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kshekar23
@kshekar23 shared a link, 1 year, 1 month ago
Freelancer

Sending Custom Metrics from Python to Prometheus

#monitor...   #prometh...   #Python  
Prometheus Python

A short guide for instrumenting your Python app with the Prometheus Python Client library

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prathamesh-sonpatki
@prathamesh-sonpatki shared a link, 1 year, 5 months ago
SRE, Last9.io

Webinar: Embracing Declarative Provisioning and Observability in cloud environments

#DevOps   #SRE   #observa...   #provisi...   #webinar  
Terraform AWS EKS Prometheus

Join us on 20th July at 9 AM PDT for a webinar on Declarative Provisioning and Observability with Pravanjan Choudhury.

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Webinar: Embracing Declarative Provisioning and Observability in cloud environments
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mohammad_zaigam
@mohammad_zaigam shared a post, 1 year, 5 months ago
Technical Solutions Specialist, Logiq.ai

How to Scale Prometheus with Thanos for Long-Term Data

#scalabi...   #scaling   #thanos   #longter...   #prometh...  
Prometheus Thanos

- Prometheus is a powerful open-source system for service monitoring and time series data storage.

- Thanos is a companion tool that adds high availability and long-term storage capabilities to Prometheus.

- Thanos seamlessly integrates with Prometheus and provides object storage for historical data.

- It ensures rapid query response times and offers a global query view for real-time data merging.

- Thanos enables high availability for Prometheus and allows for long-term metrics retention.

- It simplifies the backup process and facilitates cross-cluster scalability.

- Thanos provides cost-effective data access and enhances Prometheus' scalability and reliability.

- Scaling Prometheus with Thanos involves storage configuration, utilizing the Thanos Sidecar, setting up Thanos Query, and aggregating Thanos Query nodes.

- LOGIQ.AI offers a comprehensive platform, LOGIQ Stack, for scaling Prometheus using Thanos.

Scaling Prometheus with Thanos for Long-Term Data.png
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