Operations | Monitoring | ITSM | DevOps | Cloud

Put simply, managing incidents—big or small—is good for business. Not only is it a regulatory requirement, but also a factor in your profits. Your customers expect smooth operations, good customer service and protection. A dedicated incident management tool can help protect all of these. While many may think of incidents as an IT or DevOps issue, it’s hard to over emphasize that they can happen in any department.

Terraform can orchestrate your infrastructure the same way every time, giving you confidence in your consistent platform. Idempotency for the win.

A lot is expected of automation in IT environments in the next few years. By 2024 Gartner predicts IT automation will drive a 20% reduction in unplanned downtime and lower operational costs by 30%. At the same time, the efficiencies generated by IT automation and analytics will allow organizations to refocus 30% of their IT operations management resources from support to “continuous engineering.”

This need for AIOps was simmering conveniently and gradually reaching its threshold when the pandemic suddenly hit the world, pushing organizations into remote work. The sudden, global-scale change raised challenges for IT operations teams to monitor and detect incidents in a distributed environment and maintain cybersecurity and compliance. While the pandemic pushed some organizations into the reality of remote work, others were already on their way to digital transformation.

The onboarding experience sets the tone for a new developer — beyond the interview process, this will be the developer’s first impression of the company and the job. The onboarding process should be thoughtfully designed and should give the developer the tools they need for success and autonomy. Before you start crafting your onboarding process, think back to your first few days at the organization.

As mentioned in our documentation, Cribl Stream is built on a shared-nothing architecture. Each Worker Node and its processes operate separately and independently. This means that the state is not shared across processes or nodes.This means that if we have a large data set we need to access across all worker processes, we have to get creative. There are two main ways of doing this: In this blog, we’ll walk through how to deploy a Stream leader, Stream worker, and Redis containers via Docker.