-founder at Prometheus).
Join our Meetup: www.meetup.com/cloud-native-muc
Abstract: This talk is on monitoring dynamic cloud environments with Prometheus.
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.
An Introduction to Prometheus (GrafanaCon 2016)Brian Brazil
Often what you monitor and get alerted on is defined by your tools, rather than what makes the most sense to you and your organisation. Alerts on metrics such as CPU usage which are noisy and rarely spot real problems, while outages go undetected. Monitoring systems can also be challenging to maintain, and overall provide a poor return on investment.
In the past few years several new monitoring systems have appeared with more powerful semantics and which are easier to run, which offer a way to vastly improve how your organisation operates and prepare you for a Cloud Native environment. Prometheus is one such system. This talk will look at the monitoring ideal and how whitebox monitoring with a time series database, multi-dimensional labels and a powerful querying/alerting language can free you from midnight pages.
Monitoring Kubernetes with Prometheus (Kubernetes Ireland, 2016)Brian Brazil
Prometheus is a next-generation monitoring system. Since being publicly announced last year it has seen wide-spread interest and adoption. This talk will look at the concepts behind monitoring with Prometheus, and how to use it with Kubernetes which has direct support for Prometheus.
How to monitor your Java micro-service with Prometheus? How to design metrics, what is USE and RED? Metrics for a REST service with Prometheus, AlertManager, and Grafana.
Slides and live-coding demo from Warsaw Java User Group Meetup in Warsaw #238.
Monitoring Cloud Native Applications with PrometheusJacopo Nardiello
This talk is a quick intro to Prometheus with an overview on all its components. The presentation points to a generally available demo so that you can see all its components in action.
How to monitor your micro-service with Prometheus? How to design metrics, what is USE and RED? Metrics for a REST service with Prometheus, AlertManager, and Grafana.
Monitoring in Big Data Platform - Albert Lewandowski, GetInDataGetInData
Did you like it? Check out our blog to stay up to date: https://getindata.com/blog
The webinar was organized by GetinData on 2020. During the webinar we explaned the concept of monitoring and observability with focus on data analytics platforms.
Watch more here: https://www.youtube.com/watch?v=qSOlEN5XBQc
Whitepaper - Monitoring ang Observability for Data Platform: https://getindata.com/blog/white-paper-big-data-monitoring-observability-data-platform/
Speaker: Albert Lewandowski
Linkedin: https://www.linkedin.com/in/albert-lewandowski/
___
Getindata is a company founded in 2014 by ex-Spotify data engineers. From day one our focus has been on Big Data projects. We bring together a group of best and most experienced experts in Poland, working with cloud and open-source Big Data technologies to help companies build scalable data architectures and implement advanced analytics over large data sets.
Our experts have vast production experience in implementing Big Data projects for Polish as well as foreign companies including i.a. Spotify, Play, Truecaller, Kcell, Acast, Allegro, ING, Agora, Synerise, StepStone, iZettle and many others from the pharmaceutical, media, finance and FMCG industries.
https://getindata.com
Prometheus: A Next Generation Monitoring System (FOSDEM 2016)Brian Brazil
A look at how Prometheus's instrumentation, data model, query language, manageability and reliability make it a next generation solution.
Video: https://www.youtube.com/watch?v=cwRmXqXKGtk
Contact us: prometheus@robustperception.io
Timely Year Two: Lessons Learned Building a Scalable Metrics Analytic SystemAccumulo Summit
Timely was born to visualize and analyze metric data at a scale untenable for existing solutions. We're returning to talk about what we've achieved over the past year, provide a detailed look into production architecture and discuss additional features added within the past year including alerting and support for external analytics.
– Speakers –
Drew Farris
Chief Technologist, Booz Allen Hamilton
Drew Farris is a software developer and technology consultant at Booz Allen Hamilton where he helps his client solve problems related to large scale analytics, distributed computing and machine learning. He is a member of the Apache Software Foundation and a contributing author to Manning Publications’ “Taming Text” and the Booz Allen Hamilton “Field Guide to Data Science”.
Bill Oley
Senior Lead Engineer, Booz Allen Hamilton
Bill Oley is a senior lead software engineer at Booz Allen Hamilton where he helps his clients analyze and solve problems related to large scale data ingest, storage, retrieval, and analysis. He is particularly interested in improving visibility into large scale systems by making actionable metrics scalable and usable. He has 16 years of experience designing and developing fault-tolerant distributed systems that operate on continuous streams of data. He holds a bachelor's degree in computer science from the United States Naval Academy and a master's degree in computer science from The Johns Hopkins University.
— More Information —
For more information see http://www.accumulosummit.com/
Outdated training deck for Prometheus monitoring tool - shared as a basis for newer content for potential MeetUp and Conference talks. I'm sharing it since there is some intrinsic value remaining.
Jacopo Nardiello - Monitoring Cloud-Native applications with Prometheus - Cod...Codemotion
We are going to talk about Prometheus and how to use to monitor micro-services "Cloud-Native" application s. We are going to dive deep into the Prometheus monitoring model, we will see what are the components be hind this system and how they integrate with each others to provide an efficient and modern monitoring sy stem. We will also have a glance on Prometheus native integrations for cloud-native environments such as Kubernetes.
Container orchestration from theory to practiceDocker, Inc.
"Join Laura Frank and Stephen Day as they explain and examine technical concepts behind container orchestration systems, like distributed consensus, object models, and node topology. These concepts build the foundation of every modern orchestration system, and each technical explanation will be illustrated using SwarmKit and Kubernetes as a real-world example. Gain a deeper understanding of how orchestration systems work in practice and walk away with more insights into your production applications."
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
Google Cloud Platform monitoring with ZabbixMax Kuzkin
This presentation describes how to configure Zabbix (https://zabbix.com/) to configure Google Cloud Platform events through its Monitoring API, using gcpmetrics (https://github.com/odin-public/gcpmetrics/) command line tool.
Devfest 2023 - Service Weaver Introduction - Taipei.pdfKAI CHU CHUNG
In modern software development, decentralized applications are increasingly common. Decentralized applications can split applications into multiple independent services, each service can be developed, deployed and managed independently.
Service Weaver is a decentralized application development framework provided by Google Cloud. It helps you develop, deploy and manage decentralized applications easily.
In this session, Google Cloud developer expert Kai-Chu Chung will introduce the basic concepts and usage of Service Weaver.
Similar to Monitoring using Prometheus and Grafana (20)
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
1. Large Scale Production Engineering
#31 Quarterly Meetup
Monitoring using Prometheus and Grafana
Arvind Kumar GS
SMTS@Oracle Cloud
https://arvindkgs.com
contact@arvindkgs.com
2. 2
Monitoring using Prometheus and Grafana
Agenda
1. Why monitoring?
2. Pillars of Observability
3. What is Prometheus?
4. What is Grafana?
5. How to setup local monitoring stack?
6. Demo Pull Metrics
7. Demo Push Metrics
8. How is Monitoring done in Oracle?
9. Questions
3. 3
Why Monitoring?
Consider the following microservices architecture
Img Source: https://www.capgemini.com/2017/09/microservices-architectures-are-
here-to-stay/
Microservices help building scalable architecture on which you can build enterprise
applications. However, one of the drawbacks of splitting your application into
4. 4
Pillars of Observability
There are 3 pillars of observability:
1. Metrics (Prometheus, Graphite, InfluxDB, Splunk)
2. Logs (Lumberjack, Splunk, Elastic search)
3.Tracing (Opentracing.io - Jaeger)
5. 5
What is Prometheus?
Prometheus is tool that you can use to monitor always running services as well as
one-time jobs (batch jobs)
Built on Go, by Soundcloud
It persists these metrics in time-series db and you can query the metrics.
Time series are defined by its metric names and values. Each metric can have
multiple labels.
Querying a particular combination of labels for a metric, produces a unique time-
series.
Metric is represented as-
<metric name>{<label name>=<label value>, …}
6. 6
What is Prometheus?
Prometheus basically supports two modes:
Pull - Here it is responsibility of Prometheus to pull metrics. An agent will
periodically scrap metrics off configured end-point micro-services.
Push - Here it is responsibility of the end-points to push metrics to an agent of
Prometheus called Pushgateway. This is usually used for one time batch jobs
8. 8
What is Prometheus?
Metric types
Counter - Int value that only increases or can be reset to 0.
Gauge - single numerical value that can arbitrarily go up and down.
Histogram - A histogram samples observations and counts them in configurable
buckets. It also provides a multiple time series during scrape like sum of all
observed values, count of events.
Summary - a summary samples observations (usually things like request
durations and response size) over a sliding time window.
9. 9
What is Prometheus?
Histograms and summaries both sample observations, typically
request durations or response sizes. They track the number of
observations and the sum of the observed values, allowing you to
calculate the average of the observed values
10. 10
What is Prometheus?
Instrumentation is adding sending metrics on some business logic from your microservice. For
example
import io.prometheus.client.Counter;
class YourClass {
static final Counter requests = Counter.build()
.name("requests_total").help("Total requests.").register();
void processRequest() {
requests.inc();
// Your code here.
}
}
https://github.com/prometheus/client_java
11. 11
What is Prometheus?
To expose the metrics used in your code, you would add the Prometheus servlet to your Jetty
server.
Add dependency on ‘io.prometheus.simpleclient’ and add code below to start your metrics
endpoint
Server server = new Server(1234);
ServletContextHandler context = new ServletContextHandler();
context.setContextPath("/");
server.setHandler(context);
context.addServlet(new ServletHolder(new MetricsServlet()), "/metrics");
You can also expose metrics using spring-metrics
12. 12
What is Grafana?
Grafana is a stand-alone tool that let’s you visualize your data. It can
be combined with a host of different sources like – Prometheus, AWS
CloudWatch, ElasticSearch, Mysql, Postgres, InfluxDB and so on.
More on the supported sources .
Grafana lets you create dashboards that monitor different metrics.
You can configure alerts that can integrate with email, slack, pager
duty.
13. 13
How to setup local monitoring stack?
Running from Docker
Setup docker
# Install Docker.
sudo yum install -y docker-engine
sudo systemctl start docker
sudo systemctl enable docker
# Enable non-root user to run docker commands
sudo usermod -aG docker $USER
Pull images - prom/prometheus
prom/pushgateway
prom/prometheus
grafana/grafana
14. 14
How to setup local monitoring stack?
Optionally setup bridge network, if you want isolation of these containers from
other containers
Configure prometheus
Prometheus can be configured via cmd line flags and configuration file.
Prometheus can reload its configuration at runtime.
Prometheus can scrap metrics from targets.
Targets may be statically configured via the static_configs parameter or
dynamically discovered using one of the supported service-discovery
mechanisms.
https://prometheus.io/docs/prometheus/latest/configuration/configuration/
15. 15
How to setup a local monitoring stack?
You can start Grafana on docker by using simply running-
docker run -d -p 3000:3000 grafana/grafana -v grafana-storage:/var/lib/grafana grafana/grafana
You will need to configure your data source (Prometheus) and
your graphs first time. This will then persist on the docker volume.
Disadvantages of this is, to deploy this on production you will
need to clone this docker volume
16. 16
How to setup a local monitoring stack?
However, recommended is using provisioned Grafana data source
and dashboards
Start Grafana
docker run -d -p 3000:3000
--name=grafana
--label name=prometheus
--network=host
-v <absolute-path-to-local-config>:/etc/grafana:ro
-v <absolute-path-to-local-persistence-folder>:/var/lib/grafana:rw
grafana/grafana
17. 17
Demo Pull Metrics
Consider I have three endpoints I need to monitor.
Imagine that the first two endpoints are production targets, while the third one
represents a canary instance.
Configuration is as follows:
- job_name: 'example-random'
# Override the global default and scrape targets from this job every 5 seconds.
scrape_interval: 5s
static_configs:
- targets: ['localhost:8080', 'localhost:8081']
labels:
group: 'production'
- targets: ['localhost:8082']
labels:
group: 'canary'
18. 18
Demo Pull Metrics
Start your service end-points
Clone https://github.com/prometheus/client_golang.git
Install Go compiler
# Start 3 example targets in separate terminals:
./random -listen-address=:8080
./random -listen-address=:8081
./random -listen-address=:8082
19. 19
Demo Pull Metrics
Start Prometheus server
docker run -d -p 9090:9090
--name=prometheus
--label name=prometheus
--network=host
-v <absolute-path-to-local-prometheus.yml>:/etc/prometheus/prometheus.yml:ro
-v <absolute-path-to-local-persistence-folder>:/prometheus:rw prom/prometheus
Verify by navigating to
http://localhost:9090/
20. 20
Demo Pull Metrics
Build Graph on grafana by selecting the Prometheus data source.
Set query:
sum(rate(go_gc_duration_seconds{job="example-random"}[10m]))
by (group)
22. 22
Demo Push Metrics
Configure prometheus to scrap of push gateway
# Scrape PushGateway for client metrics
- job_name: "pushgateway"
# Override the global default and scrape targets from this job every 5 seconds.
scrape_interval: 5s
# By default prometheus adds labels, job (=job_name) and instance (=host:port), to scrapped metrics. This may conflict
# with pushed metrics. Hence it’s recommended to set honor_labels to true, then the scrapped metrics ‘job’ and ‘instance’
# are retained
honor_labels: true
static_configs:
- targets: ["localhost:9091"]
Start push gateway
docker run -d -p 9091:9091
--name=pushgateway
--label name=prometheus
--network=host
prom/pushgateway
23. 23
Demo Push Metrics
Push using curl as
echo "some_metric 3.14" | curl --data-binary @- http://localhost:9091/metrics/job/some_job
cat <<EOF | curl --data-binary @- http://localhost:9091/metrics/job/some_job/instance/some_instance
# TYPE test_counter counter
test_counter{label="val1"} 42
# TYPE test_gauge gauge
# HELP test_gauge Just an example.
test_gauge 2398.283
24. 24
How is Monitoring done in Oracle?
In Oracle cloud we use a variety of tools:
Metrics, we used Prometheus, but now we are moving to T2, that is
an custom built time series monitoring tool similar to Prometheus.
Logging, lumberjack
Alerting, Pagerduty