For many IT organizations, widescale remote working brings new requirements for supporting both end-users and assets. This is stretching resources and capabilities for many IT teams as they adapt to this change without compromising quality or security. Until recently, the office was the traditional hub of connectivity—not just to business systems, but also among employees.
Google Cloud Platform (GCP) is a collection of Google’s computing resources, made available via services to the general public as a public cloud offering. The GCP resources consist of physical hardware infrastructure — computers, hard disk drives, solid-state drives, and networking — contained within Google’s globally distributed data centers, where any of the components are custom designed using patterns similar to those available in the Open Compute Project.
As we connect with customers we increasingly hear the need for teams to be more predictive with their data. A big challenge is uncertainty around how to get started, especially when much of their data is unstructured. At Splunk, our goal is to make data — and machine learning — accessible for a broad range of users. The good news is, with machine learning doing even more work on your behalf, you don’t need to be a data scientist to use these advanced capabilities.
In a world full of threats targeting data as well as stringent compliance mandates, it’s never been more important to create a strong unified cloud security strategy. But as cloud environments become more complex and diverse, it’s also never been more difficult. Even if you’re partnering with a notably secure provider, it’s still important to understand your security responsibility and to be proactive about protecting your data in the cloud.
Is it week 6 or 8 of telework now? I can't keep up, and it's probably not worth counting anymore. By now, all agencies have a majority of their employees working remotely and adjusting to the new normal; and we, at Splunk, are as well. In a way — like our CIO, Steve McMahon, puts it — we did have an early start.
There’s no question that subscription-based businesses are an incredibly popular revenue model in today’s economy. While single transaction revenue models tend to fluctuate due to the seasonality of markets, subscription plans offer much more consistent and predictable revenues. Although the subscription revenue model can certainly be advantageous over one-off transactions, these businesses are also notoriously challenging to keep subscribers active on their plan.
In this article we are going to explain Jaeger integration with the OpenTelemetry collector, describe differences between these two and have a look at Kubernetes deployment via Jaeger Operator. OpenTelemetry collector is a vendor-agnostic service for receiving, processing and exporting telemetry data. In the Jaeger project we have decided to deprecate the Jaeger collector and migrate its functionality to an implementation based on OpenTelemetry collector.
In our recent Tech Talk, Agentless Monitoring and Custom Monitors, OpsRamp’s Curt Thorin explained how agentless and custom monitoring are critical for distributed IT operations teams. The Tech Talk also provides an interactive demo of how agentless and custom monitoring capabilities can not only support remote work strategies but also prioritize digital transformation initiatives.
The recent shift to remote work has been anything but subtle for millions of people and their companies. And like many in IT Ops, our customers have been preoccupied with maintaining an error-free VPN experience. But that’s often easier said than done. Luckily for them, VPN issues that would normally take weeks to resolve are being turned around in minutes with Nexthink’s patented technology.
