If you’re running a fleet of containerized applications on Kubernetes, aggregating and analyzing your logs can be a bit daunting if you’re not equipped with the proper knowledge and tools. Thankfully, there’s plenty of useful documentation to help you get started; observIQ provides the tools you need to gather and analyze your application logs with ease.
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.
With our ability to ingest GCP logs and metrics into Splunk and Splunk Infrastructure Monitoring, there’s never been a better time to start driving value out of your GCP data. We’ve already started to explore this with the great blog from Matt here: Getting to Know Google Cloud Audit Logs. Expanding on this, there’s now a pre-built set of dashboards available in a Splunkbase App: GCP Application Template for Splunk!
Logz.io has always prided itself as a company pushing the use of open source tech. As we have moved to expand our reach with metrics and traces over the past year and a half, we have doubled down on our own contributions to the community. With (distributed) traces in particular, we have been able to forge ahead. Our relationship with the teams at Jaeger and OpenTelemetry have really blossomed (and we are kind of proud to have supported the latter in the run-up to the OpenTelemetry v1.0 release).
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.
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.
