Oftentimes, security attacks that were clearly recorded in logs go unnoticed. They are obscured by a large sea of log data created by most modern cloud environments. In some cases, like during a DDoS attack, there will be a huge spike in logs so it will be very clear what happened. In other situations, just a few logs will document the attack. Finding these logs can be like finding a needle in a hay stack. But if you know what to looks for, it doesn’t need to be so hard to spot these attacks.

Java is a well-established object-oriented programming language that epitomizes cross-platform software development and helped to popularize the “write once, run anywhere” (WORA) concept. Java runs on billions of devices worldwide and powers a huge range of important software, such as the popular Android operating system and Elasticsearch. In this tutorial, we will go over how to manage Java logs with the ELK Stack and Logz.io.

Open source grafana is one of the most popular OSS UI for metrics and infrastructure monitoring today. Capable of ingesting metrics from the most popular time series databases, it’s an indispensable tool in modern DevOps. This OSS grafana tutorial will go over installation, configuration, queries, and initial metrics shipping. Open source grafana is the equivalent of what Kibana is for logs (for more, see Grafana vs. Kibana).

We have been busy adding new features to our growing list of abilities. Logz.io Cloud SIEM is no exception. Throughout 2020 we have been enriching our security incident and event management tool, refining threat intelligence, adding new dashboards, and improving the user experience to ensure there’s an eagle’s-eye view of the security challenges that organizations face. Here are a few of those updates that we have recently put to production.

In the field of open-source metrics and time series monitoring, it is quite clear today that Grafana is the most popular tool of choice. One of Grafana’s main advantages is its storage backend flexibility. It can support almost all the major time series datastores (Prometheus, InfluxDB, Elasticsearch, Graphite etc.), when each datastore has its own query language syntax, and slight differences in the actual Grafana UI and capabilities resulting from these differences.

Logs, metrics and traces are the three pillars of the Observability world. The distributed tracing world, in particular, has seen a lot of innovation in recent months, with OpenTelemetry standardization and with Jaeger open source project graduating from the CNCF incubation. According to the recent DevOps Pulse report, Jaeger is used by over 30% of those practicing distributed tracing.

Holler is a messaging tech company that enriches conversations everywhere by creating and delivering useful, entertaining, expressive visual content to add texture and emotion to messaging environments. As the company has continued to grow, the engineering organization has scaled to meet the demand for its services. However, without a fully staffed Operations team, most of the engineers at Holler perform double duty across DevOps to keep the service performant for consumers.

At Logz.io, we’ve built our Log Management solution on the ELK Stack because we know it’s what modern engineering teams prefer. It’s familiar, powerful, and integrates easily with other DevOps and cloud technologies. That’s what makes migrating from ELK to Logz.io a seamless process. This means current ELK users can easily transition to Logz.io. If you’re currently using ELK, you can ship the same data using exactly the same shipping mechanisms.