Operations | Monitoring | ITSM | DevOps | Cloud

ITOps is at a crossroads: Teams struggle to manage a high volume of alerts and coordinate between different tools and teams. Teams also must balance cloud technologies’ agility and on-premise solutions’ stability. The sheer speed of today’s IT demands both flexibility and visibility in development and harmonized tech stacks.

In today’s digital-first business landscape, collaborative platforms like Microsoft SharePoint are not merely a convenience but a necessity. They facilitate seamless interaction, information sharing, and collective project management across geographically dispersed teams. However, the enhanced connectivity and accessibility come with a set of security challenges.

Escalation policies are essential for making sure that incidents are quickly addressed and resolved. They provide a systematic approach to automate alerts, guaranteeing that no incident goes unnoticed. Let’s get you started, shall we? An escalation policy is a way to automate alerts and assure that incidents are never missed. The first point of contact for an incident is through an alert that is sent according to the escalation policy.

A few days ago a memo from logistics company Flexport leaked to the media announcing significant layoffs. Now, a tech company doing layoffs in 2023 is hardly notable. A 20% RIF here and there is almost expected. What is notable is the reason for the layoffs: Flexport is trying to achieve profitability.

A spicy article hit my inbox the other day. It came with a bold claim — “API testing is better than UI testing”. Absolutes like “A is better than B” rarely hold in the software world. “It depends” is the answer to most tech questions for a reason. Let’s compare API and UI testing and discuss why one isn’t better than the other. The frenemies are “just different”, and always will be. And that’s a good thing.

At Cribl, we have the privilege of helping our customers achieve their strategic data goals by giving them visibility and control over all of their observability data. The reality today is that data is commonly stored across many places. Whether intentional (such as using Cribl Stream to create a security data lake) or unintentional (because of silos and tool sprawl), organizations desire the ability to access and analyze all of this information at any time.