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

5 Best Wi-Fi Heat Mapping Tools + Guide

Wi-Fi has become an essential component of our daily life, allowing for seamless connectivity between several devices. However, maintaining the best possible Wi-Fi performance and coverage may be difficult, particularly in complicated settings like huge stadiums, universities, and workplaces. Wi-Fi heat mapping is useful in this situation.

The Hater's Guide to Dealing with Generative AI

Generative AI is having a bit of a moment—well, maybe more than just a bit. It’s an exciting time to be alive for a lot of people. But what if you see stories detailing a six month old AI firm with no revenue seeking a $2 billion valuation and feel something other than excitement in the pit of your stomach? Phillip Carter has an answer for you in his recent talk at Monitorama 2024. As he puts it, “you can keep being a hater, but you can also be super useful, too!”

Building an AI Assistant in Splunk Observability Cloud

Splunk Observability Cloud is a full-stack observability solution, combining purpose-built systems for application, infrastructure and end-user monitoring, pulled together by a common data model, in a unified interface. This provides essential end-to-end visibility across complex tech stacks and various data types, such as metrics, events, logs, and traces (MELT), as well as end-user sessions, database queries, stack traces and more.

Unlocking Smiles: HappyCo's Observability Success

With a diverse range of applications, HappyCo sought to advance their system investigations with a modern observability solution while embarking on an application refactor project. Since its start in 2011, HappyCo has experienced rapid growth through both organic expansion and strategic acquisitions. As a result, the company has a diverse range of applications for customers to smile about.

Identify anomalies, outlier detection, forecasting: How Grafana Cloud uses AI/ML to make observability easier

At Grafana Labs, our No. 1 approach when building AI/ML tools is to enable humans (a.k.a. all of us!) to understand complex systems. In other words, we want to make observability still human, but less complicated. (Our second use case? Making social media more fun.) We believe that AI/ML tools in observability should work towards minimizing toil and the need for everyone in your organization to have the same deep domain knowledge about your increasingly complex stack.

Database Observability and Storage Insights

Storage monitoring involves discovering the estate, devices, and network interconnections. Key telemetry requirements include their states, performance metrics, and logs. As the complexity of the environment increases and storage reliability improves, the focus shifts. Understanding the layers above, such as file systems and databases, and their demand for storage services becomes crucial. This article delves into the detailed knowledge required to achieve effective observability.

Leveraging observability to improve digital resilience

With increasing competition and a digitizing landscape, small and medium enterprises (SMEs) in Australia are being forced to level up their game using AI and modernization. This means eventually relying on cloud and AI integration to ensure agility and responsiveness. The diversity of applications and the complexity of tech architecture pose challenges like increasing costs, security risks, and scalability challenges.

What Developers Should Know about Observability

Peter is a serial entrepreneur and co-founder of Percona, FerretDB, and other tech companies. As a leading expert in open-source strategy and database optimization, Peter has applied his technical knowledge and entrepreneurial drive to contribute as a board member and advisor to several open-source startups. His insights into performance optimization and system reliability play a crucial role in shaping Coroot’s functionality.

Optimizing observability costs with a DIY framework

Observability costs are exploding as businesses strive to deliver maximum customer satisfaction with high performance and 24/7 availability. Global annual spending on observability in 2024 is well over 2.4 billion USD and is expected to reach 4.1 billion USD by 2028. On an individual company basis, this is reflected by observability costs ranging from 10-30% of overall infrastructure spend. These costs will undoubtedly rise with digital environments expanding and becoming ever more complex.