#monitor...   #prometh...   #Python  

@kshekar23 shared a link, 4 weeks, 1 day ago

Freelancer

Sending Custom Metrics from Python to Prometheus

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

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#webinar   #provisi...   #observa...   #SRE   #DevOps  

@prathamesh-sonpatki shared a link, 4 months, 3 weeks ago

SRE, Last9.io

Webinar: Embracing Declarative Provisioning and Observability in cloud environments

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

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#prometh...   #longter...   #thanos   #scaling   #scalabi...  

@mohammad_zaigam shared a post, 5 months ago

Technical Solutions Specialist, Logiq.ai

How to Scale Prometheus with Thanos for Long-Term Data

- 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.

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