Monitoring is often not the first thing on the mind of the modern developer. Yet, it’s necessary at many points of the software development lifecycle, including: before deprecating an API, before launching a new feature, after launching the feature, and more. In fact, monitoring needs can vary much more than the classic Ops monitoring. My podcast guest Liran Haimovitch is the co-founder and CTO of Rookout, a live data collection and debugging platform.

On May 27, 2022, an interesting Microsoft Word doc was uploaded to VirusTotal by an independent security research team called nao_sec. The Word doc contains built-in code that calls an HTML file from a remote source that in-turn executes more (malicious) code and Microsoft Defender for Endpoint misses detection. Two days later, May 29, Kevin Beaumont publishes an article describing the behavior of this Word doc, and deems this a new 0-day vulnerability in Office/Windows products.

From the moment Elastic announced plans to abandon a pure open source license for its Elasticsearch engine and Kibana dashboards in early 2021, there’s been a massive effort underway to create clear alternatives for the global community of active users. Logz.io has been an outspoken advocate and contributor to this work – fully embracing it as part of our product roadmap to best serve the needs of our customers, and preserve our long-term commitment to open source observability.

In this tutorial, we will go through a working example of a NestJS application auto-instrumented with OpenTelemetry. In our example we will use a simple application that outputs “Hello World!” when we call it in the browser. We will instrument this application with OpenTelemetry’s Node.js client library to generate trace data and send it to an OpenTelemetry Collector. The Collector will then export the trace data to an external distributed tracing analytics tool of our choice.

After creating your Logz.io account, the first step for onboarding is to send you log, metric, and trace data. Logz.io makes this flexible – allowing for multiple ways to get data into your Logz.io account depending on your use case and technology stack. Today, we’re excited to announce another easy and fast way to get AWS metric data into Logz.io: by setting up a CloudWatch metrics stream and a Kinesis Firehose.

Regardless of economic conditions, IT usually operates under an axiom no one in business ever likes to hear: “We have to do more with less.” Doing more with less is essentially the default position for IT, but when it comes to security operations, that position can have real consequences.

When you migrated critical infrastructure to the cloud, what were your goals and expectations? Odds are, you hoped leaving on-premises infrastructure would produce significant organizational benefits. You probably figured you’d streamline operations and reduce management overhead. You felt you’d have an easier time meeting business goals. Perhaps most important of all, you likely expected your environment would become less complex, and even cost less to operate.

For the last five years, Logz.io has tracked and measured the pulse of DevOps, as well as adoption of key trends and technology, through our DevOps Pulse survey and report. One of the obvious focus areas for us, as a company whose products are based on industry-leading open source, is the increased rise of incredibly useful open-source observability solutions, in general.

Elasticsearch has long been the prominent solution for log management and analytics. Cloud-native and microservices architectures, together with the surge in workload volumes and diversity, have surfaced some challenges for web-scale enterprises such as Slack and Twitter. My podcast guest Suman Karumuri, a Sr. Staff software engineer at Slack, has made a career on solving this problem. In my chat with Suman, he discusses for the first time in a public space a new project from his team at Slack: KalDB.

Oh how quickly the times change. Over the past 5 years, as Logz.io has executed its annual DevOps Pulse Survey and created the accompanying report, the state of “modern” cloud engineering and monitoring practices have advanced at a torrid pace. As a result, so has the project itself. Back in 2017 when we started polling the industry and collecting data, we sought to validate the usefulness of DevOps itself.