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Sponsored Link OpenAI Team

#ChatGPT   #GPT-3.5   #GPT-4   #gpt-3   #OpenAI  

@faun shared a link, 1 week, 4 days ago

The art and science of developing intelligent apps with OpenAI GPT-3, DALL·E 2, CLIP, and Whisper.

Explore the fascinating world of Artificial Intelligence and solve real-world problems!

In this practical guide, you will build intelligent real-world applications using GPT-3, DALL-E, Whisper, CLIP, and more tools from the OpenAI and ML ecosystem.

Rest assured, you don't need to be a data scientist or machine learning engineer to follow this guide!

The art and science of developing intelligent apps with OpenAI GPT-3, DALL·E 2, CLIP, and Whisper.

#observa...   #observa...   #SRE  

@squadcast shared a post, 1 day, 2 hours ago

How important is Observability for SRE?

Observability is what defines a strong SRE team. In this blog, we have covered the importance of observability, and how SREs can leverage it to enhance their business.

How important is Observability for SRE?
Story Lightrun Team

#observa...   #logging   #trouble...   #user-sp...  

@ek121268 shared a post, 3 weeks, 6 days ago
Global Head of Product Marketing,

Troubleshooting User-Specific Issues: A Practical Guide.

How to debug and solve user-specific issues using Lightrun in your IDE in real-time and without redeploying.

Troubleshooting with Lightrun

#Inciden...   #observa...   #DevOps   #SRE  

@squadcast shared a post, 2 months ago

Introducing our open source SLO Tracker - A simple tool to track SLOs and Error Budget

Check out our open-source SLO tracker and set up your SLO's so that you can accurately track your error budgets. Automate your SRE, with Squadcast's SLO tool!

squadcast .webp

#slo   #OnCall...   #monitor...   #observa...   #SRE  

@squadcast shared a post, 1 year, 3 months ago

What can SREs do to make holiday season’s peak traffic less chaotic?

Holiday season's peak traffic is the most challenging period for SREs and on-call engineers. In this blog, we have highlighted the things that SREs can do to make the holiday season less chaotic.


#monitor...   #observa...   #DevOps  

@oshoval shared a post, 1 year, 4 months ago

SRE? Understand vendor lock-in for your managed monitoring service.

Vendor lock-in refers to a situation where the cost of switching to a different vendor is so high that the customer is essentially stuck with the original vendor


#ITOps   #MLOps   #observa...   #AIOps   #DevOps  

@gurubaran shared a post, 1 year, 5 months ago
Software Enthusiast, CloudFabrix

What is Observability and why you may need it

What is meant by Observability and how has it evolved into something which has transformed the entire IT ecosystem. We will break down all the information in this blog. Before Agile methodology was born, developers also used something called Test-Driven Development

What is Observability and why you may need it
Story Trending

#visuali...   #observa...   #logging   #DevOps  

@eon01 shared a post, 1 year, 6 months ago
Founder, FAUN

Monitoring vs Observability, What’s the Difference?

Monitoring and observability are two closely related concepts that help IT professionals understand and trouble their systems. This article explains the important component of the two concepts, focusing on observability to differentiate between the two.

Monitoring vs Observability
Story The Chief I/O Team

#monitor...   #observa...   #severle...  

@eon01 shared a post, 1 year, 10 months ago
Founder, FAUN

The Pitfalls of Serverless Computing

Serverless is one of the significant trends of the moment in software development and deployment. A promising technology, Serverless Computing is developing very quickly in companies. In this concept, the cloud provider is fully responsible for launching and executing the code of your applications. A Serverless platform ensures that the resources necessary for its optimal operation are available.



@eon01 shared an episode, 1 year, 4 months ago
Founder, FAUN

The Four Golden Signals, SlO, SLI, and Kubernetes

It's 2018 in Kubecon North America, a loud echo in the microphone, and then Ben Sigelman is on the stage.

There is conventional wisdom that observing microservice is hard. Google and Facebook solved this problem, right? They solved it in a way that allowed Observability to scale to multiple orders of magnitude to suit their use cases.

The prevailing assumption that we needed to sacrifice features in order to scale is wrong. In other words, the notion that people need to solve scalability problems as a tradeoff for having a powerful set of features is incorrect.

People assume that you need these three pillars of Observability: metrics, logging, and tracing, and all of a sudden, everything is solved. However, more often than not, this is not the case.

Today we are going to discuss Observability and why this is a critical day-2 operation in Kubernetes. Next, we will discuss the problems with Observability and leverage its three pillars to dive deep into some concepts like service level objectives, service level indicators, and finally, service level agreements.