The million-dollar question we are hearing on an almost daily basis is ‘when will we have a vaccine for COVID-19?’. According to many sources, including the New York Times, it may still be a long way off. This means the prospect of living in the ‘new normal’ is something we may need to accept and adapt to for quite some time.
Financial services is no stranger to disruption. From fintech to blockchain and beyond, the industry has bobbed and weaved through a decade of constant change. The good news is that this experience makes the industry uniquely positioned to lead through the challenges of COVID-19. The bad news is that those financial organizations that can’t rise to the task can lose the trust of customers counting on them in their time of need.
Think about it. Without the efforts of communication service providers (CSPs) who handled a massive surge in traffic patterns, it would be much more difficult to work from home, learn online, or binge Tiger King. However, while they rose to the challenge, it also exposed the need for more agility in communications operations, sparking a renewed focus on the need for service transformation.
Ten years ago NewRelic, DataDog, Splunk, Dynatrace and SolarWinds built tools we loved to use. They were easy to implement and solved problems quickly and efficiently. Each company was known primarily for a single, well-conceived product. NewRelic’s APM. Splunk’s log file analyzer. DataDog’s server monitor. SolarWinds’ network performance monitor. These companies were beloved by users during the 2000s. Fast forward to 2020 and the world is very different.
GrafanaCONline wrapped up last Friday, and we were thrilled to have so many of you join the sessions over the past three weeks. Thank you for tuning in, asking questions, chatting on Slack, and generally making our reimagined conference a success.
At LogicMonitor, we deal primarily with large quantities of time series data. Customer devices are monitored at regular intervals and data points are provided to our agentless application to be processed and interpreted. Recently, we’ve endeavored to expand the presence of machine learning in our application to enhance anomaly detection.
