Operations | Monitoring | ITSM | DevOps | Cloud

A typical bit of feedback I have had during my time at Splunk is that the Splunk Machine Learning Toolkit (MLTK) looks nice and all, but how are we supposed to get started using it? Choosing the right technique, let alone the right algorithm can be a daunting task for those who are unfamiliar with machine learning (ML). We’ve been thinking long and hard about how we can help offer more prescriptive introductions into using ML at Splunk and I’m pleased to present our set of MLTK deep dives.

MongoDB is a cross-platform NoSQL database that uses JSON-like documents with optional schema to store data. It was designed for high availability, high performance for high-data persistance use cases, and automatic scaling. Of course, all with the right infrastructure in mind. It is usually a good choice for document-oriented use cases when you need quick prototyping or massive scale. With the massive scale comes massive traffic, though.

Maximizing the value of streaming data requires carefully navigating operational tradeoffs when developing and managing cloud native applications. Organizations that are rapidly producing and processing high volumes of data — like Netflix, Salesforce, Shopify and even the United States Postal Service (USPS), are constantly applying and testing new methods to manage the complexity of data streaming in the cloud.

The Datadog platform has evolved to meet the needs of organizations that are investing in cloud-based solutions and modernizations. These organizations need professionals that are highly skilled and understand how to get the most out of the Datadog platform. With our suite of products, features, and tools in mind, we wanted to offer a path for individuals to demonstrate their knowledge of our best-in-class monitoring platform and their understanding of observability best practices.

Aiven for Apache Kafka® Klaw, an open source data governance toolkit, helps enterprises exercise Apache Kafka® Topic and schema governance. Find out what you can accomplish with it!

Aiven enters the next phase of its open source commitment with Apache Kafka® data governance. Read what Oskari Saarenmaa has to say about Kafkawize.

So far in our series on scaling observability for game launches, we’ve discussed ways to 1) quickly analyze large volumes of telemetry data and, 2) ensure high-quality telemetry data for more effective analysis at lower costs. The best practices in these blogs outline best practices for scaling observability during game launch day – which is necessary to ensure high performance across all infrastructure components – to ensure no lag, no glitches, and no bugs.

Welcome to the September edition of What’s New in Sysdig in 2022! I’m Ayu Shah, Principal Sales Engineer based out of San Francisco Bay Area. I joined Sysdig a little over six months ago and it has been an exciting journey to say the least! I have worn many hats in my career, from Software Engineering to Sales and everything in between. I am excited to share some updates to What’s New in Sysdig for this month!