In the realm of IT, incidents are inevitable. However, the true test of an organization's resilience lies in its ability to mitigate the impact of these incidents. Traditional incident management focused mainly on reducing downtime, but as we evolve in our approach, it's become evident that minimizing the damage and costs incurred during downtime is equally crucial.

As we reach the end of our blog series on the occurrences in 2023 from the fourth installment of our blog series, Restore: Repair vs. Root Cause, the unavoidable truth is that incidents are a universal challenge for organisations, regardless of their scale or field. In the APAC region, there’s a noticeable increase in regulatory bodies imposing strict penalties on major companies for service failures.

Securing reliable system operation necessitates building a formidable Site Reliability Engineering (SRE) team. However, a critical strategic decision confronts every organization: do we cultivate SRE talent internally or venture into the external talent pool? Both approaches possess distinct advantages and disadvantages, each impacting the composition, skillset, and overall effectiveness of the SRE team.

Did Microsoft Teams chat seem a little quieter on Friday, January 26th? Maybe messages seemed to be coming in choppily or delayed – possibly some issues logging into Teams. It wasn’t a coincidence, Microsoft Teams started experiencing issues earlier in the day and at 11:45 a.m. ET issued incident TM710344 with the following message on X – formerly known as Twitter.

In the fast-paced landscape of technology, AI-driven Incident Management and Site Reliability Engineering (SRE) have emerged as critical components in ensuring the seamless functioning of digital systems. AI algorithms are increasingly employed to detect, diagnose, and resolve incidents with unprecedented speed and efficiency, revolutionizing the traditional approaches to reliability.

When you’re in the thick of an incident, communication is both essential and challenging. A wide variety of stakeholders will need timely updates on the situation in order to respond effectively. At the same time, breaking away from the actual diagnostic and resolving work to send these updates can massively slow progress.

Today, any revenue-generating website is like a house of cards, poised to collapse with multiple points of failure. The modern service delivery chain relies on intricate multi-step transactions and third-party API integrations, making the system more complex and interconnected. A single point of failure in the architectural diagram above can lead to slowdowns and outages with tangible consequences on your bottom line.

In the world of IT monitoring and IoT systems, it is crucial to alert users promptly and reliably about critical issues. Whether it’s about security and ongoing systems at the workplace, in public facilities, or other places, the way in which alarm notifications are delivered can make the difference between chaos and an organized response in an emergency.

Quickly finding and resolving monitoring anomalies can make all the difference between service issues – and service excellence. But it’s far from easy, whether you’re trying to sift through countless alerts, understand the context behind anomalies, or swiftly pinpoint their root causes. If you’re an ITOps practitioner or enterprise architect looking to fine-tune your anomaly detection and resolution skills, you’ve come to the right place.

Often we receive a series of alerts that get auto-resolved within a short period of time. Such alerts are called flapping or transient alerts. In this blog, we'll explore Auto Pause transient alert (APTA) feature that detects flapping alerts and temporarily pause incident notifications hence reducing alert fatigue.