Operations | Monitoring | ITSM | DevOps | Cloud

There’s an AI-led developer and operations (DevOps) evolution afoot which is stoking SREs’ increasingly critical efforts to assure and improve the customer experience by automating the toil out of observability. This movement feeds on a supercharged process of turning telemetry into actionable insight by automatically drawing anomalies, changes and events out of the full-stack event and telemetry data, and analyzing it for correlation and causality.

Say you are an awesome developer sitting contentedly at your desk when a Slack message suddenly interrupts your peaceful mental flow: It would appear there is a data issue with the new Activity History service released last month… Or at least a couple people think there is. Now, instead of making progress on new tasks, you now need to drop those and look into what’s happening here. Sigh.

In our industry, we often like to use the analogy of building a house when we describe how we build software. In our house-building analogy, this would be the blueprint of the house or the process that we are going to follow to construct a home or software. The analogy continues to be relevant because of all the interdependencies that are at work in terms of understanding the blueprint and translating it into work.

It goes without saying that 2020 has been a challenging year for businesses. Faced with unexpected and unfamiliar hurdles, organizations have been under immense pressure to maintain or improve performance in all areas of their business. But this has also been a year of innovation. We’ve seen modern organizations embrace new, innovative technologies and tactics that have reshaped the way they manage IT performance.

Elasticsearch is a great platform for any data lake initiative, and ideal for analyzing your monitoring and observability data. But if you’re working with a number of different monitoring and observability tools, especially across multiple cloud environments, you might find it challenging to get all your data into Elasticsearch.

By industrializing software delivery, DevOps has the potential to transform IT in the same way that Henry Ford transformed manufacturing Back in 1913, Henry Ford started a manufacturing revolution. On December 1, the first automotive assembly line heralded the advent of mass production and reduced the time required to build a Model T to only 2 ½ hours. That allowed Ford to slash manufacturing costs as well as the price of his iconic automobile.

TL;DR: This blog contains some immediate guidance on using Splunk Core and Splunk Enterprise Security to protect (and detect activity on) your network from the Sunburst Backdoor malware delivered via SolarWinds Orion software. Splunk’s threat research team will release more guidance in the coming week. Also please note that you may see some malicious network activity but it may not mean your network is compromised. As always review carefully.

There is more to Distributed Tracing with Jaeger than just capturing machine data as with metrics, or tailing log files. To start, you should read this primer. In this article, I will walk you through the initial principles you’ll need before executing anything within your codebase. This is going to focus on Node.js, as slight differences and concerns exist for browser applications.

Serverless is synonymous with Event-Driven Architecture, where Events are a fundamental block of information that is passed around to execute certain application logic. It is very important that events are delivered to the right destination with expected behavior to make sure the whole serverless application works as one. Events are relayed from one place to another through communication services, either in sequence or in parallel.