Cloud services make the daily tasks of business easier. They enable remote workforce collaboration, streamline administrative tasks, and reduce capital costs. However, these “pros” come with a few “cons.” The IT stack’s increased complexity means staff work across divergent log management tools when something breaks. Centralized log management for the cloud makes root cause analysis easier by aggregating all event log data in a single location.

We built LogDNA around the idea that developers are more productive when they have access to all of the logs they need, when they need them. However, we also know that log management can get expensive fast. And, for anyone who owns the budget for developer tools, logs can be an unpredictable line item as you try to determine your monthly, quarterly or even annual spend.

Any organization with data assets is a possible target for an attacker. Hackers use various forms of advanced cyberattack techniques to obtain valuable company data; in fact, a study by the University of Maryland showed that a cyberattack takes place every 39 seconds, or 2,244 times a day on average. This number has increased exponentially since the COVID-19 pandemic forced most employees to work remotely, and drastically increased the attack surface of organizations around the world.

LogDNA recently celebrated 5 years since our launch in Y Combinator and during this half-a-decade we’ve learned several lessons about balancing cost and scalability. As a founder, here are the top 3 things I wish someone had told me as we were racing towards success. The appeal of building a cloud-native application for a startup is a no brainer—it’s agile, scalable, and can be managed by a distributed team. Not to mention, it’s the cheapest way to get off the ground.

If you’re investigating an incident, every minute means degraded performance or even downtime for customers. The causes of an issue often come from parts of your systems and applications that you would not think to check, and the sooner you can bring these to light, the better.

We first released the usage insights Enterprise feature in Grafana 7.0 based on feedback from customers that they would like to better understand how their users are interacting with Grafana, including the dashboards they visit, the information they query, and where they run into issues. What we learned was that dashboard sprawl is a real issue: Administrators estimate that almost 60% of dashboards might not be used at all.

Troubleshooting an application running on Google Kubernetes Engine (GKE) often means poking around various tools to find the key bit of information in your logs that leads to the root cause. With Cloud Operations, our integrated management suite, we’re working hard to provide the information that you need right where and when you need it. Today, we’re bringing GKE logs closer to where you are—in the Cloud Console—with a new logs tab in your GKE resource details pages.

Metricbeat, an Elastic Beat based on the libbeat framework from Elastic, is a lightweight shipper that you can install on your servers to periodically collect metrics from the operating system and from services running on the server. Everything from CPU to memory, Redis to NGINX, etc… Metricbeat takes the metrics and statistics that it collects and ships them to the output that you specify, such as Elasticsearch or Logstash.