On December 8, 2023, Adobe's extensive customer base was impacted by a series of outages in the Adobe Experience Cloud, starting from 8:00 AM EST and continuing until 1:45 AM EST on December 9. We haven't seen a third-party outage of this magnitude since the DoubleClick outage of 2018.

If you're on a data team, have you ever considered using an incident management tool to respond to pipeline issues? If the answer is no, then you might want to check out this episode. Here, we chat with Jack, Data Analyst at incident.io, to better understand why data teams can—and should—look to incident management tools like incident.io to manage issues. We chat about: Read Jack's blog post about incident management for data teams.

Mean Time to Resolution (MTTR) is a key performance indicator (KPI) that measures the average duration needed to restore normal operation for an application, service or piece of infrastructure component. Your MTTR directly impacts customer satisfaction, so you must have a keen understanding how it influences the reliability and availability of your services and applications to make informed decisions, enable operational efficiency, and ensure a seamless customer experience.

Have you ever wondered about your IT team’s efficiency in detecting incidents? Your Mean Time to Detect (MTTD) is an incident management Key Performance Indicator (KPI) that reveals your productivity during the first stage of incident resolution and enables investigation into opportunities for improvement. ITOps and DevOps teams that can lower their MTTD can more quickly identify issues, minimize potential downtime, and maintain system reliability too.

A wise person once said, “What’s measured is what matters.” This couldn’t be more true than in the high-stakes world of IT operations, where the ability to swiftly measure, analyze, and respond to events is crucial for improving IT operational performance. This blog delves into defining IT event analytics, guiding you on getting started, showcasing real-world examples, and introducing essential methods to transforming your incident response strategy.

In the quest for a high-velocity development environment, one fundamental question looms large: "How can you ensure an exceptional end-user experience when an array of engineers continually push and deploy code?" The unequivocal answer to this pivotal inquiry lies in the establishment of robust, straightforward, and well-defined monitoring practices.

Constantly juggling IT incidents can be exhausting as you try to track and resolve them before they escalate into disruptions. With each incident demanding prompt and precise attention, keeping up takes significant work. However, you can manage these challenges more efficiently and with less stress and less risk by optimizing your incident-tracking process.

Fault incidents are inevitable. They occur in any large-scale enterprise IT environment, especially when: In fact, research indicates, more than half (50%) the leaders in tech and business organizations consider the complexity of their data architecture a significant pain point. From an end-user perspective, businesses must overcome complex architecture in order to ensure service delivery and continuity.

Although FireHydrant has spent five years focused on what happens after your team (erg, I mean service 🙄) gets paged, the topic of alerting often comes up in discussions with our community. People are tired of paying big bucks for software that’s expensive, bloated, and hasn’t seen much innovation. Clearly, there’s a problem here – and we’re tackling it head on.

With the increasing complexity of technology stacks and monitoring tools, managing incidents can become overwhelming, leading to alert noise, alert fatigue, and delayed responses. This is where Key-Based Deduplication comes to the rescue, streamlining incident handling and enhancing the effectiveness of your Incident Management platform.