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The latest News and Information on Observabilty for complex systems and related technologies.

The Crossroad of Security & Observability in Kubernetes: A Fireside Chat

Security as an afterthought is no longer an option and must be deeply embedded in the design and implementation of the products that will be running in the cloud. It is increasingly more critical for many security teams to be almost, if not equally, knowledgeable of the emerging and rapidly evolving technology. Join Manish Sampat from Tigera, as explores the topic in detail with Stan Lee from Paypal.

Service Mesh, Observability and Beyond - Sheetal Joshi, AWS

Congratulations! You’re now cloud-native with microservices. No more legacy monoliths. However, troubleshooting takes time, debugging is difficult, and security is scary. How can you scale your organization without losing an understanding of your environment? Services mesh is here to help! It gives you the observability of connected services and is easier to adopt than you might think. Come and learn service mesh concepts, best practices, and key challenges.

Kubernetes Observability & Troubleshooting: Best Practices - Raj Singh, Box

Early adoption of Kubernetes came with its set of challenges for Box, that led to innovative solutions & learnings. In this session, the speaker will take you through some of those solutions around Kubernetes Observability & best practices which will make your Kubernetes journey easier.

A New Approach to Metrics

Today at o11ycon+hnycon—right now, actually, if you’re reading this blog when it was posted—we’re announcing several new Honeycomb features during the keynote. Our industry and community have come a long way since we burst onto the scene, and I’m delighted to give you another version of Honeycomb that continues to demonstrate what’s possible with observability. And it includes metrics.

Multi-Project Cloud Monitoring made easier

Customers need scale and flexibility from their cloud and this extends into supporting services such as monitoring and logging. Google Cloud’s Monitoring and Logging observability services are built on the same platforms used by all of Google that handle over 16 million metrics queries per second, 2.5 exabytes of logs per month, and over 14 quadrillion metric points on disk, as of 2020.

Unified Observability: A Business-Centric View

Here at LogicMonitor, we’re on a mission to build the most comprehensive, extensible, and intelligent monitoring and observability platform in the world to help businesses run seamlessly. We’ve spent more than a decade building a best-in-class monitoring platform. Over the past two years, however, we have further evolved our platform to deliver invaluable end-to-end observability across applications, networks, and infrastructure for companies of all sizes and in a variety of industries.

Total Economic Impact study: Elastic delivers 10X performance with up to 75% cost savings

Ten times faster at a fraction of the cost. If you want a headline as to why you should consider adopting Elastic for security and observability, that is it. We often work with our customers to help them establish the business value of Elastic within their organizations. We commissioned Forrester to conduct a Total Economic Impact (TEI) study of our security and observability solutions so our customers have an unbiased view that they can share with their internal stakeholders.

Chapter 7: In Which Sarah Experiments with Observable Low-Code

This is the seventh chapter in a series of blog posts exploring the role that intelligent observability plays in the day-to-day life of smart teams. In this chapter, our DevOps Engineer, Sarah, experiments with low code and Moogsoft in her team’s DevOps toolchain to rush a new feature out the door to keep up with a competitor.

Anomaly Detection on Observability Data using Machine Learning

Machine learning helps detect undesired behaviors in your observability data. This makes it easier to spot performance degradation in your applications, services, or instances. In this video, you'll learn how to automate anomaly detections using machine learning on your observability data.