In an era where digital infrastructures are increasingly hybrid, the ability to efficiently monitor, analyze, and act on vast amounts of operational data is a significant challenge. According to Gartner, the surge in data volumes, with some workloads producing petabytes of telemetry annually, has led to heightened complexity and soaring costs—potentially exceeding $10 million annually for large enterprises.

Open Shortest Path First (OSPF) is a standard routing protocol that’s been used the world over for many years. Supported by practically every routing vendor, as well as the open source community, OSPF is one of the few protocols in the IT industry you can count on being available just about anywhere you might need it. Enterprise networks that outgrow a single site will often use OSPF to interconnect their campuses and wide area networks (WANs).

Predictive analytics has become a key goal in observability. If teams can foresee potential system failures, performance bottlenecks, or resource constraints before they happen, they can act preemptively to mitigate issues. AI holds the promise of making this possible. In this post, we explore how AI can push observability toward predictive analytics, the industry’s current hurdles, and practical use cases for leveraging AI today.

You hear us at Percepio talking about Observability a lot. For customers using our award-winning Tracealyzer tool, this might sound a bit strange – isn’t Tracealyzer about diagnostics, debugging and profiling? Mostly, yes, but let me share why we are putting so much emphasis on our Continuous Observability solutions.

Engineering teams are always shipping something—new services, resources, models, clusters, etc. You probably have a set of standards you expect developers to abide by when doing that work, like adequate testing, code coverage, resolution of outstanding vulnerabilities, etc. But how are you actually tracking and enforcing those standards? Without an Internal Developer Portal, you might find that to be an incredibly manual effort.

In today’s complex IT environments, logs are the unsung heroes of infrastructure management. They hold a wealth of information that can mean the difference between reactive firefighting and proactive performance tuning. Log analysis is a process in modern IT and security environments that involves collecting, processing, and interpreting log information generated by computer systems. These systems include the various applications and devices on a business network.

Businesses in many industries turn to MetricFire for one goal: to quickly set up hosted monitoring with an expert team. Developers everywhere ask, "Will setting up a monitoring solution with a free trial be worth my time?" How can you find the right monitoring solution for your use case? This article will review some common monitoring use cases for online retail and ecommerce businesses. If any part of this article rings true for your business, click here to contact us.

Email round-trip monitoring is a powerful tool that tracks the full journey of an email from when it is sent to when it is successfully received. This comprehensive monitoring provides real-time insights into the performance and reliability of email systems, helping to identify issues that could affect uptime, deliverability, and overall communication efficiency.

AIOps monitoring is a proactive process that uses AI to anticipate and identify IT infrastructure issues. Going beyond traditional troubleshooting, it enables your systems to detect anomalies in advance to prevent potential disruptions. AIOps uses advanced technology like AI and machine learning to simplify IT operations. AIOps monitoring collects and analyzes large data sets from diverse sources, such as logs, metrics, and events.