At Sumo Logic, we’re committed to helping you scale without breaking your budget. As you may have heard, we recently launched Flex Licensing, a first-of-its-kind economic model that offers free, unlimited log data ingest so different teams can capture and analyze critical data across their enterprise in one place. We’re also committed to tackling related challenges raised by other data sources — like metrics.

While major outages like the recent CrowdStrike incident dominate headlines, those of us in the trenches ensuring Internet Resilience know that most of our issues are not necessarily global but localized by geography, autonomous systems, or something else. Micro-outages – those elusive, localized incidents – can pose the most persistent threat to observability.

Handling resource allocation within Kubernetes clusters is of paramount importance. Proper resource allocation in Kubernetes ensures optimal performance and efficient utilization of the underlying infrastructure, safeguarding against capacity issues and application downtime. In contrast, improper resource allocation can lead to a plethora of challenges, from wasted resources to compromised application performance.

Finding the right automation tool for Windows environments can be frustrating. Legacy systems, a GUI-centric design, and proprietary tooling are a few of the reasons automating Windows infrastructure can be challenging – especially in environments where Windows isn’t the only OS. Many organizations struggle to choose tools that will let them automate Windows infrastructure without contributing to tool sprawl.

There is immense pressure on IT. Now more than ever, IT teams bear the brunt of the seismic shift in how people live and work. Delivering service quality while driving innovation is imperative. Yet, IT teams are continually fighting outage fires, managing day-to-day events, updating legacy systems, and navigating IT complexity – while trying to innovate. AIOps and cloud computing sought to address these challenges.

Monitoring and Observability of messaging and middleware has and will continue to be a function of increasing importance and this is especially true for organizations in the Financial Services industry. In the financial services industry, observability refers to the ability to monitor, measure, and analyze the performance, health, and security of financial systems, applications, messaging and middleware which power long running processes in real-time.

When an ambulance is dispatched to a call, the assumption is that it will be fully stocked with the right equipment and medicines for emergency medical technicians, EMTs for short, to stabilize patients or perform life-saving measures in the field. But with the increased number of calls for service in many parts of the world, it’s becoming more difficult for EMTs to maintain proper stock in their ambulances – and that has patient care implications.

When discussing the technical foundations of observability, several key components, often referred to as the “pillars,” emerge. While there is no universally agreed-upon number of pillars, this post will focus on four fundamental elements: metrics, logs, traces, and profiles. Due to the vast amount of data generated by metrics, logs, and traces, sampling is often employed to reduce data volume while maintaining representative information.

A few weeks ago we released a feature on IncidentHub which gives you a historical view of your monitored services' availability.

Performance testing is a form of software testing that focuses on how a system running the system performs under a particular load. This type of test is not about finding software bugs or defects. Different performance testing types measures according to benchmarks and standards. Performance testing gives developers the diagnostic information they need to eliminate bottlenecks. In this article you will learn about.