Operations | Monitoring | ITSM | DevOps | Cloud

A classic problem that every backend developer has faced during their work is testing an application that uses a database. A perfectly valid solution is to use the real database for testing your application, but you would be doing an integration test, while you want a unit test. There are many ways to solve this problem. You could create the database with docker, or use an in-memory compatible one, but if you are writing unit tests that can be easily parallelized this will become quite uncomfortable.

In this second installment of this blog series, we’ll discuss the importance of analyzing metrics, and how AIOps helps you with this fundamental pillar of observability. Without proper metrics analysis, you’re left blind to potential outages, or possibly worse — inundated with false positive anomalies, leading to alert fatigue and ultimately business impacts. Automated discovery and analysis can’t be achieved with legacy tools nor will it scale with humans.

Unplanned downtime can drive significant losses in the form of unrealized revenue. Teams may be caught off guard, or may face an outage outside their control, extending downtime hours unnecessarily. Without automated monitoring and alerting, teams face undetected outages that silently threaten SLA fulfillment. The recommendations in this report are best used as a guide on what trends may drive Site Reliability Engineering in the near term.

Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. This week, we delve into how organizations are increasingly adopting a remote work model, and how they can equip themselves to build a synchronized virtual workspace. In the wake of COVID-19 and the subsequent mandates to stay at home, many organizations have implemented a remote work environment in order to maintain business operations.